A Mathematical Framework for Analyzing Drug Combination Toxicity for Personalized Medicine Applications

Abstract

The use of drug combinations to increase efficacy and lower resistance to therapy for personalized cancer medicine is being commonly recognized. Approaches have been recently designed to address the selection of drug combinations that can be highly effective across tumor cells but limited research have been conducted on the toxicity of these unique drug combinations. In this article, we approach this problem of combination drug toxicity by analyzing drug synergy over in vitro normal cell lines and generate combination drug concentrations whose combined effect on normal cell lines is less than the maximum mono-therapy effect at approved concentrations. We present a mathematical framework for combination response estimation among multiple cell cultures along with stochastic analysis of prediction uncertainty. Results indicate the ability of the proposed framework to generate feasibly combination drug concentrations satisfying mono-therapy toxicity constraints.