alitretinoin and Chemical-and-Drug-Induced-Liver-Injury

Although advanced renal-cell carcinoma (RCC) responds poorly to standard therapies, phase I-II trials have shown activity for combinations of interferon-alpha2b (IFN) with a retinoid. Alitretinoin (9-cis RA) is an endogenous retinoid with high binding affinity for both RAR and RXR receptor families. This phase I-II study enrolled 38 patients with RCC in a dose-escalation study of tolerability, pharmacokinetics (PK), and efficacy of twice daily oral 9-cis RA with subcutaneous IFN. In contrast to studies with similar doses of daily 9-cis RA, PK studies found a consistent reduction in 9-cis RA concentrations of about 50% after multiple b.i.d. doses of 30 or 50 mg/m2, independent of cotreatment with IFN. In the phase I portion, toxicities included systemic symptoms typical of IFN and biochemical abnormalities previously associated with retinoids. Two patients experienced dose-limiting toxicity at 50 mg/m2 b.i.d. of 9-cis RA, thus the recommended phase II dose was 30 mg/m2 b.i.d. One of twenty-six evaluable patients achieved a durable objective partial remission, and repeated dosing with this regimen was poorly tolerated. This combination of retinoid and interferon is not recommended for further study in RCC.

Topics: Adult; Aged; Alitretinoin; Antineoplastic Agents; Carcinoma, Renal Cell; Chemical and Drug Induced Liver Injury; Combined Modality Therapy; Dose-Response Relationship, Drug; Drug Administration Schedule; Drug Synergism; Fatigue; Female; Fever; Humans; Immunologic Factors; Interferon alpha-2; Interferon-alpha; Kidney Neoplasms; Male; Middle Aged; Nephrectomy; Pain; Recombinant Proteins; Remission Induction; Treatment Failure; Tretinoin

Farnesoid X receptor (FXR) plays a key role in bile acid homeostasis, inflammation, fibrosis, and metabolism of lipid and glucose and becomes a promising therapeutic target for nonalcoholic steatohepatitis (NASH) or other FXR-dependent diseases. The phase III trial results of obeticholic acid demonstrate that the FXR agonists emerge as a promising intervention in patients with NASH and fibrosis, but this bile acid-derived FXR agonist brings severe pruritus and an elevated risk of cardiovascular disease for patients. Herein, we reported our efforts in the discovery of a series of non-bile acid FXR agonists, and 36 compounds were designed and synthesized based on the structure-based drug design and structural optimization strategies. Particularly, compound

Topics: Animals; Binding Sites; Chemical and Drug Induced Liver Injury; Chenodeoxycholic Acid; Drug Design; Drug Evaluation, Preclinical; Half-Life; Humans; Liver; Male; Mice; Mice, Inbred C57BL; Molecular Docking Simulation; Non-alcoholic Fatty Liver Disease; Rats; Rats, Sprague-Dawley; Receptors, Cytoplasmic and Nuclear; Structure-Activity Relationship

Drug-induced liver injury is one of the main causes of drug attrition. The ability to predict the liver effects of drug candidates from their chemical structures is critical to help guide experimental drug discovery projects toward safer medicines. In this study, we have compiled a data set of 951 compounds reported to produce a wide range of effects in the liver in different species, comprising humans, rodents, and nonrodents. The liver effects for this data set were obtained as assertional metadata, generated from MEDLINE abstracts using a unique combination of lexical and linguistic methods and ontological rules. We have analyzed this data set using conventional cheminformatics approaches and addressed several questions pertaining to cross-species concordance of liver effects, chemical determinants of liver effects in humans, and the prediction of whether a given compound is likely to cause a liver effect in humans. We found that the concordance of liver effects was relatively low (ca. 39-44%) between different species, raising the possibility that species specificity could depend on specific features of chemical structure. Compounds were clustered by their chemical similarity, and similar compounds were examined for the expected similarity of their species-dependent liver effect profiles. In most cases, similar profiles were observed for members of the same cluster, but some compounds appeared as outliers. The outliers were the subject of focused assertion regeneration from MEDLINE as well as other data sources. In some cases, additional biological assertions were identified, which were in line with expectations based on compounds' chemical similarities. The assertions were further converted to binary annotations of underlying chemicals (i.e., liver effect vs no liver effect), and binary quantitative structure-activity relationship (QSAR) models were generated to predict whether a compound would be expected to produce liver effects in humans. Despite the apparent heterogeneity of data, models have shown good predictive power assessed by external 5-fold cross-validation procedures. The external predictive power of binary QSAR models was further confirmed by their application to compounds that were retrieved or studied after the model was developed. To the best of our knowledge, this is the first study for chemical toxicity prediction that applied QSAR modeling and other cheminformatics techniques to observational data generated by the means of automate

Topics: Animals; Chemical and Drug Induced Liver Injury; Cluster Analysis; Databases, Factual; Humans; MEDLINE; Mice; Models, Chemical; Molecular Conformation; Quantitative Structure-Activity Relationship