title: Computer systems for the prediction of xenobiotic metabolism.
abstract: The aim of pharmaceutical research and development is to ensure a continuing pipeline of new chemical entities (NCEs) displaying high therapeutic efficacy with few or no side effects. Failure of promising lead candidates late in the drug discovery processes is regarded as commercially unacceptable in today's increasingly competitive business environment. An inappropriate ADME/Toxicity profile in humans is the major cause of failure of lead candidates in late clinical stages of drug development. Combinatorial chemistry techniques coupled with high throughput screening protocols means that pharmaceutical companies are now dealing with an unprecedented number of NCEs on an annual basis. As a consequence, screening for undesirable ADME/Toxicity properties in the early stages of drug development, preferably pre-synthesis, is now considered the essential paradigm. In silico assessment of NCEs is rapidly emerging as the next wave of technology for early ADME/Toxicity prediction. In this review, we discuss the major commercially available products for the assessing the potential metabolic activity of xenobiotic substances in mammalian systems.
authors.affiliation: LHASA Limited, School of Chemistry, University of Leeds, Woodhouse Lane, LS2 9JT, West Yorkshire, UK.
authors.forename: Jan
authors.initials: J
authors.lastname: Langowski
authors.forename: Anthony
authors.initials: A
authors.lastname: Long
mesh_terms: D000818:Animals; D019295:Computational Biology / Q000379:methods*; D003201:Computers; D016208:Databases, Factual; D004798:Enzymes / Q000378:metabolism; D005103:Expert Systems; D006801:Humans; D008958:Models, Molecular; D011237:Predictive Value of Tests; D015262:Xenobiotics / Q000378:metabolism*
chemical_list: D004798:Enzymes; D015262:Xenobiotics