Drexplorer: A Tool to Assess Dose-Response Relationship for Anti-Cancer Drug-Screening Data and Evaluate Drug-Drug Interactions

• Activity Number: 86
• Type: Contributed
• Date/Time: Sunday, August 9, 2015 : 4:00 PM to 5:50 PM
• Sponsor: Biopharmaceutical Section
• Author(s): Pan Tong* and Kevin R. Coombes and Faye M. Johnson and Lauren A. Byers and Lixia Diao and Diane D. Liu and J. Jack Lee and John N. Weinstein and John V. Heymach and Jing Wang
• Companies: MD Anderson Cancer Center and The Ohio State University and MD Anderson Cancer Center and MD Anderson Cancer Center and MD Anderson Cancer Center and MD Anderson Cancer Center and MD Anderson Cancer Center and MD Anderson Cancer Center and MD Anderson Cancer Center and MD Anderson Cancer Center
• Keywords: dose response data ; drug interaction ; drug discovery ; pharmacodynamics ; model selection

Abstract

Pharmacodynamics study of therapeutic compounds is a major focus of clinical oncology. Large-scale drug screening has the potential to identify compounds that significantly reduce mortality and improve quality of life for cancer patients. As a result, accurately estimating drug potency plays an important role. We developed the drexplorer R package to encompass several aspects of dose-response analysis: assess reproducibility of replicated experiments, detect outlier data points, fit different models, identify the best model, estimate inhibitory concentration (IC), area under curve (AUC), GI50 (50% growth inhibition), TGI (total growth inhibition) as well as LC50 (50% killing effect) and evaluate drug-drug interactions. To evaluate different metrics, we also perform comprehensive analysis with over one thousand compounds. Drexplorer is a versatile tool for pharmacodynamics study. Real data analysis shows that IC50 has best correlation with other metrics including GI50, TGI and Emax, supporting its popularity in practice. We further find that IC50 performs at least as good as other metrics even for targeted compounds.