Chapter title |
Modeling ADMET.
|
---|---|
Chapter number | 4 |
Book title |
In Silico Methods for Predicting Drug Toxicity
|
Published in |
Methods in molecular biology, January 2016
|
DOI | 10.1007/978-1-4939-3609-0_4 |
Pubmed ID | |
Book ISBNs |
978-1-4939-3607-6, 978-1-4939-3609-0
|
Authors |
Jayeeta Ghosh, Michael S. Lawless, Marvin Waldman, Vijay Gombar, Robert Fraczkiewicz |
Editors |
Emilio Benfenati |
Abstract |
Drug discovery and development is a costly and time-consuming endeavor (Calcoen et al. Nat Rev Drug Discov 14(3):161-162, 2015; The truly staggering cost of inventing new drugs. Forbes. http://www.forbes.com/sites/matthewherper/2012/02/10/the-truly-staggering-cost-of-inventing-new-drugs/, 2012; Scannell et al. Nat Rev Drug Discov 11(3):191-200, 2012). Over the last two decades, computational tools and in silico models to predict ADMET (Adsorption, Distribution, Metabolism, Excretion, and Toxicity) profiles of molecules have been incorporated into the drug discovery process mainly in an effort to avoid late-stage failures due to poor pharmacokinetics and toxicity. It is now widely recognized that ADMET issues should be addressed as early as possible in drug discovery. Here, we describe in detail how ADMET models can be developed and applied using a commercially available package, ADMET Predictor™ 7.2 (ADMET Predictor v7.2. Simulations Plus, Inc., Lancaster, CA, USA). |
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Demographic breakdown
Readers by professional status | Count | As % |
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Researcher | 7 | 11% |
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Engineering | 3 | 5% |
Other | 8 | 13% |
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