Validating ADME QSAR Models Using Marketed Drugs

SLAS Discov. 2021 Dec;26(10):1326-1336. doi: 10.1177/24725552211017520. Epub 2021 Jun 26.

Abstract

Problems with drug ADME are responsible for many clinical failures. By understanding the ADME properties of marketed drugs and modeling how chemical structure contributes to these inherent properties, we can help new projects reduce their risk profiles. Kinetic aqueous solubility, the parallel artificial membrane permeability assay (PAMPA), and rat liver microsomal stability constitute the Tier I ADME assays at the National Center for Advancing Translational Sciences (NCATS). Using recent data generated from in-house lead optimization Tier I studies, we update quantitative structure-activity relationship (QSAR) models for these three endpoints and validate in silico performance against a set of marketed drugs (balanced accuracies range between 71% and 85%). Improved models and experimental datasets are of direct relevance to drug discovery projects and, together with the prediction services that have been made publicly available at the ADME@NCATS web portal (https://opendata.ncats.nih.gov/adme/), provide important tools for the drug discovery community. The results are discussed in light of our previously reported ADME models and state-of-the-art models from scientific literature.Graphical Abstract[Figure: see text].

Keywords: ADME; PAMPA permeability; QSAR; high-throughput screening; rat liver microsomal stability; solubility.

Publication types

  • Research Support, N.I.H., Intramural

MeSH terms

  • Animals
  • Drug Discovery / methods
  • Models, Biological
  • National Center for Advancing Translational Sciences (U.S.)
  • Pharmaceutical Preparations / chemistry*
  • Quantitative Structure-Activity Relationship
  • Rats
  • Translational Science, Biomedical / methods
  • United States

Substances

  • Pharmaceutical Preparations