Global Analysis of Models for Predicting Human Absorption: QSAR, <i>In Vitro</i> , and Preclinical Models

Abstract

Models intended to predict intestinal absorption are an essential part of the drug development process. Although many models exist for capturing intestinal absorption, many questions still exist around the applicability of these models to drug types like "beyond rule of 5" (bRo5) and low absorption compounds. This presents a challenge as current models have not been rigorously tested to understand intestinal absorption. Here, we assembled a large, structurally diverse dataset of ∼1000 compounds with known <i>in vitro</i>, preclinical, and human permeability and/or absorption data. <i>In silico</i> (quantitative structure-activity relationship), <i>in vitro</i> (Caco-2), and <i>in vivo</i> (rat) models were statistically evaluated for predictive performance against this human intestinal absorption dataset. We expect this evaluation to serve as a resource for DMPK scientists and medicinal/computational chemists to increase their understanding of permeability and absorption model utility and applications for academia and industry.