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The University of Paris Selects ACD/Percepta Software to Enhance Teaching and Research into Pharmaceuticals
Product News

The University of Paris Selects ACD/Percepta Software to Enhance Teaching and Research into Pharmaceuticals

The University of Paris Selects ACD/Percepta Software to Enhance Teaching and Research into Pharmaceuticals
Product News

The University of Paris Selects ACD/Percepta Software to Enhance Teaching and Research into Pharmaceuticals


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The Université Paris-Sud, School of Pharmacy, has selected ACD/Labs’ ADME, Toxicity, and PhysChem predictors on the ACD/Percepta Platform, to enable in silico evaluation of pharmaceutical substances and research compounds.

The software is to be applied by undergraduate students to help them understand the effect of drugs on the body in terms of toxicity, and the body’s ability to use and dispose of a drug, i.e., ADME properties (absorption, distribution, metabolism, and excretion). Graduate students will use the software in their investigations towards innovative therapeutics from natural products. 

“As an educator I want to prepare my students for a successful career in the pharmaceutical industry. Software is used more and more, and our students will benefit from being exposed to these tools early in their education”, says Prof. Delphine Joseph. “Ease of use was very important to us, particularly since undergraduate classes will only use the software for one academic session, to understand the concepts behind drug design. Our research programs will benefit because graduate students will be able to profile synthetic modifications to molecular structures in silico, and investigate the effect on physiological behavior.”

Percepta modules provide predictions for oral bioavailability, CYP450 inhibition, blood brain barrier permeation, hERG inhibition, lipophilicity, and many other physiologically relevant properties. The values and supporting information provided in the software (such as similar structures, effect of pH, and color coded mapping) can help scientists understand the behavior of molecular structures, and direct discovery research in terms of achieving an optimal drug-like profile.

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