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GALAS Modeling Methodology Applications In The Prediction Of Drug Metabolism Related Properties
EP20355
Poster Title: GALAS Modeling Methodology Applications In The Prediction Of Drug Metabolism Related Properties
Submitted on 19 Dec 2013
Author(s): Remigijus Didziapetris, Justas Dapkunas, Andrius Sazonovas and Pranas Japertas
Affiliations: ACD Labs
Poster Views: 975
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Poster Information
Abstract: Every model, no matter what data, descriptors, or modeling techniques used to build it, has a certain applicability domain, beyond which the quality of predictions becomes highly questionable. This reality is one of the fundamental issues concerning the effective use of third-party predictive algorithms in industry. The simple reason for this is that literature based training sets rarely cover the specific part of the chemical space that ‘in-house’ projects are focused on. Discrepancies between ‘in-house’ experimental protocols and methods used to measure properties for compounds in publicly available sources further affect the quality of resulting in silico predictions. Therefore the need has long existed for a method that would allow any company to effectively assess the Applicability Domain of any third-party model and to tailor it to its specific needs using proprietary ‘in-house’ data.

Addressing the aforementioned issue, a GALAS (Global, Adjusted Locally According to Similarity) model concept has been developed providing a novel solution to this problem.
Summary: Analytical identification of metabolites for a drug candidate is usually a time consuming and low-throughput task and is performed only at the later phases of drug development. Therefore the possibility to predict possible sites of human liver microsomal (HLM) metabolism using in silico techniques would be a very attractive feature for any medicinal chemist.Report abuse »
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