Page last updated: 2024-08-03 21:03:30
gkt137831
Description
setanaxib: NOX4/NOX1 inhibitor; a pyrazolopyridine dione derivative [MeSH]
Cross-References
ID Source | ID |
PubMed CID | 58496428 |
CHEMBL ID | 4303187 |
SCHEMBL ID | 1302603 |
MeSH ID | M0579465 |
Synonyms (40)
Synonym |
SCHEMBL1302603 |
setanaxib |
unii-45ii35329v |
2-(2-chlorophenyl)-4-(3-(dimethylamino)phenyl)-5-methyl-1h-pyrazolo(4,3-c)pyridine-3,6(2h,5h)-dione |
1218942-37-0 |
45ii35329v , |
gkt-831 |
gkt 137831 |
gkt-137831 |
gkt137831 |
S7171 |
setanaxib [inn] |
1h-pyrazolo(4,3-c)pyridine-3,6(2h,5h)-dione, 2-(2-chlorophenyl)-4-(3-(dimethylamino)phenyl)-5-methyl- |
HY-12298 |
CS-3290 |
AKOS022176138 |
2-(2-chlorophenyl)-4-(3-(dimethylamino)phenyl)-5-methyl-1h-pyrazolo[4,3-c]pyridine-3,6(2h,5h)-dione |
AC-33132 |
DTXSID30153432 |
J-690070 |
mfcd27923122 |
EX-A577 |
AS-74753 |
2-(2-chlorophenyl)-4-[3-(dimethylamino)phenyl]-5-methyl-1h,2h,3h,5h,6h-pyrazolo[4,3-c]pyridine-3,6-dione |
NCGC00378460-08 |
NCGC00378460-09 |
2-(2-chlorophenyl)-4-[3-(dimethylamino)phenyl]-5-methylpyrazolo[4,3-c]pyridine-3,6(2h,5h)-dione |
gkt831 |
gtpl9932 |
2-(2-chlorophenyl)-4-[3-(dimethylamino)phenyl]-5-methyl-1h-pyrazolo[4,3-c]pyridine-3,6-dione |
FT-0700121 |
BCP14159 |
1h-pyrazolo[4,3-c]pyridine-3,6(2h,5h)-dione, 2-(2-chlorophenyl)-4-[3-(dimethylamino)phenyl]-5-methyl- |
SB19230 |
CCG-268595 |
CHEMBL4303187 |
Q27258840 |
2-(2-chlorophenyl)-4-(3-(dimethylamino)phenyl)-5-methyl-1,2-dihydro-3h-pyrazolo[4,3-c]pyridine-3,6(5h)-dione |
NCGC00378460-05 |
EN300-20043919 |
Protein Targets (7)
Potency Measurements
Bioassays (9)
Assay ID | Title | Year | Journal | Article |
AID1296008 | Cytotoxic Profiling of Annotated Libraries Using Quantitative High-Throughput Screening | 2020 | SLAS discovery : advancing life sciences R & D, 01, Volume: 25, Issue:1 ISSN: 2472-5560 | Cytotoxic Profiling of Annotated and Diverse Chemical Libraries Using Quantitative High-Throughput Screening. |
AID1347160 | Primary screen NINDS Rhodamine qHTS for Zika virus inhibitors | 2020 | Proceedings of the National Academy of Sciences of the United States of America, 12-08, Volume: 117, Issue:49 ISSN: 1091-6490 | Therapeutic candidates for the Zika virus identified by a high-throughput screen for Zika protease inhibitors. |
AID1347159 | Primary screen GU Rhodamine qHTS for Zika virus inhibitors: Unlinked NS2B-NS3 protease assay | 2020 | Proceedings of the National Academy of Sciences of the United States of America, 12-08, Volume: 117, Issue:49 ISSN: 1091-6490 | Therapeutic candidates for the Zika virus identified by a high-throughput screen for Zika protease inhibitors. |
AID1347411 | qHTS to identify inhibitors of the type 1 interferon - major histocompatibility complex class I in skeletal muscle: primary screen against the NCATS Mechanism Interrogation Plate v5.0 (MIPE) Libary | 2020 | ACS chemical biology, 07-17, Volume: 15, Issue:7 ISSN: 1554-8937 | High-Throughput Screening to Identify Inhibitors of the Type I Interferon-Major Histocompatibility Complex Class I Pathway in Skeletal Muscle. |
AID1508591 | NCATS Rat Liver Microsome Stability Profiling | 2020 | Scientific reports, 11-26, Volume: 10, Issue:1 ISSN: 2045-2322 | Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models. |
AID1508612 | NCATS Parallel Artificial Membrane Permeability Assay (PAMPA) Profiling | 2017 | Bioorganic & medicinal chemistry, 02-01, Volume: 25, Issue:3 ISSN: 1464-3391 | Highly predictive and interpretable models for PAMPA permeability. |
AID1346987 | P-glycoprotein substrates identified in KB-8-5-11 adenocarcinoma cell line, qHTS therapeutic library screen | 2019 | Molecular pharmacology, 11, Volume: 96, Issue:5 ISSN: 1521-0111 | A High-Throughput Screen of a Library of Therapeutics Identifies Cytotoxic Substrates of P-glycoprotein. |
AID1346986 | P-glycoprotein substrates identified in KB-3-1 adenocarcinoma cell line, qHTS therapeutic library screen | 2019 | Molecular pharmacology, 11, Volume: 96, Issue:5 ISSN: 1521-0111 | A High-Throughput Screen of a Library of Therapeutics Identifies Cytotoxic Substrates of P-glycoprotein. |
AID1645848 | NCATS Kinetic Aqueous Solubility Profiling | 2019 | Bioorganic & medicinal chemistry, 07-15, Volume: 27, Issue:14 ISSN: 1464-3391 | Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity. |
Research
Studies (59)
Timeframe | Studies, This Drug (%) | All Drugs % |
pre-1990 | 0 (0.00) | 18.7374 |
1990's | 0 (0.00) | 18.2507 |
2000's | 0 (0.00) | 29.6817 |
2010's | 39 (66.10) | 24.3611 |
2020's | 20 (33.90) | 2.80 |
Study Types
Publication Type | This drug (%) | All Drugs (%) |
Trials | 4 (6.67%) | 5.53% |
Reviews | 5 (8.33%) | 6.00% |
Case Studies | 0 (0.00%) | 4.05% |
Observational | 0 (0.00%) | 0.25% |
Other | 51 (85.00%) | 84.16% |
Substance | Studies | Classes | Roles | First Year | Last Year | Average Age | Relationship Strength | Trials | pre-1990 | 1990's | 2000's | 2010's | post-2020 |
b 844-39 | | diarylmethane | | 2017 | 2017 | 7.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
pk 11195 | | aromatic amide; isoquinolines; monocarboxylic acid amide; monochlorobenzenes | antineoplastic agent | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
jtv519 | | | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
alprazolam | | organochlorine compound; triazolobenzodiazepine | anticonvulsant; anxiolytic drug; GABA agonist; muscle relaxant; sedative; xenobiotic | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
dan 2163 | | aromatic amide; aromatic amine; benzamides; pyrrolidines; sulfone | environmental contaminant; second generation antipsychotic; xenobiotic | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
amlexanox | | monocarboxylic acid; pyridochromene | anti-allergic agent; anti-ulcer drug; non-steroidal anti-inflammatory drug | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
astemizole | | benzimidazoles; piperidines | anti-allergic agent; anticoronaviral agent; H1-receptor antagonist | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
benzbromarone | | 1-benzofurans; aromatic ketone | uricosuric drug | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
bisindolylmaleimide i | | | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
bufexamac | | aromatic ether; hydroxamic acid | antipyretic; non-narcotic analgesic; non-steroidal anti-inflammatory drug | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
cadralazine | | organic molecular entity | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
carvedilol | | carbazoles; secondary alcohol; secondary amino compound | alpha-adrenergic antagonist; antihypertensive agent; beta-adrenergic antagonist; cardiovascular drug; vasodilator agent | 2019 | 2020 | 4.5 | low | 0 | 0 | 0 | 0 | 2 | 0 |
cetirizine | | ether; monocarboxylic acid; monochlorobenzenes; piperazines | anti-allergic agent; environmental contaminant; H1-receptor antagonist; xenobiotic | 2019 | 2020 | 4.5 | low | 0 | 0 | 0 | 0 | 2 | 0 |
chlorcyclizine | | diarylmethane | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
ci 994 | | acetamides; benzamides; substituted aniline | antineoplastic agent; EC 3.5.1.98 (histone deacetylase) inhibitor | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
cyclosporine | | | | 2017 | 2020 | 5.5 | high | 0 | 0 | 0 | 0 | 2 | 0 |
fenbendazole | | aryl sulfide; benzimidazoles; carbamate ester | antinematodal drug | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
berotek | | resorcinols; secondary alcohol; secondary amino compound | beta-adrenergic agonist; bronchodilator agent; sympathomimetic agent; tocolytic agent | 2017 | 2017 | 7.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
go 6976 | | indolocarbazole; organic heterohexacyclic compound | EC 2.7.11.13 (protein kinase C) inhibitor | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
haloperidol | | aromatic ketone; hydroxypiperidine; monochlorobenzenes; organofluorine compound; tertiary alcohol | antidyskinesia agent; antiemetic; dopaminergic antagonist; first generation antipsychotic; serotonergic antagonist | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
homochlorocyclizine | | diarylmethane | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
hydroxyzine | | hydroxyether; monochlorobenzenes; N-alkylpiperazine | anticoronaviral agent; antipruritic drug; anxiolytic drug; dermatologic drug; H1-receptor antagonist | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
ifenprodil | | piperidines | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
1-(2-naphthalenyl)-3-[(phenylmethyl)-propan-2-ylamino]-1-propanone | | naphthalenes | | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
ketamine | | cyclohexanones; monochlorobenzenes; secondary amino compound | analgesic; environmental contaminant; intravenous anaesthetic; neurotoxin; NMDA receptor antagonist; xenobiotic | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
ketoprofen | | benzophenones; oxo monocarboxylic acid | antipyretic; drug allergen; EC 1.14.99.1 (prostaglandin-endoperoxide synthase) inhibitor; environmental contaminant; non-steroidal anti-inflammatory drug; xenobiotic | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
mebendazole | | aromatic ketone; benzimidazoles; carbamate ester | antinematodal drug; microtubule-destabilising agent; tubulin modulator | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
mephenesin | | aromatic ether; glycerol ether | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
niclosamide | | benzamides; C-nitro compound; monochlorobenzenes; salicylanilides; secondary carboxamide | anthelminthic drug; anticoronaviral agent; antiparasitic agent; apoptosis inducer; molluscicide; piscicide; STAT3 inhibitor | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
oxibendazole | | benzimidazoles; carbamate ester | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
4-(2'-methoxyphenyl)-1-(2'-(n-(2''-pyridinyl)-4-iodobenzamido)ethyl)piperazine | | | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
perphenazine | | N-(2-hydroxyethyl)piperazine; N-alkylpiperazine; organochlorine compound; phenothiazines | antiemetic; dopaminergic antagonist; phenothiazine antipsychotic drug | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
pimobendan | | benzimidazoles; pyridazinone | cardiotonic drug; EC 3.1.4.* (phosphoric diester hydrolase) inhibitor; vasodilator agent | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
ag 1879 | | aromatic amine; monochlorobenzenes; pyrazolopyrimidine | beta-adrenergic antagonist; EC 2.7.10.2 (non-specific protein-tyrosine kinase) inhibitor; geroprotector | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
3-[(3,5-dibromo-4-hydroxyphenyl)methylidene]-5-iodo-1H-indol-2-one | | indoles | | 2017 | 2020 | 5.5 | medium | 0 | 0 | 0 | 0 | 2 | 0 |
ro 31-8220 | | imidothiocarbamic ester; indoles; maleimides | EC 2.7.11.13 (protein kinase C) inhibitor | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
ropinirole | | indolones; tertiary amine | antidyskinesia agent; antiparkinson drug; central nervous system drug; dopamine agonist | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
vorinostat | | dicarboxylic acid diamide; hydroxamic acid | antineoplastic agent; apoptosis inducer; EC 3.5.1.98 (histone deacetylase) inhibitor | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
2-[4-(4-chloro-1,2-diphenylbut-1-enyl)phenoxy]-N,N-dimethylethanamine | | stilbenoid | | 2017 | 2020 | 5.5 | high | 0 | 0 | 0 | 0 | 2 | 0 |
trifluperidol | | aromatic ketone | | 2017 | 2017 | 7.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
3-(5'-hydroxymethyl-2'-furyl)-1-benzylindazole | | aromatic primary alcohol; furans; indazoles | antineoplastic agent; apoptosis inducer; platelet aggregation inhibitor; soluble guanylate cyclase activator; vasodilator agent | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
zotepine | | dibenzothiepine; tertiary amino compound | alpha-adrenergic drug; second generation antipsychotic; serotonergic drug | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
colchicine | | alkaloid; colchicine | anti-inflammatory agent; gout suppressant; mutagen | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
benziodarone | | aromatic ketone | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
cyclizine | | N-alkylpiperazine | antiemetic; central nervous system depressant; cholinergic antagonist; H1-receptor antagonist; local anaesthetic | 2019 | 2019 | 5.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
trehalose | | trehalose | Escherichia coli metabolite; geroprotector; human metabolite; mouse metabolite; Saccharomyces cerevisiae metabolite | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
triclocarban | | dichlorobenzene; monochlorobenzenes; phenylureas | antimicrobial agent; antiseptic drug; disinfectant; environmental contaminant; xenobiotic | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
4-tert-octylphenol | | alkylbenzene | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
ethamivan | | methoxybenzenes; phenols | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
methysergide | | ergoline alkaloid | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
emetine | | isoquinoline alkaloid; pyridoisoquinoline | antiamoebic agent; anticoronaviral agent; antiinfective agent; antimalarial; antineoplastic agent; antiprotozoal drug; antiviral agent; autophagy inhibitor; emetic; expectorant; plant metabolite; protein synthesis inhibitor | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
podophyllotoxin | | furonaphthodioxole; lignan; organic heterotetracyclic compound | antimitotic; antineoplastic agent; keratolytic drug; microtubule-destabilising agent; plant metabolite; tubulin modulator | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
etonitazene | | | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
clothiapine | | dibenzothiazepine | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
benperidol | | aromatic ketone | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
7-hydroxychlorpromazine | | phenothiazines | | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
camptothecin | | delta-lactone; pyranoindolizinoquinoline; quinoline alkaloid; tertiary alcohol | antineoplastic agent; EC 5.99.1.2 (DNA topoisomerase) inhibitor; genotoxin; plant metabolite | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
thenalidine | | dialkylarylamine; tertiary amino compound | | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
bromocriptine | | indole alkaloid | antidyskinesia agent; antiparkinson drug; dopamine agonist; hormone antagonist | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
dexchlorpheniramine | | chlorphenamine | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
dv 1006 | | | | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
climbazole | | aromatic ether; hemiaminal ether; imidazoles; ketone; monochlorobenzenes | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
triadimenol | | aromatic ether; conazole fungicide; hemiaminal ether; monochlorobenzenes; secondary alcohol; triazole fungicide | antifungal agrochemical; EC 1.14.13.70 (sterol 14alpha-demethylase) inhibitor; xenobiotic metabolite | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
amonafide | | isoquinolines | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
flupirtine | | aminopyridine | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
chaetochromin | | | | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
enoximone | | aromatic ketone | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
aripiprazole | | aromatic ether; delta-lactam; dichlorobenzene; N-alkylpiperazine; N-arylpiperazine; quinolone | drug metabolite; H1-receptor antagonist; second generation antipsychotic; serotonergic agonist | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
aloxistatin | | epoxide; ethyl ester; L-leucine derivative; monocarboxylic acid amide | anticoronaviral agent; cathepsin B inhibitor | 2019 | 2019 | 5.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
indocate | | | | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
N(4)-acetylsulfathiazole | | 1,3-thiazoles; acetamides; sulfonamide | marine xenobiotic metabolite | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
cyclizine hydrochloride | | | | 2017 | 2020 | 5.5 | medium | 0 | 0 | 0 | 0 | 2 | 0 |
2,3-trimethylene-4-quinazolone | | quinazolines | | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
1,3-dimethyluric acid | | oxopurine | metabolite | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
danofloxacin | | quinolines | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
nitrefazole | | imidazoles | | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
methotrimeprazine | | phenothiazines; tertiary amine | anticoronaviral agent; cholinergic antagonist; dopaminergic antagonist; EC 3.4.21.26 (prolyl oligopeptidase) inhibitor; non-narcotic analgesic; phenothiazine antipsychotic drug; serotonergic antagonist | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
honokiol | | biphenyls | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
9-methoxyellipticine | | | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
3-aminophenoxazone | | phenoxazine | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
3-deazaneplanocin | | | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
tryptanthrine | | alkaloid antibiotic; organic heterotetracyclic compound; organonitrogen heterocyclic compound | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
2-chlorodiazepam | | | | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
Polycartine B | | phenazines | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
aminoquinuride dihydrochloride | | | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
thioproperazine mesylate | | phenothiazines | | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
n(6)-(delta(2)-isopentenyl)adenine | | 6-isopentenylaminopurine | cytokinin | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
4-methyl-N-(phenylmethyl)benzenesulfonamide | | sulfonamide | | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
zpck | | | | 2019 | 2020 | 4.5 | low | 0 | 0 | 0 | 0 | 2 | 0 |
sr141716 | | amidopiperidine; carbohydrazide; dichlorobenzene; monochlorobenzenes; pyrazoles | anti-obesity agent; appetite depressant; CB1 receptor antagonist | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
(6R)-7-[4-(dimethylamino)phenyl]-N-hydroxy-4,6-dimethyl-7-oxohepta-2,4-dienamide | | aromatic ketone | | 2017 | 2020 | 5.5 | high | 0 | 0 | 0 | 0 | 2 | 0 |
fingolimod | | aminodiol; primary amino compound | antineoplastic agent; CB1 receptor antagonist; immunosuppressive agent; prodrug; sphingosine-1-phosphate receptor agonist | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
tesmilifene | | diarylmethane | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
sr 27897 | | indolyl carboxylic acid | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
n-(n-(3-carboxyoxirane-2-carbonyl)leucyl)isoamylamine | | leucine derivative | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
norketamine | | organochlorine compound | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
indatraline | | indanes | | 2019 | 2020 | 4.5 | low | 0 | 0 | 0 | 0 | 2 | 0 |
methotrexate | | dicarboxylic acid; monocarboxylic acid amide; pteridines | abortifacient; antimetabolite; antineoplastic agent; antirheumatic drug; dermatologic drug; DNA synthesis inhibitor; EC 1.5.1.3 (dihydrofolate reductase) inhibitor; immunosuppressive agent | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
salvinorin a | | organic heterotricyclic compound; organooxygen compound | metabolite; oneirogen | 2019 | 2019 | 5.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
4-diethoxyphosphorylmethyl-n-(4-bromo-2-cyanophenyl)benzamide | | | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
n,n-di-n-hexyl-2-(4-fluorophenyl)indole-3-acetamide | | phenylindole | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
l 741626 | | piperidines | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
dx 8951 | | pyranoindolizinoquinoline | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
tipifarnib | | imidazoles; monochlorobenzenes; primary amino compound; quinolone | antineoplastic agent; apoptosis inducer; EC 2.5.1.58 (protein farnesyltransferase) inhibitor | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
cyc 202 | | 2,6-diaminopurines | antiviral drug; EC 2.7.11.22 (cyclin-dependent kinase) inhibitor | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
avasimibe | | monoterpenoid | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
l 163191 | | | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
dizocilpine | | secondary amino compound; tetracyclic antidepressant | anaesthetic; anticonvulsant; neuroprotective agent; nicotinic antagonist; NMDA receptor antagonist | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
s-benzylcysteine | | S-aryl-L-cysteine zwitterion | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
chelidonine | | alkaloid antibiotic; alkaloid fundamental parent; benzophenanthridine alkaloid | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
lapatinib | | furans; organochlorine compound; organofluorine compound; quinazolines | antineoplastic agent; tyrosine kinase inhibitor | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
roxindole | | indoles | alpha-adrenergic antagonist; serotonergic drug | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
conidendrin | | | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
Porfiromycine | | mitomycin | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
nsc 95397 | | 1,4-naphthoquinones | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
4-methyl-2-quinazolinamine | | | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
2-glycineamide-5-chlorophenyl-2-pyrryl ketone | | | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
niguldipine hydrochloride | | | | 2019 | 2020 | 4.5 | medium | 0 | 0 | 0 | 0 | 2 | 0 |
2,5-bis(5-hydroxymethyl-2-thienyl)furan | | thiophenes | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
ritonavir | | 1,3-thiazoles; carbamate ester; carboxamide; L-valine derivative; ureas | antiviral drug; environmental contaminant; HIV protease inhibitor; xenobiotic | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
bardoxolone methyl | | cyclohexenones | | 2019 | 2019 | 5.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
Destruxin B | | cyclodepsipeptide | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
tosylphenylalanyl chloromethyl ketone | | alpha-chloroketone; sulfonamide | alkylating agent; serine proteinase inhibitor | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
trichostatin a | | antibiotic antifungal agent; hydroxamic acid; trichostatin | bacterial metabolite; EC 3.5.1.98 (histone deacetylase) inhibitor; geroprotector | 2019 | 2019 | 5.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
sitafloxacin | | fluoroquinolone antibiotic; quinolines; quinolone antibiotic | | 2019 | 2019 | 5.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
2'-c-methylcytidine | | | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
jp-1302 | | | | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
7-chloro-5,10-dihydrothieno[3,4-b][1,5]benzodiazepin-4-one | | benzodiazepine | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
tenatoprazole | | imidazopyridine | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
s 1033 | | (trifluoromethyl)benzenes; imidazoles; pyridines; pyrimidines; secondary amino compound; secondary carboxamide | anticoronaviral agent; antineoplastic agent; tyrosine kinase inhibitor | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
5-[(2-fluoroanilino)methyl]-8-quinolinol | | hydroxyquinoline | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
benidipine hydrochloride | | | | 2017 | 2020 | 5.5 | low | 0 | 0 | 0 | 0 | 2 | 0 |
benidipine | | | | 2019 | 2019 | 5.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
2-(1,3-benzoxazol-2-ylamino)-5-spiro[1,6,7,8-tetrahydroquinazoline-4,1'-cyclopentane]one | | quinazolines | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
chlorprothixene | | chlorprothixene | | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
jrf 12 | | | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
5-amino-3-(4-methoxyphenyl)-4-oxo-1-thieno[3,4-d]pyridazinecarboxylic acid ethyl ester | | methoxybenzenes; substituted aniline | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
3-hydroxypyridine, sodium salt | | | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
N-(3-cyano-4,5,6,7-tetrahydro-1-benzothiophen-2-yl)-1-naphthalenecarboxamide | | naphthalenecarboxamide | | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
5-[(2-bromoanilino)methyl]-8-quinolinol | | hydroxyquinoline | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
3-amino-n-(4-methoxybenzyl)-4,6-dimethylthieno(2,3-b)pyridine-2-carboxamide | | | | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
N-[(2-methoxyphenyl)methyl]-4-(1-piperidinyl)aniline | | aromatic amine | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
1-[4-(4-bromophenyl)-2-thiazolyl]-4-piperidinecarboxamide | | piperidinecarboxamide | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
5-[[2-(trifluoromethyl)anilino]methyl]-8-quinolinol | | hydroxyquinoline | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
N-[3-[2-[(4-methyl-2-pyridinyl)amino]-4-thiazolyl]phenyl]acetamide | | acetamides; anilide | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
5-bromo-N-(5-cyclohexyl-1,3,4-thiadiazol-2-yl)-2-thiophenecarboxamide | | aromatic amide; thiophenes | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
6-amino-1-[2-(3,4-dimethoxyphenyl)ethyl]-2-sulfanylidene-4-pyrimidinone | | dimethoxybenzene | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
N-[4-[(3,4-dimethyl-5-isoxazolyl)sulfamoyl]phenyl]-6,8-dimethyl-2-(2-pyridinyl)-4-quinolinecarboxamide | | aromatic amide | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
N-[5-[(4-chlorophenoxy)methyl]-1,3,4-thiadiazol-2-yl]-5-methyl-3-phenyl-4-isoxazolecarboxamide | | aromatic ether | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
3-chloro-1-(2,5-dimethoxyphenyl)-4-(1-piperidinyl)pyrrole-2,5-dione | | maleimides | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
Src Inhibitor-1 | | aromatic ether; polyether; quinazolines; secondary amino compound | EC 2.7.10.2 (non-specific protein-tyrosine kinase) inhibitor | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
1-[2-(3,4-dimethoxyphenyl)ethyl]-6-propyl-2-sulfanylidene-7,8-dihydro-5H-pyrimido[4,5-d]pyrimidin-4-one | | dimethoxybenzene | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
2-phenyl-N-[4-(2-thiazolylsulfamoyl)phenyl]-4-quinolinecarboxamide | | quinolines | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
3-(2,5-dimethyl-1-phenyl-3-pyrrolyl)-6,7,8,9-tetrahydro-5H-[1,2,4]triazolo[4,3-a]azepine | | pyrroles | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
bi-78d3 | | aryl sulfide | | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
kartogenin | | | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
toremifene | | aromatic ether; organochlorine compound; tertiary amine | antineoplastic agent; bone density conservation agent; estrogen antagonist; estrogen receptor modulator | 2019 | 2019 | 5.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
vx-745 | | aryl sulfide; dichlorobenzene; difluorobenzene; pyrimidopyridazine | anti-inflammatory drug; apoptosis inducer; EC 2.7.11.24 (mitogen-activated protein kinase) inhibitor | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
dasatinib | | 1,3-thiazoles; aminopyrimidine; monocarboxylic acid amide; N-(2-hydroxyethyl)piperazine; N-arylpiperazine; organochlorine compound; secondary amino compound; tertiary amino compound | anticoronaviral agent; antineoplastic agent; tyrosine kinase inhibitor | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
zd 6474 | | aromatic ether; organobromine compound; organofluorine compound; piperidines; quinazolines; secondary amine | antineoplastic agent; tyrosine kinase inhibitor | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
N-[2-(diethylamino)ethyl]-5-[(5-fluoro-2-oxo-1H-indol-3-ylidene)methyl]-2,4-dimethyl-1H-pyrrole-3-carboxamide | | indoles | | 2019 | 2020 | 4.5 | high | 0 | 0 | 0 | 0 | 2 | 0 |
nih-12848 | | | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
2,4-dioxo-3-pentyl-N-[3-(1-piperidinyl)propyl]-1H-quinazoline-7-carboxamide | | quinazolines | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
[1-(3-methylphenyl)-5-benzimidazolyl]-(1-piperidinyl)methanone | | benzimidazoles | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
2-[[(6-bromo-1H-imidazo[4,5-b]pyridin-2-yl)thio]methyl]benzonitrile | | imidazopyridine | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
3-[(3-fluorophenyl)methyl]-8-[4-(4-fluorophenyl)-4-oxobutyl]-1-phenyl-1,3,8-triazaspiro[4.5]decan-4-one | | aromatic ketone | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
4-[[7-[(4-fluorophenyl)methyl]-1,3-dimethyl-2,6-dioxo-8-purinyl]methyl]-1-piperazinecarboxylic acid ethyl ester | | oxopurine | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
N,N-dimethylcarbamodithioic acid (1-acetamido-2,2,2-trichloroethyl) ester | | organonitrogen compound; organosulfur compound | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
6-bromo-2-(4-methylphenyl)-N-[(1-methyl-4-pyrazolyl)methyl]-4-quinolinecarboxamide | | quinolines | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
LSM-1924 | | organic heterotricyclic compound; organooxygen compound | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
ferrostatin-1 | | ethyl ester; primary arylamine; substituted aniline | antifungal agent; antioxidant; ferroptosis inhibitor; neuroprotective agent; radiation protective agent; radical scavenger | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
6-(2-methyl-1-piperidinyl)-5-nitro-4-pyrimidinamine | | C-nitro compound | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
rabeprazole(1-) | | organic nitrogen anion | | 2019 | 2020 | 4.5 | high | 0 | 0 | 0 | 0 | 2 | 0 |
ncgc00099374 | | | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
2-nitro-4-[(6-nitro-4-quinolinyl)amino]-N-[4-(pyridin-4-ylamino)phenyl]benzamide | | benzamides | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
luteolin | | 3'-hydroxyflavonoid; tetrahydroxyflavone | angiogenesis inhibitor; anti-inflammatory agent; antineoplastic agent; apoptosis inducer; c-Jun N-terminal kinase inhibitor; EC 2.3.1.85 (fatty acid synthase) inhibitor; immunomodulator; nephroprotective agent; plant metabolite; radical scavenger; vascular endothelial growth factor receptor antagonist | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
cyclosporine | | | | 2019 | 2019 | 5.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
kaempferol | | 7-hydroxyflavonol; flavonols; tetrahydroxyflavone | antibacterial agent; geroprotector; human blood serum metabolite; human urinary metabolite; human xenobiotic metabolite; plant metabolite | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
genistein | | 7-hydroxyisoflavones | antineoplastic agent; EC 5.99.1.3 [DNA topoisomerase (ATP-hydrolysing)] inhibitor; geroprotector; human urinary metabolite; phytoestrogen; plant metabolite; tyrosine kinase inhibitor | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
mycophenolate mofetil | | carboxylic ester; ether; gamma-lactone; phenols; tertiary amino compound | anticoronaviral agent; EC 1.1.1.205 (IMP dehydrogenase) inhibitor; immunosuppressive agent; prodrug | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
bruceantin | | triterpenoid | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
chrysin | | 7-hydroxyflavonol; dihydroxyflavone | anti-inflammatory agent; antineoplastic agent; antioxidant; EC 2.7.11.18 (myosin-light-chain kinase) inhibitor; hepatoprotective agent; plant metabolite | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
daidzein | | 7-hydroxyisoflavones | antineoplastic agent; EC 2.7.7.7 (DNA-directed DNA polymerase) inhibitor; EC 3.2.1.20 (alpha-glucosidase) inhibitor; phytoestrogen; plant metabolite | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
neticonazole | | aromatic ether; benzenes; conazole antifungal drug; enamine; imidazole antifungal drug; imidazoles; methyl sulfide | antifungal drug; EC 1.14.13.70 (sterol 14alpha-demethylase) inhibitor | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
N-(4Z,7Z,10Z,13Z,16Z,19Z)-docosahexaenoylethanolamine | | endocannabinoid; N-acylethanolamine 22:6 | | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
n-oleoylethanolamine | | endocannabinoid; N-(long-chain-acyl)ethanolamine; N-acylethanolamine 18:1 | EC 3.5.1.23 (ceramidase) inhibitor; geroprotector; PPARalpha agonist | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
alpha-zearalenol | | macrolide | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
su 9516 | | | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
N-(4-bromo-3-methylphenyl)-2,5-dimethyl-[1,2,4]triazolo[1,5-a]pyrimidin-7-amine | | triazolopyrimidines | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
sb 277011 | | | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
sb 223412 | | | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
sr 59230a | | tetralins | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
3-[6-[4-(trifluoromethoxy)anilino]-4-pyrimidinyl]benzamide | | pyrimidines | | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
kn 62 | | piperazines | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
MeJA | | Jasmonate derivatives | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
1h-pyrrole-2,5-dione, 3-(1-methyl-1h-indol-3-yl)-4-(1-methyl-6-nitro-1h-indol-3-yl)- | | | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
pd 161570 | | | | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
su 11248 | | monocarboxylic acid amide; pyrroles | angiogenesis inhibitor; antineoplastic agent; EC 2.7.10.1 (receptor protein-tyrosine kinase) inhibitor; immunomodulator; neuroprotective agent; vascular endothelial growth factor receptor antagonist | 2017 | 2017 | 7.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
palbociclib | | aminopyridine; aromatic ketone; cyclopentanes; piperidines; pyridopyrimidine; secondary amino compound; tertiary amino compound | antineoplastic agent; EC 2.7.11.22 (cyclin-dependent kinase) inhibitor | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
jnj-7706621 | | sulfonamide | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
virginiamycin factor s1 | | cyclodepsipeptide; macrolide antibiotic | antibacterial drug; bacterial metabolite | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
fenoterol | | hydrobromide | beta-adrenergic agonist; bronchodilator agent; sympathomimetic agent | 2019 | 2020 | 4.5 | low | 0 | 0 | 0 | 0 | 2 | 0 |
xib 4035 | | | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
gw-5074 | | | | 2019 | 2019 | 5.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
belotecan | | pyranoindolizinoquinoline | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
norgestimate | | ketoxime; steroid ester; terminal acetylenic compound | contraceptive drug; progestin; synthetic oral contraceptive | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
b 43 | | aromatic amine; aromatic ether; cyclopentanes; primary amino compound; pyrrolopyrimidine | EC 2.7.10.2 (non-specific protein-tyrosine kinase) inhibitor; geroprotector | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
4-(2' methoxyphenyl)-1-(2'-(n-(2''-pyridinyl)-4-fluorobenzamido)ethyl)piperazine | | | | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
methiazole | | benzimidazoles; carbamate ester | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
sb 218795 | | quinolines | | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
bvt.948 | | | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
fk 866 | | benzamides; N-acylpiperidine | | 2019 | 2019 | 5.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
a 38503 | | | | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
parthenolide | | sesquiterpene lactone | drug allergen; inhibitor; non-narcotic analgesic; non-steroidal anti-inflammatory drug; peripheral nervous system drug | 2017 | 2019 | 6.0 | medium | 0 | 0 | 0 | 0 | 2 | 0 |
krn 633 | | | | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
5-amino-4-oxo-3-phenyl-1-thieno[3,4-d]pyridazinecarboxylic acid | | organonitrogen heterocyclic compound; organosulfur heterocyclic compound | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
gw 501516 | | 1,3-thiazoles; aromatic ether; aryl sulfide; monocarboxylic acid; organofluorine compound | carcinogenic agent; PPARbeta/delta agonist | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
dolastatin 10 | | 1,3-thiazoles; tetrapeptide | animal metabolite; antineoplastic agent; apoptosis inducer; marine metabolite; microtubule-destabilising agent | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
spc-839 | | | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
midostaurin | | benzamides; gamma-lactam; indolocarbazole; organic heterooctacyclic compound | antineoplastic agent; EC 2.7.11.13 (protein kinase C) inhibitor | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
valnemulin | | | | 2019 | 2020 | 4.5 | medium | 0 | 0 | 0 | 0 | 2 | 0 |
nu 7026 | | organic heterotricyclic compound; organooxygen compound | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
osi 930 | | aromatic amide | | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
ticagrelor | | aryl sulfide; hydroxyether; organofluorine compound; secondary amino compound; triazolopyrimidines | P2Y12 receptor antagonist; platelet aggregation inhibitor | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
l 692585 | | peptide | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
pi103 | | aromatic amine; morpholines; organic heterotricyclic compound; phenols; tertiary amino compound | antineoplastic agent; EC 2.7.1.137 (phosphatidylinositol 3-kinase) inhibitor; mTOR inhibitor | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
nnc 26-9100 | | aminopyridine | | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
2-(3-chlorobenzyloxy)-6-(piperazin-1-yl)pyrazine | | | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
tivozanib | | aromatic ether | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
hki 272 | | nitrile; quinolines | antineoplastic agent; tyrosine kinase inhibitor | 2019 | 2019 | 5.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
n-(6-chloro-7-methoxy-9h-beta-carbolin-8-yl)-2-methylnicotinamide | | | | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
tae226 | | morpholines | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
gw0742 | | monocarboxylic acid | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
u 18666a | | hydrochloride | antiviral agent; EC 1.3.1.72 (Delta(24)-sterol reductase) inhibitor; Hedgehog signaling pathway inhibitor; nicotinic antagonist; sterol biosynthesis inhibitor | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
sb 525334 | | quinoxaline derivative | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
bx795 | | ureas | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
azd 6244 | | benzimidazoles; bromobenzenes; hydroxamic acid ester; monochlorobenzenes; organofluorine compound; secondary amino compound | anticoronaviral agent; antineoplastic agent; EC 2.7.11.24 (mitogen-activated protein kinase) inhibitor | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
1-(2-(1-adamantyl)ethyl)-1-pentyl-3-(3-(4-pyridyl)propyl)urea | | | | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
bay 61-3606 | | pyrimidines | | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
sd-208 | | | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
crenolanib | | aminopiperidine; aromatic ether; benzimidazoles; oxetanes; quinolines; tertiary amino compound | angiogenesis inhibitor; antineoplastic agent; apoptosis inducer; EC 2.7.10.1 (receptor protein-tyrosine kinase) inhibitor | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
cj 033466 | | | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
cc 401 | | pyrazoles; ring assembly | | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
PB28 | | aromatic ether; piperazines; tetralins | anticoronaviral agent; antineoplastic agent; apoptosis inducer; sigma-2 receptor agonist | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
arterolane | | | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
cariprazine | | | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
krp-203 | | | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
regorafenib | | (trifluoromethyl)benzenes; aromatic ether; monochlorobenzenes; monofluorobenzenes; phenylureas; pyridinecarboxamide | antineoplastic agent; hepatotoxic agent; tyrosine kinase inhibitor | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
at 7867 | | monochlorobenzenes; piperidines; pyrazoles | antineoplastic agent; EC 2.7.11.1 (non-specific serine/threonine protein kinase) inhibitor | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
acetic acid 2-[4-methyl-8-(4-morpholinylsulfonyl)-1,3-dioxo-2-pyrrolo[3,4-c]quinolinyl]ethyl ester | | pyrroloquinoline | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
ptc 124 | | oxadiazole; ring assembly | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
degrasyn | | | | 2019 | 2020 | 4.5 | low | 0 | 0 | 0 | 0 | 2 | 0 |
bi 2536 | | | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
azd 1152 | | anilide; monoalkyl phosphate; monofluorobenzenes; pyrazoles; quinazolines; secondary amino compound; secondary carboxamide; tertiary amino compound | antineoplastic agent; Aurora kinase inhibitor; prodrug | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
carfilzomib | | epoxide; morpholines; tetrapeptide | antineoplastic agent; proteasome inhibitor | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
idelalisib | | aromatic amine; organofluorine compound; purines; quinazolines; secondary amino compound | antineoplastic agent; apoptosis inducer; EC 2.7.1.137 (phosphatidylinositol 3-kinase) inhibitor | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
motesanib | | pyridinecarboxamide | | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
pf-562,271 | | indoles | | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
gliocladin c | | | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
sb 706504 | | | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
ku-0060648 | | dibenzothiophenes | | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
bgt226 | | aromatic ether; imidazoquinoline; N-arylpiperazine; organofluorine compound; pyridines | antineoplastic agent; EC 2.7.1.137 (phosphatidylinositol 3-kinase) inhibitor; mTOR inhibitor | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
n-desmethyldanofloxacin | | | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
rabeprazole sodium | | organic sodium salt | | 2017 | 2017 | 7.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
azd 1152-hqpa | | anilide; monofluorobenzenes; primary alcohol; pyrazoles; quinazolines; secondary amino compound; secondary carboxamide; tertiary amino compound | antineoplastic agent; Aurora kinase inhibitor | 2019 | 2020 | 4.5 | low | 0 | 0 | 0 | 0 | 2 | 0 |
CDN1163 | | aromatic ether; quinolines; secondary carboxamide | SERCA activator | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
gsk 269962a | | | | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
pha 848125 | | | | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
nvp-bhg712 | | benzamides | | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
pf 04217903 | | quinolines | | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
5-[[4-(4-acetylphenyl)-1-piperazinyl]sulfonyl]-1,3-dihydroindol-2-one | | aromatic ketone | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
ph 797804 | | aromatic ether; benzamides; organobromine compound; organofluorine compound; pyridone | anti-inflammatory agent; EC 2.7.11.24 (mitogen-activated protein kinase) inhibitor | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
srt1720 | | | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
purfalcamine | | | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
bms 754807 | | pyrazoles; pyridines; pyrrolidines; pyrrolotriazine | antineoplastic agent; EC 2.7.10.1 (receptor protein-tyrosine kinase) inhibitor | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
ponatinib | | (trifluoromethyl)benzenes; acetylenic compound; benzamides; imidazopyridazine; N-methylpiperazine | antineoplastic agent; tyrosine kinase inhibitor | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
quizartinib | | benzoimidazothiazole; isoxazoles; morpholines; phenylureas | antineoplastic agent; EC 2.7.10.1 (receptor protein-tyrosine kinase) inhibitor; necroptosis inhibitor | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
PP121 | | aromatic amine; cyclopentanes; pyrazolopyrimidine; pyrrolopyridine | antineoplastic agent; EC 2.7.1.137 (phosphatidylinositol 3-kinase) inhibitor; tyrosine kinase inhibitor | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
navitoclax | | aryl sulfide; monochlorobenzenes; morpholines; N-sulfonylcarboxamide; organofluorine compound; piperazines; secondary amino compound; sulfone; tertiary amino compound | antineoplastic agent; apoptosis inducer; B-cell lymphoma 2 inhibitor | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
gsk 650394 | | phenylpyridine | | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
dcc-2036 | | organofluorine compound; phenylureas; pyrazoles; pyridinecarboxamide; quinolines | tyrosine kinase inhibitor | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
cabozantinib | | aromatic ether; dicarboxylic acid diamide; organofluorine compound; quinolines | antineoplastic agent; tyrosine kinase inhibitor | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
TAK-580 | | 1,3-thiazolecarboxamide; aminopyrimidine; chloropyridine; organofluorine compound; pyrimidinecarboxamide; secondary carboxamide | antineoplastic agent; apoptosis inducer; B-Raf inhibitor | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
8-(4-aminophenyl)-2-(4-morpholinyl)-1-benzopyran-4-one | | chromones | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
pf 3758309 | | organic heterobicyclic compound; organonitrogen heterocyclic compound; organosulfur heterocyclic compound | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
(5-(2,4-bis((3s)-3-methylmorpholin-4-yl)pyrido(2,3-d)pyrimidin-7-yl)-2-methoxyphenyl)methanol | | benzyl alcohols; morpholines; pyridopyrimidine; tertiary amino compound | antineoplastic agent; apoptosis inducer; mTOR inhibitor | 2019 | 2020 | 4.5 | low | 0 | 0 | 0 | 0 | 2 | 0 |
5-(2-benzofuranyl)-4-[(1-methyl-5-tetrazolyl)thio]thieno[2,3-d]pyrimidine | | aryl sulfide; thienopyrimidine | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
5-(3-methylsulfonylphenyl)-4-[(1-methyl-5-tetrazolyl)thio]thieno[2,3-d]pyrimidine | | aryl sulfide; thienopyrimidine | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
5-bromo-4-[(1-methyl-5-tetrazolyl)thio]thieno[2,3-d]pyrimidine | | aryl sulfide; thienopyrimidine | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
baricitinib | | azetidines; nitrile; pyrazoles; pyrrolopyrimidine; sulfonamide | anti-inflammatory agent; antirheumatic drug; antiviral agent; EC 2.7.10.2 (non-specific protein-tyrosine kinase) inhibitor; immunosuppressive agent | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
6-(1,3-benzodioxol-5-yl)-N-methyl-N-(thiophen-2-ylmethyl)-4-quinazolinamine | | quinazolines | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
6-[(3-aminophenyl)methyl]-4-methyl-2-methylsulfinyl-5-thieno[3,4]pyrrolo[1,3-d]pyridazinone | | organic heterobicyclic compound; organonitrogen heterocyclic compound; organosulfur heterocyclic compound | | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
N-[(5-bromo-8-hydroxy-7-quinolinyl)-thiophen-2-ylmethyl]acetamide | | hydroxyquinoline | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
p505-15 | | | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
mrt67307 | | aromatic amine | | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
N-[3-[[5-chloro-2-[4-(4-methyl-1-piperazinyl)anilino]-4-pyrimidinyl]oxy]phenyl]-2-propenamide | | piperazines | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
ribociclib | | | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
1-[3-[4-[(1-methyl-5-tetrazolyl)thio]-5-thieno[2,3-d]pyrimidinyl]phenyl]ethanone | | aromatic ketone; thienopyrimidine | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
pha 793887 | | piperidinecarboxamide | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
gsk 2334470 | | indazoles | | 2019 | 2019 | 5.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
ml228 probe | | 1,2,4-triazines; biphenyls; pyridines; secondary amino compound | hypoxia-inducible factor pathway activator | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
pf-03882845 | | | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
jq1 compound | | carboxylic ester; organochlorine compound; tert-butyl ester; thienotriazolodiazepine | angiogenesis inhibitor; anti-inflammatory agent; antineoplastic agent; apoptosis inducer; bromodomain-containing protein 4 inhibitor; cardioprotective agent; ferroptosis inducer | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
pf-04620110 | | | | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
gsk525762a | | benzodiazepine | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
birinapant | | dipeptide | | 2019 | 2019 | 5.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
torin 1 | | N-acylpiperazine; N-arylpiperazine; organofluorine compound; pyridoquinoline; quinolines | antineoplastic agent; mTOR inhibitor | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
abt-199 | | aromatic ether; C-nitro compound; monochlorobenzenes; N-alkylpiperazine; N-arylpiperazine; N-sulfonylcarboxamide; oxanes; pyrrolopyridine | antineoplastic agent; apoptosis inducer; B-cell lymphoma 2 inhibitor | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
1-[4-fluoro-3-(trifluoromethyl)phenyl]-3-(5-pyridin-4-yl-1,3,4-thiadiazol-2-yl)urea | | ureas | | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
N-(4-methyl-2-pyridinyl)-4-[3-(trifluoromethyl)anilino]-1-piperidinecarbothioamide | | (trifluoromethyl)benzenes | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
ncgc00242364 | | quinazolines | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
gsk1210151a | | imidazoquinoline | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
hs-173 | | | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
sr1664 | | indolecarboxamide | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
4-(3-chloro-5-(trifluoromethyl)pyridin-2-yl)-n-(4-methoxypyridin-2-yl)piperazine-1-carbothioamide | | | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
N-[4-(1-benzoyl-4-piperidinyl)butyl]-3-(3-pyridinyl)-2-propenamide | | benzamides; N-acylpiperidine | | 2017 | 2020 | 5.5 | high | 0 | 0 | 0 | 0 | 2 | 0 |
N-[4-[3-chloro-4-(2-pyridinylmethoxy)anilino]-3-cyano-7-ethoxy-6-quinolinyl]-4-(dimethylamino)-2-butenamide | | aminoquinoline | | 2017 | 2020 | 5.5 | high | 0 | 0 | 0 | 0 | 2 | 0 |
cudc-907 | | | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
methacycline | | | | 2019 | 2019 | 5.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
methacycline monohydrochloride | | | | 2017 | 2020 | 5.5 | low | 0 | 0 | 0 | 0 | 2 | 0 |
2-[[[4-hydroxy-2-oxo-1-(phenylmethyl)-3-quinolinyl]-oxomethyl]amino]acetic acid | | quinolines | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
agi-5198 | | | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
cep-32496 | | | | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
epz004777 | | N-glycosyl compound | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
3-[[2-(2-pyridinyl)-6-(1,2,4,5-tetrahydro-3-benzazepin-3-yl)-4-pyrimidinyl]amino]propanoic acid | | organonitrogen heterocyclic compound | | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
entecavir | | benzamides; N-acylpiperidine | | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
vx-509 | | | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
vx-970 | | sulfonamide | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
gs-9973 | | | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
amg 925 | | | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
gne-618 | | | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
g007-lk | | | | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
volitinib | | | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
ML355 | | benzothiazoles; monomethoxybenzene; phenols; secondary amino compound; substituted aniline; sulfonamide | EC 1.13.11.31 (arachidonate 12-lipoxygenase) inhibitor; platelet aggregation inhibitor | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
acp-196 | | aromatic amine; benzamides; imidazopyrazine; pyridines; pyrrolidinecarboxamide; secondary carboxamide; tertiary carboxamide; ynone | antineoplastic agent; apoptosis inducer; EC 2.7.10.2 (non-specific protein-tyrosine kinase) inhibitor | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
gsk343 | | aminopyridine; indazoles; N-alkylpiperazine; N-arylpiperazine; pyridone; secondary carboxamide | antineoplastic agent; apoptosis inducer; EC 2.1.1.43 (enhancer of zeste homolog 2) inhibitor | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
agi-6780 | | | | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
khs101 | | | | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
cb-839 | | | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
gsk-j4 | | organonitrogen heterocyclic compound | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
pf-06424439 | | | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
etp-46464 | | | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
onc201 | | | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
kai407 | | | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
6,7-dimethoxy-2-(pyrrolidin-1-yl)-n-(5-(pyrrolidin-1-yl)pentyl)quinazolin-4-amine | | | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
enasidenib | | 1,3,5-triazines; aminopyridine; aromatic amine; organofluorine compound; secondary amino compound; tertiary alcohol | antineoplastic agent; EC 1.1.1.42 (isocitrate dehydrogenase) inhibitor | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
oicr-9429 | | | | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
lly-507 | | | | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
at 9283 | | | | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
hypoxanthine | | nucleobase analogue; oxopurine; purine nucleobase | fundamental metabolite | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
clozapine | | benzodiazepine; N-arylpiperazine; N-methylpiperazine; organochlorine compound | adrenergic antagonist; dopaminergic antagonist; EC 3.4.21.26 (prolyl oligopeptidase) inhibitor; environmental contaminant; GABA antagonist; histamine antagonist; muscarinic antagonist; second generation antipsychotic; serotonergic antagonist; xenobiotic | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
1-hydroxyphenazine | | phenazines | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
ro 24-7429 | | benzodiazepine | | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
nintedanib | | | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
n'-(3,4-dihydroxybenzylidene)-3-hydroxy-2-naphthahydrazide | | catechols; hydrazide; hydrazone; naphthols | EC 3.6.5.5 (dynamin GTPase) inhibitor | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
ver 52296 | | aromatic amide; isoxazoles; monocarboxylic acid amide; morpholines; resorcinols | angiogenesis inhibitor; antineoplastic agent; Hsp90 inhibitor | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
rvx 208 | | | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
bmn 673 | | | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Condition | Indicated | Studies | First Year | Last Year | Average Age | Relationship Strength | Trials | pre-1990 | 1990's | 2000's | 2010's | post-2020 |
Ache | 0 | | 2020 | 2020 | 4.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
ACL Injuries | 0 | | 2019 | 2019 | 5.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
Acute Brain Injuries | 0 | | 2017 | 2017 | 7.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
Acute Kidney Failure | 0 | | 2019 | 2019 | 5.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
Acute Kidney Injury | 0 | | 2019 | 2019 | 5.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
Acute Lung Injury | 0 | | 2018 | 2018 | 6.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
Adenocarcinoma | 0 | | 2018 | 2018 | 6.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
Adenocarcinoma, Basal Cell | 0 | | 2018 | 2018 | 6.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
Age-Related Macular Degeneration | 0 | | 2021 | 2021 | 3.0 | low | 0 | 0 | 0 | 0 | 0 | 1 |
Aging | 0 | | 2016 | 2016 | 8.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
Albuminuria | 0 | | 2014 | 2020 | 6.0 | low | 2 | 0 | 0 | 0 | 3 | 0 |
Alloxan Diabetes | 0 | | 2014 | 2021 | 7.2 | low | 0 | 0 | 0 | 0 | 4 | 1 |
Alveolitis, Fibrosing | 0 | | 2023 | 2023 | 1.0 | low | 0 | 0 | 0 | 0 | 0 | 1 |
Angiitis | 0 | | 2020 | 2020 | 4.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
Angiogenesis, Pathologic | 0 | | 2019 | 2019 | 5.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
Anoxemia | 0 | | 2015 | 2015 | 9.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
Asymmetric Diabetic Proximal Motor Neuropathy | 0 | | 2020 | 2020 | 4.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
Atherogenesis | 0 | | 2014 | 2014 | 10.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
Atheroma | 0 | | 2014 | 2014 | 10.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
Atherosclerosis | 0 | | 2014 | 2014 | 10.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
Autoimmune Chronic Hepatitis | 0 | | 2012 | 2012 | 12.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
Autoimmune Diabetes | 0 | | 2015 | 2020 | 5.2 | low | 2 | 0 | 0 | 0 | 4 | 0 |
Benign Neoplasms | 0 | | 2020 | 2020 | 4.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
Biliary Cirrhosis | 0 | | 2023 | 2023 | 1.0 | low | 2 | 0 | 0 | 0 | 0 | 2 |
Birth Weight | 0 | | 2018 | 2018 | 6.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
Blood Pressure, High | 0 | | 2019 | 2020 | 4.5 | low | 0 | 0 | 0 | 0 | 2 | 0 |
Brain Injuries | 0 | | 2017 | 2017 | 7.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
Cancer of Digestive System | 0 | | 2018 | 2018 | 6.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
Cancer of Esophagus | 0 | | 2018 | 2020 | 5.0 | low | 0 | 0 | 0 | 0 | 2 | 0 |
Cancer of Head | 0 | | 2018 | 2018 | 6.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
Cancer of Lung | 0 | | 2016 | 2018 | 7.0 | low | 0 | 0 | 0 | 0 | 2 | 0 |
Cancer of Mouth | 0 | | 2018 | 2018 | 6.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
Cancer of Oropharnyx | 0 | | 2018 | 2018 | 6.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
Cancer of Prostate | 0 | | 2018 | 2018 | 6.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
Cancer of Skin | 0 | | 2017 | 2017 | 7.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
Cancer, Radiation-Induced | 0 | | 2017 | 2017 | 7.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
Carbon Tetrachloride Poisoning | 0 | | 2015 | 2015 | 9.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
Carcinogenesis | 0 | | 2017 | 2017 | 7.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
Carcinoma, Epidermoid | 0 | | 2018 | 2018 | 6.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
Carcinoma, Non-Small Cell Lung | 0 | | 2016 | 2018 | 7.0 | low | 0 | 0 | 0 | 0 | 2 | 0 |
Carcinoma, Non-Small-Cell Lung | 0 | | 2016 | 2018 | 7.0 | low | 0 | 0 | 0 | 0 | 2 | 0 |
Carcinoma, Squamous Cell | 1 | | 2018 | 2018 | 6.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
Cardiac Hypertrophy | 0 | | 2020 | 2020 | 4.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
Cardiac Remodeling, Ventricular | 0 | | 2012 | 2012 | 12.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
Cardiomegaly | 0 | | 2020 | 2020 | 4.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
Cirrhosis | 0 | | 2014 | 2020 | 7.0 | low | 0 | 0 | 0 | 0 | 3 | 0 |
Cirrhosis, Liver | 0 | | 2012 | 2015 | 10.5 | low | 0 | 0 | 0 | 0 | 4 | 0 |
Colorectal Cancer | 0 | | 2018 | 2018 | 6.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
Colorectal Neoplasms | 0 | | 2018 | 2018 | 6.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
Congenital Zika Syndrome | 0 | | 2020 | 2020 | 4.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
Cruveilhier-Baumgarten Syndrome | 0 | | 2019 | 2019 | 5.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
Delayed Effects, Prenatal Exposure | 0 | | 2018 | 2018 | 6.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
Dermatoses | 0 | | 2014 | 2014 | 10.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
Diabetes Mellitus, Adult-Onset | 0 | | 2017 | 2020 | 5.5 | low | 0 | 0 | 0 | 0 | 2 | 0 |
Diabetes Mellitus, Type 1 | 0 | | 2015 | 2020 | 5.2 | low | 2 | 0 | 0 | 0 | 4 | 0 |
Diabetes Mellitus, Type 2 | 0 | | 2017 | 2020 | 5.5 | low | 0 | 0 | 0 | 0 | 2 | 0 |
Diabetic Angiopathies | 0 | | 2014 | 2014 | 10.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
Diabetic Glomerulosclerosis | 0 | | 2014 | 2020 | 7.5 | low | 1 | 0 | 0 | 0 | 4 | 0 |
Diabetic Nephropathies | 0 | | 2014 | 2020 | 7.5 | low | 1 | 0 | 0 | 0 | 4 | 0 |
Diabetic Neuropathies | 0 | | 2020 | 2020 | 4.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
Digestive System Neoplasms | 0 | | 2018 | 2018 | 6.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
Disease Exacerbation | 0 | | 2018 | 2018 | 6.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
Disease Models, Animal | 0 | | 2014 | 2020 | 6.7 | low | 0 | 0 | 0 | 0 | 11 | 0 |
Erectile Dysfunction | 0 | | 2021 | 2021 | 3.0 | low | 0 | 0 | 0 | 0 | 0 | 1 |
Esophageal Neoplasms | 0 | | 2018 | 2020 | 5.0 | low | 0 | 0 | 0 | 0 | 2 | 0 |
Esophageal Squamous Cell Carcinoma | 0 | | 2020 | 2020 | 4.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
Fatigue | 0 | | 2023 | 2023 | 1.0 | low | 1 | 0 | 0 | 0 | 0 | 1 |
Fatty Liver | 0 | | 2015 | 2015 | 9.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
Fibrosis | 0 | | 2014 | 2020 | 7.0 | low | 0 | 0 | 0 | 0 | 3 | 0 |
Group A Strep Infection | 0 | | 2016 | 2016 | 8.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
Head and Neck Neoplasms | 0 | | 2018 | 2018 | 6.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
Hemorrhage, Subarachnoid | 0 | | 2017 | 2017 | 7.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
Hepatitis | 0 | | 2015 | 2015 | 9.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
Hepatitis, Autoimmune | 0 | | 2012 | 2012 | 12.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
Hypertension | 0 | | 2019 | 2020 | 4.5 | low | 0 | 0 | 0 | 0 | 2 | 0 |
Hypertension, Portal | 0 | | 2019 | 2019 | 5.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
Hypertension, Pulmonary | 0 | | 2012 | 2012 | 12.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
Hypoxia | 0 | | 2015 | 2015 | 9.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
Idiopathic Parkinson Disease | 0 | | 2020 | 2020 | 4.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
Impotence | 0 | | 2021 | 2021 | 3.0 | low | 0 | 0 | 0 | 0 | 0 | 1 |
Inflammation | 0 | | 2014 | 2020 | 6.5 | low | 0 | 0 | 0 | 0 | 4 | 0 |
Injury, Ischemia-Reperfusion | 0 | | 2018 | 2018 | 6.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
Innate Inflammatory Response | 0 | | 2014 | 2020 | 6.5 | low | 0 | 0 | 0 | 0 | 4 | 0 |
Insulin Resistance | 0 | | 2015 | 2015 | 9.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
Insulin Sensitivity | 0 | | 2015 | 2015 | 9.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
Ischemia | 0 | | 2014 | 2015 | 9.5 | low | 0 | 0 | 0 | 0 | 2 | 0 |
Kidney Calculi | 0 | | 2019 | 2019 | 5.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
Kidney Diseases | 0 | | 2018 | 2018 | 6.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
Kidney Stones | 0 | | 2019 | 2019 | 5.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
Lassitude | 0 | | 2023 | 2023 | 1.0 | low | 1 | 0 | 0 | 0 | 0 | 1 |
Liver Cirrhosis | 0 | | 2012 | 2015 | 10.5 | low | 0 | 0 | 0 | 0 | 4 | 0 |
Liver Cirrhosis, Biliary | 1 | | 2023 | 2023 | 1.0 | low | 2 | 0 | 0 | 0 | 0 | 2 |
Liver Steatosis | 0 | | 2015 | 2015 | 9.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
Lung Injury, Acute | 0 | | 2018 | 2018 | 6.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
Lung Neoplasms | 0 | | 2016 | 2018 | 7.0 | low | 0 | 0 | 0 | 0 | 2 | 0 |
Macular Degeneration | 0 | | 2021 | 2021 | 3.0 | low | 0 | 0 | 0 | 0 | 0 | 1 |
Malnourishment | 0 | | 2018 | 2018 | 6.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
Malnutrition | 0 | | 2018 | 2018 | 6.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
Mouth Neoplasms | 0 | | 2018 | 2018 | 6.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
Neoplasms | 0 | | 2020 | 2020 | 4.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
Neuroretinitis | 0 | | 2015 | 2015 | 9.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
Obesity | 0 | | 2015 | 2015 | 9.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
Oropharyngeal Neoplasms | 0 | | 2018 | 2018 | 6.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
Osteoarthritis of Knee | 0 | | 2019 | 2019 | 5.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
Osteoarthritis, Knee | 0 | | 2019 | 2019 | 5.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
Pain | 0 | | 2020 | 2020 | 4.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
Parkinson Disease | 0 | | 2020 | 2020 | 4.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
Pregnancy | 0 | | 2018 | 2018 | 6.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
Prostatic Neoplasms | 0 | | 2018 | 2018 | 6.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
Pulmonary Fibrosis | 0 | | 2023 | 2023 | 1.0 | low | 0 | 0 | 0 | 0 | 0 | 1 |
Pulmonary Hypertension | 0 | | 2012 | 2012 | 12.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
Reperfusion Injury | 0 | | 2018 | 2018 | 6.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
Retinitis | 0 | | 2015 | 2015 | 9.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
Retinopathy of Prematurity | 0 | | 2014 | 2014 | 10.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
Retrolental Fibroplasia | 0 | | 2014 | 2014 | 10.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
Rhabdomyosarcoma | 0 | | 2020 | 2020 | 4.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
Skin Diseases | 0 | | 2014 | 2014 | 10.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
Skin Neoplasms | 0 | | 2017 | 2017 | 7.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
Streptococcal Infections | 0 | | 2016 | 2016 | 8.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
Subarachnoid Hemorrhage | 0 | | 2017 | 2017 | 7.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
Vascular Injuries | 0 | | 2014 | 2014 | 10.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
Vasculitis | 0 | | 2020 | 2020 | 4.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
Zika Virus Infection | 0 | | 2020 | 2020 | 4.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
A physician-initiated double-blind, randomised, placebo-controlled, phase 2 study evaluating the efficacy and safety of inhibition of NADPH oxidase with the first-in-class Nox-1/4 inhibitor, GKT137831, in adults with type 1 diabetes and persistently elevaContemporary clinical trials, , Volume: 90, 2020
Evaluating the efficacy and safety of GKT137831 in adults with type 1 diabetes and persistently elevated urinary albumin excretion: a statistical analysis plan.Trials, , Jun-03, Volume: 21, Issue:1, 2020
Genetic targeting or pharmacologic inhibition of NADPH oxidase nox4 provides renoprotection in long-term diabetic nephropathy.Journal of the American Society of Nephrology : JASN, , Volume: 25, Issue:6, 2014
Evaluating the efficacy and safety of GKT137831 in adults with type 1 diabetes and persistently elevated urinary albumin excretion: a statistical analysis plan.Trials, , Jun-03, Volume: 21, Issue:1, 2020
Targeting the NADPH Oxidase-4 and Liver X Receptor Pathway Preserves Schwann Cell Integrity in Diabetic Mice.Diabetes, , Volume: 69, Issue:3, 2020
A physician-initiated double-blind, randomised, placebo-controlled, phase 2 study evaluating the efficacy and safety of inhibition of NADPH oxidase with the first-in-class Nox-1/4 inhibitor, GKT137831, in adults with type 1 diabetes and persistently elevaContemporary clinical trials, , Volume: 90, 2020
Targeting NADPH oxidase with a novel dual Nox1/Nox4 inhibitor attenuates renal pathology in type 1 diabetes.American journal of physiology. Renal physiology, , Jun-01, Volume: 308, Issue:11, 2015
Targeting the NADPH Oxidase-4 and Liver X Receptor Pathway Preserves Schwann Cell Integrity in Diabetic Mice.Diabetes, , Volume: 69, Issue:3, 2020
APX-115, a first-in-class pan-NADPH oxidase (Nox) inhibitor, protects db/db mice from renal injury.Laboratory investigation; a journal of technical methods and pathology, , Volume: 97, Issue:4, 2017
A physician-initiated double-blind, randomised, placebo-controlled, phase 2 study evaluating the efficacy and safety of inhibition of NADPH oxidase with the first-in-class Nox-1/4 inhibitor, GKT137831, in adults with type 1 diabetes and persistently elevaContemporary clinical trials, , Volume: 90, 2020
APX-115, a first-in-class pan-NADPH oxidase (Nox) inhibitor, protects db/db mice from renal injury.Laboratory investigation; a journal of technical methods and pathology, , Volume: 97, Issue:4, 2017
Targeting NADPH oxidase with a novel dual Nox1/Nox4 inhibitor attenuates renal pathology in type 1 diabetes.American journal of physiology. Renal physiology, , Jun-01, Volume: 308, Issue:11, 2015
Genetic targeting or pharmacologic inhibition of NADPH oxidase nox4 provides renoprotection in long-term diabetic nephropathy.Journal of the American Society of Nephrology : JASN, , Volume: 25, Issue:6, 2014
Nox1/4 inhibition exacerbates age dependent perivascular inflammation and fibrosis in a model of spontaneous hypertension.Pharmacological research, , Volume: 161, 2020
Therapeutic potential of NADPH oxidase 1/4 inhibitors.British journal of pharmacology, , Volume: 174, Issue:12, 2017
NADPH oxidase enzymes in skin fibrosis: molecular targets and therapeutic agents.Archives of dermatological research, , Volume: 306, Issue:4, 2014
Inhibition of the ROS-EGFR Pathway Mediates the Protective Action of Nox1/4 Inhibitor GKT137831 against Hypertensive Cardiac Hypertrophy via Suppressing Cardiac Inflammation and Activation of Akt and ERK1/2.Mediators of inflammation, , Volume: 2020, 2020
Nox1/4 dual inhibitor GKT137831 attenuates hypertensive cardiac remodelling associating with the inhibition of ADAM17-dependent proinflammatory cytokines-induced signalling pathways in the rats with abdominal artery constriction.Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie, , Volume: 109, 2019
Therapeutic potential of NADPH oxidase 1/4 inhibitors.British journal of pharmacology, , Volume: 174, Issue:12, 2017
Pharmacological inhibition of NOX reduces atherosclerotic lesions, vascular ROS and immune-inflammatory responses in diabetic Apoe(-/-) mice.Diabetologia, , Volume: 57, Issue:3, 2014
Inhibition of NOX1/4 with GKT137831: a potential novel treatment to attenuate neuroglial cell inflammation in the retina.Journal of neuroinflammation, , Jul-30, Volume: 12, 2015
NADPH oxidase, NOX1, mediates vascular injury in ischemic retinopathy.Antioxidants & redox signaling, , Jun-10, Volume: 20, Issue:17, 2014
Deficiency of NOX1 or NOX4 Prevents Liver Inflammation and Fibrosis in Mice through Inhibition of Hepatic Stellate Cell Activation.PloS one, , Volume: 10, Issue:7, 2015
Hepatocyte Nicotinamide Adenine Dinucleotide Phosphate Reduced Oxidase 4 Regulates Stress Signaling, Fibrosis, and Insulin Sensitivity During Development of Steatohepatitis in Mice.Gastroenterology, , Volume: 149, Issue:2, 2015
Nicotinamide adenine dinucleotide phosphate oxidase in experimental liver fibrosis: GKT137831 as a novel potential therapeutic agent.Hepatology (Baltimore, Md.), , Volume: 56, Issue:6, 2012
Liver fibrosis and hepatocyte apoptosis are attenuated by GKT137831, a novel NOX4/NOX1 inhibitor in vivo.Free radical biology & medicine, , Jul-15, Volume: 53, Issue:2, 2012
Setanaxib, a first-in-class selective NADPH oxidase 1/4 inhibitor for primary biliary cholangitis: A randomized, placebo-controlled, phase 2 trial.Liver international : official journal of the International Association for the Study of the Liver, , Volume: 43, Issue:7, 2023
Impact of setanaxib on quality of life outcomes in primary biliary cholangitis in a phase 2 randomized controlled trial.Hepatology communications, , 03-01, Volume: 7, Issue:3, 2023
Multiple therapeutic targets in rare cholestatic liver diseases: Time to redefine treatment strategies.Annals of hepatology, , Volume: 19, Issue:1
NOX1/4 Inhibitor GKT-137831 Improves Erectile Function in Diabetic Rats by ROS Reduction and Endothelial Nitric Oxide Synthase Reconstitution.The journal of sexual medicine, , Volume: 18, Issue:12, 2021
Targeting the NADPH Oxidase-4 and Liver X Receptor Pathway Preserves Schwann Cell Integrity in Diabetic Mice.Diabetes, , Volume: 69, Issue:3, 2020
Targeting NADPH oxidase with a novel dual Nox1/Nox4 inhibitor attenuates renal pathology in type 1 diabetes.American journal of physiology. Renal physiology, , Jun-01, Volume: 308, Issue:11, 2015
Genetic targeting or pharmacologic inhibition of NADPH oxidase nox4 provides renoprotection in long-term diabetic nephropathy.Journal of the American Society of Nephrology : JASN, , Volume: 25, Issue:6, 2014
Pharmacological inhibition of NOX reduces atherosclerotic lesions, vascular ROS and immune-inflammatory responses in diabetic Apoe(-/-) mice.Diabetologia, , Volume: 57, Issue:3, 2014
A physician-initiated double-blind, randomised, placebo-controlled, phase 2 study evaluating the efficacy and safety of inhibition of NADPH oxidase with the first-in-class Nox-1/4 inhibitor, GKT137831, in adults with type 1 diabetes and persistently elevaContemporary clinical trials, , Volume: 90, 2020
Targeting the NADPH Oxidase-4 and Liver X Receptor Pathway Preserves Schwann Cell Integrity in Diabetic Mice.Diabetes, , Volume: 69, Issue:3, 2020
Evaluating the efficacy and safety of GKT137831 in adults with type 1 diabetes and persistently elevated urinary albumin excretion: a statistical analysis plan.Trials, , Jun-03, Volume: 21, Issue:1, 2020
Targeting NADPH oxidase with a novel dual Nox1/Nox4 inhibitor attenuates renal pathology in type 1 diabetes.American journal of physiology. Renal physiology, , Jun-01, Volume: 308, Issue:11, 2015
Targeting the NADPH Oxidase-4 and Liver X Receptor Pathway Preserves Schwann Cell Integrity in Diabetic Mice.Diabetes, , Volume: 69, Issue:3, 2020
APX-115, a first-in-class pan-NADPH oxidase (Nox) inhibitor, protects db/db mice from renal injury.Laboratory investigation; a journal of technical methods and pathology, , Volume: 97, Issue:4, 2017
A physician-initiated double-blind, randomised, placebo-controlled, phase 2 study evaluating the efficacy and safety of inhibition of NADPH oxidase with the first-in-class Nox-1/4 inhibitor, GKT137831, in adults with type 1 diabetes and persistently elevaContemporary clinical trials, , Volume: 90, 2020
APX-115, a first-in-class pan-NADPH oxidase (Nox) inhibitor, protects db/db mice from renal injury.Laboratory investigation; a journal of technical methods and pathology, , Volume: 97, Issue:4, 2017
Targeting NADPH oxidase with a novel dual Nox1/Nox4 inhibitor attenuates renal pathology in type 1 diabetes.American journal of physiology. Renal physiology, , Jun-01, Volume: 308, Issue:11, 2015
Genetic targeting or pharmacologic inhibition of NADPH oxidase nox4 provides renoprotection in long-term diabetic nephropathy.Journal of the American Society of Nephrology : JASN, , Volume: 25, Issue:6, 2014
Nox1/4 inhibition exacerbates age dependent perivascular inflammation and fibrosis in a model of spontaneous hypertension.Pharmacological research, , Volume: 161, 2020
Inhibition of NADPH oxidase within midbrain periaqueductal gray decreases pain sensitivity in Parkinson's disease via GABAergic signaling pathway.Physiological research, , 08-31, Volume: 69, Issue:4, 2020
Therapeutic candidates for the Zika virus identified by a high-throughput screen for Zika protease inhibitors.Proceedings of the National Academy of Sciences of the United States of America, , 12-08, Volume: 117, Issue:49, 2020
NADPH oxidase 1/4 inhibition attenuates the portal hypertensive syndrome via modulation of mesenteric angiogenesis and arterial hyporeactivity in rats.Clinics and research in hepatology and gastroenterology, , Volume: 43, Issue:3, 2019
The Nox1/Nox4 inhibitor attenuates acute lung injury induced by ischemia-reperfusion in mice.PloS one, , Volume: 13, Issue:12, 2018
Kidney dysfunction in the low-birth weight murine adult: implications of oxidative stress.American journal of physiology. Renal physiology, , 09-01, Volume: 315, Issue:3, 2018
NADPH Oxidase-1 Plays a Key Role in Keratinocyte Responses to UV Radiation and UVB-Induced Skin Carcinogenesis.The Journal of investigative dermatology, , Volume: 137, Issue:6, 2017
Hepatocyte Nicotinamide Adenine Dinucleotide Phosphate Reduced Oxidase 4 Regulates Stress Signaling, Fibrosis, and Insulin Sensitivity During Development of Steatohepatitis in Mice.Gastroenterology, , Volume: 149, Issue:2, 2015
Inhibition of NOX1/4 with GKT137831: a potential novel treatment to attenuate neuroglial cell inflammation in the retina.Journal of neuroinflammation, , Jul-30, Volume: 12, 2015
Genetic targeting or pharmacologic inhibition of NADPH oxidase nox4 provides renoprotection in long-term diabetic nephropathy.Journal of the American Society of Nephrology : JASN, , Volume: 25, Issue:6, 2014
NADPH oxidase, NOX1, mediates vascular injury in ischemic retinopathy.Antioxidants & redox signaling, , Jun-10, Volume: 20, Issue:17, 2014
Nox1/4 inhibition exacerbates age dependent perivascular inflammation and fibrosis in a model of spontaneous hypertension.Pharmacological research, , Volume: 161, 2020
Therapeutic potential of NADPH oxidase 1/4 inhibitors.British journal of pharmacology, , Volume: 174, Issue:12, 2017
NADPH oxidase enzymes in skin fibrosis: molecular targets and therapeutic agents.Archives of dermatological research, , Volume: 306, Issue:4, 2014
Inhibition of the ROS-EGFR Pathway Mediates the Protective Action of Nox1/4 Inhibitor GKT137831 against Hypertensive Cardiac Hypertrophy via Suppressing Cardiac Inflammation and Activation of Akt and ERK1/2.Mediators of inflammation, , Volume: 2020, 2020
Nox1/4 dual inhibitor GKT137831 attenuates hypertensive cardiac remodelling associating with the inhibition of ADAM17-dependent proinflammatory cytokines-induced signalling pathways in the rats with abdominal artery constriction.Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie, , Volume: 109, 2019
Therapeutic potential of NADPH oxidase 1/4 inhibitors.British journal of pharmacology, , Volume: 174, Issue:12, 2017
Pharmacological inhibition of NOX reduces atherosclerotic lesions, vascular ROS and immune-inflammatory responses in diabetic Apoe(-/-) mice.Diabetologia, , Volume: 57, Issue:3, 2014
Deficiency of NOX1 or NOX4 Prevents Liver Inflammation and Fibrosis in Mice through Inhibition of Hepatic Stellate Cell Activation.PloS one, , Volume: 10, Issue:7, 2015
Hepatocyte Nicotinamide Adenine Dinucleotide Phosphate Reduced Oxidase 4 Regulates Stress Signaling, Fibrosis, and Insulin Sensitivity During Development of Steatohepatitis in Mice.Gastroenterology, , Volume: 149, Issue:2, 2015
Liver fibrosis and hepatocyte apoptosis are attenuated by GKT137831, a novel NOX4/NOX1 inhibitor in vivo.Free radical biology & medicine, , Jul-15, Volume: 53, Issue:2, 2012
Nicotinamide adenine dinucleotide phosphate oxidase in experimental liver fibrosis: GKT137831 as a novel potential therapeutic agent.Hepatology (Baltimore, Md.), , Volume: 56, Issue:6, 2012
Setanaxib, a first-in-class selective NADPH oxidase 1/4 inhibitor for primary biliary cholangitis: A randomized, placebo-controlled, phase 2 trial.Liver international : official journal of the International Association for the Study of the Liver, , Volume: 43, Issue:7, 2023
Impact of setanaxib on quality of life outcomes in primary biliary cholangitis in a phase 2 randomized controlled trial.Hepatology communications, , 03-01, Volume: 7, Issue:3, 2023
Multiple therapeutic targets in rare cholestatic liver diseases: Time to redefine treatment strategies.Annals of hepatology, , Volume: 19, Issue:1
Safety/Toxicity (1)
Bioavailability (3)
Article | Year |
A High-Throughput Screen of a Library of Therapeutics Identifies Cytotoxic Substrates of P-glycoprotein. Molecular pharmacology, , Volume: 96, Issue:5 | 2019 |
Kidney dysfunction in the low-birth weight murine adult: implications of oxidative stress. American journal of physiology. Renal physiology, , 09-01, Volume: 315, Issue:3 | 2018 |
Highly predictive and interpretable models for PAMPA permeability. Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3 | 2017 |