Author: DeLisle, Robert K.

Source: Current Computer - Aided Drug Design, Volume 5, Number 2, June 2009 , pp. 139-144(6)

Publisher: Bentham Science Publishers

Abstract:

It is not unusual for models developed to predict Absorption, Distribution, Metabolism, Elimination, and Toxicity (ADMET) as well as other endpoints to be nothing more than a black box, supplying only a numerical or categorical value by which users are expected to assess the goodness of a query compound. This type of result is, however, of little use in the overarching goal of developing better and safer drug compounds, that is, providing guidance toward improving the characteristics of the query or formulating chemical hypotheses that can be evaluated through synthetic efforts. As a result, the level of acceptance of predictions by users outside the computational chemistry and molecular modeling groups tends to be very low. In this review, I address three primary domains in which model presentation can be improved, specifically, establishing confidence in the prediction, data interrogation, and model interpretability. It has been my experience that even small efforts in these areas result in a much greater return with respect to acceptance, good faith, and usage from users regardless of the user's role within the drug discovery process.

Document Type: Research article

DOI: http://dx.doi.org/10.2174/157340909788451900

Publication date: 2009-06-01

More about this publication?

• Current Computer-Aided Drug Design aims to publish all the latest developments in drug design based on computational techniques. The field of computer-aided drug design has had extensive impact in the area of drug design. Current Computer-Aided Drug Design is an essential journal for all medicinal chemists who wish to be kept informed and up-to-date with all the latest and important developments in computer-aided methodologies and their applications in drug discovery. Each issue contains a series of timely, in-depth reviews written by leaders in the field, covering a range of computational techniques for drug design, screening, ADME studies, etc., providing excellent rationales for drug development.

Related content

• In this: publication
• By this: publisher
• In this Subject: Computer Science ,  Pharmacology
• By this author: DeLisle, Robert K.

Website © Publishing Technology. Article copyright remains with the publisher, society or author(s) as specified within the article.

• Terms and conditions
• Privacy policy
• Information for advertisers