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Current Chemical Biology


ISSN (Print): 2212-7968
ISSN (Online): 1872-3136

Advancements in Predictive In Silico Models for ADME

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

Volume 2, Issue 3, 2008

Page: [215 - 228] Pages: 14

DOI: 10.2174/2212796810802030215

Price: $65


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

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