Abstract
The accurate prediction of the in vivo pharmacokinetics of a new potential drug compound based on only its virtual structure is the ultimate goal of in silico ADME-Tox property modeling. A comprehensive review is made on recent studies concerning the A (absorption) in ADME-Tox, i.e. the in silico modeling of both Caco-2 permeability and human intestinal absorption. The data sets used, the descriptors selected to build the models, the variable selection methods, the modeling techniques and the performed model validation are critically discussed. It was concluded that reliable models which improve the success rate of compound selection and drug development are still lacking. Limiting the quality of the models are, for instance, inappropriate compilation of data sets, lack of an appropriate outlier detection and unrepresentativeness of training and test sets for the data population. The definition of some best practices or guidelines for the different steps of the modeling procedure might improve the predictions and make the procedure uniform, i.e. “standard tools” in drug development would become available.
Keywords: ADME-tox, Caco-2, drug absorption, human intestinal absorption, in silico methods, QSAR, pharmacokinetics, Combinatorial chemistry, Computer-Aided Drug Design, pharmacophore, in vitro
Combinatorial Chemistry & High Throughput Screening
Title: In Silico Predictions of ADME-Tox Properties: Drug Absorption
Volume: 14 Issue: 5
Author(s): Tessy Geerts and Yvan Vander Heyden
Affiliation:
Keywords: ADME-tox, Caco-2, drug absorption, human intestinal absorption, in silico methods, QSAR, pharmacokinetics, Combinatorial chemistry, Computer-Aided Drug Design, pharmacophore, in vitro
Abstract: The accurate prediction of the in vivo pharmacokinetics of a new potential drug compound based on only its virtual structure is the ultimate goal of in silico ADME-Tox property modeling. A comprehensive review is made on recent studies concerning the A (absorption) in ADME-Tox, i.e. the in silico modeling of both Caco-2 permeability and human intestinal absorption. The data sets used, the descriptors selected to build the models, the variable selection methods, the modeling techniques and the performed model validation are critically discussed. It was concluded that reliable models which improve the success rate of compound selection and drug development are still lacking. Limiting the quality of the models are, for instance, inappropriate compilation of data sets, lack of an appropriate outlier detection and unrepresentativeness of training and test sets for the data population. The definition of some best practices or guidelines for the different steps of the modeling procedure might improve the predictions and make the procedure uniform, i.e. “standard tools” in drug development would become available.
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Cite this article as:
Geerts Tessy and Vander Heyden Yvan, In Silico Predictions of ADME-Tox Properties: Drug Absorption, Combinatorial Chemistry & High Throughput Screening 2011; 14 (5) . https://dx.doi.org/10.2174/138620711795508359
DOI https://dx.doi.org/10.2174/138620711795508359 |
Print ISSN 1386-2073 |
Publisher Name Bentham Science Publisher |
Online ISSN 1875-5402 |
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