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Predictive ADME |
InterAction Meeting Session, Bryn Mawr, Philadelphia, USA
Thursday 16 October 2008
chaired by Anthony E. Klon (Locus Pharmaceuticals) Bio....
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The prediction of absorption, distribution, metabolism, and excretion (ADME) properties has become increasingly important as failures late in the drug discovery process become more costly. Increasingly, stringent in vitro and in vivo requirements have been placed on the hit-to-lead and lead optimization stages of the drug discovery process. Although it is tempting to dismiss ADME modeling and simply conduct an in vitro or in vivo experiment to get “the correct answer”, this approach is not practical. A skilled, competent medicinal chemist working on a lead optimization program can easily conceive of far more compounds than can reasonably be synthesized during the time of a lead optimization effort. Animal studies are expensive and time-consuming and may become the rate-limiting step for some projects, particularly for small pharmaceutical companies. Rather than providing “the correct answer”, modeling provides a means of “stacking the deck” in favor of the medicinal chemistry effort, increasing the likelihood that a given compound will show the desired effect in vitro or in vivo.
The purpose of this session is to present recent developments in the predictive modeling of ADME properties. Speakers will present their research into modeling microsomal stability, drug-drug interactions, and membrane transport processes such as blood-brain barrier penetration, intestinal absorption, and skin penetration. One topic of the accompanying discussions will be the appropriateness of relevant biological endpoints for ADME/PK modeling.
Presenters & Discussions Leaders
Heidi Einolf (Novartis), Predictions of Metabolic Drug Drug Interactions Abstract & Bio....
Anton Hopfinger (University of New Mexico), Novel MI-QSAR Descriptors for Use in Modeling Membrane Transport Processes Such as Skin Penetration Enhancement Abstract & Bio....
Anthony E. Klon (Locus Pharmaceuticals), Comparison of Machine Learning Algorithms to Predict ADME Properties Using Diverse Chemical Descriptors and Molecular Fingerprints Abstract & Bio....
Olga Obrezanova (BioFocus DPI), Automatic QSAR modeling of Blood-Brain Barrier Penetration by Gaussian Processes Method Abstract & Bio....
Yojiro Sakiyama (Pfizer), Application of Machine Learning Tools for in silico ADME Screening
Abstract & Bio....
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