Advancements in Predictive In Silico Models for ADME

Author(s): Kamaldeep K. Chohan , Stuart W. Paine , Nigel J. Waters .

Journal Name: Current Chemical Biology

Volume 2 , Issue 3 , 2008

Become EABM
Become Reviewer


This comprehensive review describes contemporary computational (in silico) quantitative structure-activity relationship (QSAR) approaches that have been used to elucidate the molecular features that influence the Absorption, Distribution, Metabolism and Elimination (ADME) of drugs. Recent studies have applied 2D and 3D QSAR, pharmacophore approaches and nonlinear techniques (for example: recursive partitioning, neural networks and support vector machines) to model ADME processes. Furthermore, this review highlights some of the challenges and opportunities for future research; the need to develop ‘global’ models and to extend the QSAR for the protein transporters that influence ADME.

Keywords: In silico, QSAR, ADME, drug metabolism, pharmacokinetics, statistical methods, protein transporters

Rights & PermissionsPrintExport Cite as

Article Details

Year: 2008
Page: [215 - 228]
Pages: 14
DOI: 10.2174/2212796810802030215
Price: $58

Article Metrics

PDF: 6