Statistical Methods for Evaluation of Bioactivity of Chemicals Using Quantitative High Throughput Screening

Abstract

Quantitative high throughput sreening (qHTS) is a technique which has originally developed as a powerful tool for drug discovery and lately is expanding its application to the neighboring field, e.g. toxicological screening test for environmental chemicals. A wide variety of in-vitro biological activity of a large amount of chemical materials can be assayed with a low cost and in a short time period. As a result of two largescale pharmacogenomic studies being published in 2012, the reproducibility of the result of screening assay of cytotoxicity for 15 drugs in 471 cell lines was revealed to be unexpectedly low. The necessity of developments of statistical methods suitable for qHTS data were emphasized. In this review, the authors explain 3 statistical methods with applications to qHTS data, which has been proposed since 2013: 1. robust ridge regression estimators for nonlinear models in the purpose of testing bioactivity of chemicals; 2. Bayesian hierarchical dose-response modeling; 3. using weighted entropy to rank chemicals. Characteristics of each method were compared, and the prospects were presented.