Advancements in Predictive In Silico Models for ADME

Title: Advancements in Predictive In Silico Models for ADME

Volume: 2 Issue: 3

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

Affiliation:

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

Abstract: 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.

Cite this article as:

Chohan K. Kamaldeep, Paine W. Stuart and Waters J. Nigel, Advancements in Predictive In Silico Models for ADME, Current Chemical Biology 2008; 2 (3) . https://dx.doi.org/10.2174/2212796810802030215