estramustine and Chemical-and-Drug-Induced-Liver-Injury

Topics: Chemical and Drug Induced Liver Injury; Databases, Factual; Drug Labeling; Humans; Pharmaceutical Preparations; Risk

To exploit the favorable dose intensity and safety profile of weekly paclitaxel, we conducted a Phase I trial of paclitaxel by 3-hour infusion in combination with estramustine phosphate (EM) in men with hormone-refractory prostate cancer (HRPC). The antimicrotubule drug combination of paclitaxel by 96-hour infusion plus EM is active in HRPC.. Twenty-four patients with metastatic HRPC and progressive tumor after antiandrogen withdrawal were enrolled in this study. Oral EM was taken at a dose of 600 mg/m(2) daily for the initial 21 patients and on a reduced schedule of 280 mg twice daily for the final 3 patients. Paclitaxel was escalated from 60 to 118 mg/m(2).. The major toxicities were gastrointestinal and thromboembolic complications related to daily oral dosing of EM. Of the first 21 patients, one third (n = 7) discontinued therapy within 4 weeks because of protracted nausea and/or thrombotic complications. Dose-limiting toxicities at 118 mg/m(2) paclitaxel were fatigue and hepatotoxicity. Of 13 patients with measurable soft-tissue lesions, 6 had objective partial regressions, and 9 (37.5%) of 24 patients (95% confidence interval 19.1% to 59.1%) with elevated prostate-specific antigen levels had a 50% or greater decline of at least 4 weeks' duration.. Weekly paclitaxel at doses of 60 to 107 mg/m(2) were feasible in combination with oral EM, but daily oral EM produced unacceptable toxicity. On the basis of these results, a Phase II trial of weekly paclitaxel with the reduced dose and schedule of EM was initiated by the Eastern Cooperative Oncology Group to assess further the benefits and risks of this treatment in men with metastatic HRPC.

Topics: Adenocarcinoma; Administration, Oral; Aged; Aged, 80 and over; Anaphylaxis; Antineoplastic Combined Chemotherapy Protocols; Chemical and Drug Induced Liver Injury; Disease Progression; Disease-Free Survival; Drug Resistance, Neoplasm; Edema; Estramustine; Gonadotropin-Releasing Hormone; Humans; Infusions, Intravenous; Male; Middle Aged; Nausea; Paclitaxel; Prostatic Neoplasms; Thrombophlebitis; Treatment Outcome

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

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

40 patients with prostatic carcinoma were treated with parenteral and/or oral Estracyt (estramustine phosphate) until 55 months. Metastases were present in 37 patients (stage D). 35 of the 40 patients developed metastases in spite of estrogen therapy and/or orchidectomy. Diminution of metastasic bone pain as well as improvement of hydroureteronephrosis was frequently observed. Paraplegia secondary to metastatic disease improved in 1 case for 6 months. Side effects were relatively rare and were mainly gastrointestinal. A possible hepatotoxic action of the compound has been pointed out previously. On the basis of our studies Estracyt is recommended in the treatment of primary estrogen resistent prostatic carcinoma and in metastatic carcinoma of the prostate not responding to conventional antiandrogenic therapy anymore.

Topics: Administration, Oral; Aged; Bone Neoplasms; Carcinoma; Chemical and Drug Induced Liver Injury; Chemical Phenomena; Chemistry; Estramustine; Estrogens; Humans; Injections, Intravenous; Long-Term Care; Male; Middle Aged; Neoplasm Metastasis; Nitrogen Mustard Compounds; Prostatic Neoplasms