title: ADMET in silico modelling: towards prediction paradise?
abstract: Following studies in the late 1990s that indicated that poor pharmacokinetics and toxicity were important causes of costly late-stage failures in drug development, it has become widely appreciated that these areas should be considered as early as possible in the drug discovery process. However, in recent years, combinatorial chemistry and high-throughput screening have significantly increased the number of compounds for which early data on absorption, distribution, metabolism, excretion (ADME) and toxicity (T) are needed, which has in turn driven the development of a variety of medium and high-throughput in vitro ADMET screens. Here, we describe how in silico approaches will further increase our ability to predict and model the most relevant pharmacokinetic, metabolic and toxicity endpoints, thereby accelerating the drug discovery process.
authors.affiliation: Pfizer Global Research & Development, PDM, Sandwich, Kent CT13 9NJ, UK. han_waterbeemd@sandwich.pfizer.com
authors.forename: Han
authors.initials: H
authors.lastname: van de Waterbeemd
authors.forename: Eric
authors.initials: E
authors.lastname: Gifford
mesh_terms: D000818:Animals; D001682:Biological Availability; D001812:Blood-Brain Barrier; D055598:Chemical Phenomena; D002627:Chemistry, Physical; D003198:Computer Simulation; D015195:Drug Design; D064420:Drug-Related Side Effects and Adverse Reactions; D006801:Humans; D008954:Models, Biological; D010599:Pharmacokinetics; D011485:Protein Binding; D021281:Quantitative Structure-Activity Relationship; D012984:Software; D014018:Tissue Distribution