Toxicogenomics strategies for predicting drug toxicity

Introduction: The failure of pharmaceutical drug candidates due to toxicity, especially hepatotoxicity, is an important and continuing problem for drug development. The current manuscript explores new toxicogenomics approaches to better understand the hepatotoxic potential of human pharmaceutical compounds and to assess their toxicity earlier in the drug development process by means of a toxicity screen. Resources: Data consisted of two commercial knowledgebases that employed a hybrid experimental design in which human drug toxicity information was extracted from the literature, dichotomized and merged with rat-based gene expression measures. One knowledgebase used gene expression from rat primary hepatocytes while the other employed whole rats. Approximately 100 compounds were used in each. Methods: Toxicity classification rules were built using a stochastic gradient boosting machine learner, with classification error estimated using a modified bootstrap estimate of true error. Several types of clusterin...