With the dawn of new century, major technological advances in the drug discovery field have revolutionized absorption, distribution, metabolism, excretion and toxicity (ADME/T) profiling of new chemical entities (NCEs) among others. The progress made in the in vitro experimental determination of the ADME/T properties fueled the growth in the so-called predictive ADME/T. The process of in silico model development improved significantly with the availability of high quality data as well newer, more accurate statistical methods of analysis. Even several such models appear in the literature regularly, the prediction accuracy is limited to ‘local’ rather than ‘global’ applicability domain in majority of the cases. Majority of the efforts are still needed to address several issues such as data quality, accuracy of the results, etc., to increase the usefulness of these models. The ultimate aim is to develop in silico ADME/T models which will largely replace their in vitro experimental counterparts. The current review article discusses the two-dimensional (2D) approaches used in the predictive ADME/T model development and their limitations and usefulness in the discovery process.
Keywords: ADME/T modeling, ADME/T predictions, QSAR, QSPR, ANN, computational toxicology
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