Mar 30, 2011

Accelrys Extends Impact of Modeling and Simulation with New QSAR Workbench

New packaged service offering automates and speeds the development, validation and deployment of predictive QSAR models.
SAN DIEGO - Accelrys, Inc, a leading scientific enterprise R&D software and services company, today announced the release of Accelrys QSAR Workbench. Developed in a collaboration between the Accelrys Professional Services team and pharmaceutical company GlaxoSmithKline, the Accelrys QSAR Workbench is a commercially available, web-based solution that automates and accelerates the development, validation and deployment of predictive Quantitative Structure-Activity Relationship (QSAR) models.

As a packaged service offering for Modeling and Simulation within the Accelrys Enterprise R&D Architecture, the QSAR Workbench supports better, faster outcomes and reduced costs through the automation and expert use of predictive science. Built on the Pipeline Pilot™ platform, the QSAR Workbench utilizes native QSAR methods and easily integrates with other statistical tools — helping experts and non-experts alike save time, reduce costs, collaborate more effectively and speed research by leveraging robust, predictive models.

"Accelrys QSAR Workbench cuts model development time from days to hours, accelerating the identification of successful hits earlier in the research process and potentially reducing the number of costly laboratory experiments," said Dr. Trevor Heritage, executive vice president, software products, Accelrys. "This new solution, developed in collaboration with GlaxoSmithKline, also helps to encode best QSAR practices, improve collaboration among experts and extend the reach of this expertise within R&D organizations."

For organizations that do not have the expertise and resources to build models for all projects, the Accelrys QSAR Workbench captures best practices of QSAR design, streamlines model development, reduces errors and automates manual, tedious and error-prone steps so that every project benefits from a model. The ability to record, play and replay protocols in a single interface simplifies and streamlines model development and validation. Statistical experts can focus on building powerful QSAR models leveraging Bayesian probability, recursive partitioning, neural networks, linear regression and other native QSAR methods. Project teams validate the models by testing hypotheses in silico. Optimal models can then be saved and deployed more widely for immediate use by others.

The QSAR Workbench is available from Accelrys Professional Services.