nystatin-a1 and Drug-Related-Side-Effects-and-Adverse-Reactions

Topics: Acne Vulgaris; Alopecia; Balanitis; Candidiasis; Dermatitis, Occupational; Dermatomycoses; Diaper Rash; Drug-Related Side Effects and Adverse Reactions; Eczema; Erectile Dysfunction; Estrogens; Female; Glucocorticoids; Griseofulvin; Humans; Keloid; Male; Nystatin; Paronychia; Psoriasis; Scabies; Sexually Transmitted Diseases; Skin Diseases; Varicose Veins; Vitamins

Compare the safety and efficacy of topical gentian violet with that of nystatin oral suspension (NYS) for the treatment of oropharyngeal candidiasis in HIV-1-infected adults in resource-limited settings.. Multicenter, open-label, evaluator-blinded, randomized clinical trial at eight international sites, within the AIDS Clinical Trials Group.. Adult HIV-infected participants with oropharyngeal candidiasis, stratified by CD4 cell counts and antiretroviral therapy status at study entry, were randomized to receive either gentian violet (0.00165%, BID) or NYS (500 000 units, QID) for 14 days.. Cure or improvement after 14 days of treatment. Signs and symptoms of oropharyngeal candidiasis were evaluated in an evaluator-blinded manner.. The study was closed early per Data Safety Monitoring Board after enrolling 221 participants (target = 494). Among the 182 participants eligible for efficacy analysis, 63 (68.5%) in the gentian violet arm had cure or improvement of oropharyngeal candidiasis versus 61 (67.8%) in the NYS arm, resulting in a nonsizable difference of 0.007 (95% confidence interval: -0.129, 0.143). There was no sizable difference in cure rates between the two arms (-0.0007; 95% confidence interval: -0.146, 0.131). No gentian violet-related adverse events were noted. No sizable differences were identified in tolerance, adherence, quality of life, or acceptability of study drugs. In gentian violet arm, 61 and 39% of participants reported 'no' and 'mild-to-moderate' staining, respectively. Cost for medication procurement was significantly lower for gentian violet versus NYS (median $2.51 and 19.42, respectively, P = 0.01).. Efficacy of gentian violet was not statistically different than NYS, was well tolerated, and its procurement cost was substantially less than NYS.

Topics: Administration, Oral; Administration, Topical; Adolescent; Adult; Aged; Aged, 80 and over; Antifungal Agents; Candidiasis, Oral; Drug-Related Side Effects and Adverse Reactions; Female; Gentian Violet; Health Care Costs; HIV Infections; Humans; Male; Middle Aged; Nystatin; Single-Blind Method; Treatment Outcome; Young Adult

The interaction between azole antifungal therapy and immunosuppressant tacrolimus (TAC) is a barrier to use.. This study quantified the drug interaction between low-dose fluconazole (LDF) and TAC to determine the appropriate TAC dose adjustment when used concurrently in renal transplant recipients.. We conducted a single-center retrospective chart review of renal transplant patients. We evaluated 94 patients and included 81. Low-dose fluconazole received a greater TAC TDD prior to post-operative day (POD) 10 (10.5 ± 4.7 mg vs. 7.1 ± 4.5 mg,. A 20% reduction in TAC TDD is warranted in renal transplant patients when used concomitantly with LDF to achieve therapeutic levels.

Topics: Antifungal Agents; Azoles; Drug-Related Side Effects and Adverse Reactions; Fluconazole; Graft Rejection; Humans; Immunosuppressive Agents; Kidney Transplantation; Nystatin; Retrospective Studies; Tacrolimus

Drug-induced liver injury (DILI) is a leading cause of drugs failing during clinical trials and being withdrawn from the market. Comparative analysis of drugs based on their DILI potential is an effective approach to discover key DILI mechanisms and risk factors. However, assessing the DILI potential of a drug is a challenge with no existing consensus methods. We proposed a systematic classification scheme using FDA-approved drug labeling to assess the DILI potential of drugs, which yielded a benchmark dataset with 287 drugs representing a wide range of therapeutic categories and daily dosage amounts. The method is transparent and reproducible with a potential to serve as a common practice to study the DILI of marketed drugs for supporting drug discovery and biomarker development.

Topics: Animals; Benchmarking; Biomarkers, Pharmacological; Chemical and Drug Induced Liver Injury; Drug Design; Drug Labeling; Drug-Related Side Effects and Adverse Reactions; Humans; Pharmaceutical Preparations; Reproducibility of Results; United States; United States Food and Drug Administration

Drug-induced liver injury (DILI) is a significant concern in drug development due to the poor concordance between preclinical and clinical findings of liver toxicity. We hypothesized that the DILI types (hepatotoxic side effects) seen in the clinic can be translated into the development of predictive in silico models for use in the drug discovery phase. We identified 13 hepatotoxic side effects with high accuracy for classifying marketed drugs for their DILI potential. We then developed in silico predictive models for each of these 13 side effects, which were further combined to construct a DILI prediction system (DILIps). The DILIps yielded 60-70% prediction accuracy for three independent validation sets. To enhance the confidence for identification of drugs that cause severe DILI in humans, the "Rule of Three" was developed in DILIps by using a consensus strategy based on 13 models. This gave high positive predictive value (91%) when applied to an external dataset containing 206 drugs from three independent literature datasets. Using the DILIps, we screened all the drugs in DrugBank and investigated their DILI potential in terms of protein targets and therapeutic categories through network modeling. We demonstrated that two therapeutic categories, anti-infectives for systemic use and musculoskeletal system drugs, were enriched for DILI, which is consistent with current knowledge. We also identified protein targets and pathways that are related to drugs that cause DILI by using pathway analysis and co-occurrence text mining. While marketed drugs were the focus of this study, the DILIps has a potential as an evaluation tool to screen and prioritize new drug candidates or chemicals, such as environmental chemicals, to avoid those that might cause liver toxicity. We expect that the methodology can be also applied to other drug safety endpoints, such as renal or cardiovascular toxicity.

Topics: Animals; Anti-Infective Agents; Anti-Inflammatory Agents; Chemical and Drug Induced Liver Injury; Databases, Factual; Drug-Related Side Effects and Adverse Reactions; Humans; Liver; Models, Biological; Predictive Value of Tests

The chemical space of registered oral drugs was explored for inhibitors of the human multidrug-resistance associated protein 2 (MRP2; ABCC2), using a data set of 191 structurally diverse drugs and drug-like compounds. The data set included a new reference set of 75 compounds, for studies of hepatic drug interactions with transport proteins, CYP enzymes, and compounds associated with liver toxicity. The inhibition of MRP2-mediated transport of estradiol-17beta-D-glucuronide was studied in inverted membrane vesicles from Sf9 cells overexpressing human MRP2. A total of 27 previously unknown MRP2 inhibitors were identified, and the results indicate an overlapping but narrower inhibitor space for MRP2 compared with the two other major ABC efflux transporters P-gp (ABCB1) and BCRP (ABCG2). In addition, 13 compounds were shown to stimulate the transport of estradiol-17beta-D-glucuronide. The experimental results were used to develop a computational model able to discriminate inhibitors from noninhibitors according to their molecular structure, resulting in a predictive power of 86% for the training set and 72% for the test set. The inhibitors were in general larger and more lipophilic and presented a higher aromaticity than the noninhibitors. The developed computational model is applicable in an early stage of the drug discovery process and is proposed as a tool for prediction of MRP2-mediated hepatic drug interactions and toxicity.

Topics: Administration, Oral; Animals; Antineoplastic Agents; Antipsychotic Agents; Antiviral Agents; ATP Binding Cassette Transporter, Subfamily B; ATP Binding Cassette Transporter, Subfamily B, Member 1; ATP Binding Cassette Transporter, Subfamily G, Member 2; ATP-Binding Cassette Transporters; Biological Transport; Cell Line; Computer Simulation; Cytochrome P-450 Enzyme System; Drug-Related Side Effects and Adverse Reactions; Estradiol; Humans; Insecta; Liver; Models, Molecular; Multidrug Resistance-Associated Protein 2; Multidrug Resistance-Associated Proteins; Neoplasm Proteins; Pharmaceutical Preparations; Pharmacology; Structure-Activity Relationship

The FDA's Spontaneous Reporting System (SRS) database contains over 1.5 million adverse drug reaction (ADR) reports for 8620 drugs/biologics that are listed for 1191 Coding Symbols for Thesaurus of Adverse Reaction (COSTAR) terms of adverse effects. We have linked the trade names of the drugs to 1861 generic names and retrieved molecular structures for each chemical to obtain a set of 1515 organic chemicals that are suitable for modeling with commercially available QSAR software packages. ADR report data for 631 of these compounds were extracted and pooled for the first five years that each drug was marketed. Patient exposure was estimated during this period using pharmaceutical shipping units obtained from IMS Health. Significant drug effects were identified using a Reporting Index (RI), where RI = (# ADR reports / # shipping units) x 1,000,000. MCASE/MC4PC software was used to identify the optimal conditions for defining a significant adverse effect finding. Results suggest that a significant effect in our database is characterized by > or = 4 ADR reports and > or = 20,000 shipping units during five years of marketing, and an RI > or = 4.0. Furthermore, for a test chemical to be evaluated as active it must contain a statistically significant molecular structural alert, called a decision alert, in two or more toxicologically related endpoints. We also report the use of a composite module, which pools observations from two or more toxicologically related COSTAR term endpoints to provide signal enhancement for detecting adverse effects.

Topics: Adverse Drug Reaction Reporting Systems; Artificial Intelligence; Computers; Databases, Factual; Drug Prescriptions; Drug-Related Side Effects and Adverse Reactions; Endpoint Determination; Models, Molecular; Quantitative Structure-Activity Relationship; Software; United States; United States Food and Drug Administration

Topics: Adrenal Cortex Hormones; Antifungal Agents; Benzene Derivatives; Cytosine; Drug-Related Side Effects and Adverse Reactions; Fluorine; Gentian Violet; Histoplasmosis; Humans; Iatrogenic Disease; Imidazoles; Immunosuppressive Agents; Mycoses; Natamycin; Nystatin; Sulfonamides