title: Predictive computational toxicology to support drug safety assessment.
abstract: Use of predictive technologies is an important aspect of many efforts in today's research, development, and regulatory landscapes. Computational methods as predictive tools for supporting drug safety assessments is of widespread interest as the field of in silico assessments rapidly changes with emerging technologies and the large amount of existing data available for modeling. There are challenges associated with application of in silico analyses for drug toxicity predictions and need for strategies and harmonization to enable an acceptable in silico evaluation for prediction of specific toxicity assay outcomes. This chapter will provide an overview focused on computational tools using structure-activity relationships and will highlight initiatives for use of computational assessments and realistic applications for predictive modeling in evaluating potential toxicities of drug-related molecules.
authors.affiliation: Office of Pharmaceutical Science, Center for Drug Evaluation and Research, U.S. Food and Drug Administration, Silver Spring, MD, USA. Luis.Valerio@FDA.hhs.gov
authors.forename: Luis G
authors.initials: LG
authors.lastname: Valerio
mesh_terms: D019295:Computational Biology / Q000379:methods*; D064420:Drug-Related Side Effects and Adverse Reactions; D006801:Humans; D009152:Mutagenicity Tests; D021281:Quantitative Structure-Activity Relationship; D015203:Reproducibility of Results; D012475:Salmonella / Q000235:genetics; D018675:Toxicity Tests