Abstract

The drug development process in the United States is an expensive and lengthy process, usually taking a decade or more to gain approval for a drug candidate. The majority of proposed, early stage therapeutics fail, even though the typical process narrows from hundreds or thousands of small molecules down to one late stage candidate. One reason for failure is due to the drug’s poor or unexpected absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties. Researchers attempt to predict ADMET properties as a way to help prioritize compounds for lead development to minimize expense and time. It was the overall goal of this
project to further the prediction of two ADMET properties (absorption and distribution) through the development and application of quantitative structure-activity (QSAR) relationship computational models predicting human intestinal absorption (HIA), Caco-2 permeability (in vivo & in vitro measurements of absorption), and protein binding (measurement of distribution). These combined models would then be paired with additional experimental methods to help prioritize compounds for future ligand discovery efforts in our lab group and for our collaborators.

By Keri Danielle Hannie