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SOT 2011: “In Silico Predictive Model for Drug-Induced Phospholipidosis using BioEpisteme software"

Washington D.C., USA: Prous Institute’s BioEpisteme® software will be featured in a scientific poster to be presented by the US FDA Center for Drug Evaluation and Research (CDER), Office of Pharmaceutical Science (OPS), at the Annual Meeting of the Society of Toxicology in Washington D.C., March 6th-10th 2011. The poster is titled: “In silico Predictive Model for Drug-Induced Phospholipidosis using BioEpisteme Software”.

The poster will present one of the new modeling efforts with BioEpisteme® v 4.1, a quantitative structure-activity relationship (QSAR) software program that constructs customized drug prediction models in line with fundamental research endpoints.  BioEpisteme® was made available to FDA/CDER/OPS via an agency-approved Research Collaboration Agreement with the Prous Institute for Biomedical Research.

The poster will form part of the SOT poster session: “Bioinformatic Profiling and Computational Pathway Prediction” which will take place on March 7th 2011, at the Exhibit Hall (Convention Center).

Abstract

“Drug-induced Phospholipidosis (DIPL) is a recognized finding in pharmaceutical drug development. DIPL is characterized by accumulation of drugs and phospholipids in lysosomes. Pathologically, DIPL manifests foamy macrophages or cytoplasmic vacuoles in various tissues of both animals and humans. These pathologic findings can be confirmed by the appearance of lamellar inclusion bodies by electron microscopy. CADs (cationic amphiphilic drugs) are known to induce PL and share common structural features of containing hydrophobic ring structure and hydrophilic amine portion. This has led FDA to investigate the structural similarities and differences for active and inactive compounds. FDA has been developing a PL database that currently contains over 700 PL positive and negative drugs. Using this database and various computational programs, FDA has developed predictive QSAR models for DIPL. In this study, new in silico models were generated and validated using BioEpisteme, a toxicity screening and QSAR model development program, developed by the Prous Institute for Biomedical Research. BioEpisteme facilitates creation and application of in silico toxicity predictions based on molecular descriptors. In addition, it provides predictions on mechanism of action (MOA) (mechanism of action) for 432 different pharmacological targets. Preliminary performance statistics of a new DIPL QSAR model using a genetic algorithm of BioEpisteme show 87% specificity, 73% sensitivity, and 82% accuracy. These results were compared with other available FDA QSAR models. In addition, the MOA model was investigated to predict possible pharmaceutical MOA targets of the DIPL data set. These highly performing in silico predictive models will help to predict DIPL early in drug development and will subsequently serve to support regulatory decisions.”  

To learn more about of BioEpisteme® prediction software, please visit www.prousresearch.com

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