Sanofi aventisAureus Pharma, a leading provider of knowledge management solutions to accelerate discovery and development in the life sciences industry, announced the extension of its agreement with sanofi-aventis for the licence of the DDI Predict 2009 Edition application.

DDI Predict 2009 Edition provides a risk analysis of potential drug-drug interactions between a drug candidate and a large panel of marketed or withdrawn drugs including the cases where multiple metabolic pathways are involved and provides new functionalities including prediction of fraction metabolized based on scaling factors (RAF, ISEF, Abundance), gut metabolism and others.

The DDI Predict 2009 Edition application is used in the Metabolism and Pharmacokinetic´s department of sanofi-aventis and provides critical information to assess potential risks of drug-drug interactions as early in the drug development process as possible.

"We are pleased to license DDI predict 2009 Edition to sanofi-aventis after intensive development and validation," said Olivier Barberan, director Product Development at Aureus Pharma. "DDI Predict 2009 Edition is the cornerstone of a wider edifice dedicated to in vitro in vivo extrapolation of drug-drug interactions developed at Aureus Pharma. This application combines Mechanistic Static Model and Aureus´ high quality data that leads to additional value to researchers."

The predictions are supported by calculation of the change of the AUC ratio based on the blood concentration of the drug candidate in the presence or absence of enzyme inhibitors. The system is using a large library containing more than 7,000 and 8,000 inhibition and PK data points respectively, measured on 1,500 drugs stored in the Aureus ADME database to calculate potential interactions. The Aureus ADME Knowledge database contains a total 25,000 compounds, 3,500 metabolites, 365,000 biological data points, analyzed out from more than 11,000 articles and FDA documents.

Aureus Pharma headquartered in Paris, France, creates and maintains scientific knowledge bases combining chemical and biological, in vitro and in vivo data for a large number of compounds, and provides software applications which enable scientists to understand the responses of biological targets to compounds under evaluation.