A New Community for Drug Discovery Researchers

BIOVIA is launching a brand new Drug Discovery & Development Community

Why? Because we are at a unique time in history with cheminformatics and modeling & simulation methods now combining with Artificial Intelligence/Machine Learning to advance molecular discovery and optimization.

BIOVIA believes that bringing researchers from these disciplines together is the key to accelerating new breakthroughs in data-driven science.

Improve Towards a Target Product Profile

In drug discovery, scientists now explore chemical space by “learning” from real experiments. The enumeration of all molecules that could be drugs is not currently possible with reasonable resources. However, chemists can use AI and machine learning to explore a large area of chemical space through an iterative generative design process with a fitness function that represents the target product profile. The discovery cycle combines virtual and real (V+R) activities in which the results of virtual generation and evaluation combine with real world synthesis and testing to allow active learning.

Novel molecules advanced by the virtual ‘generate-test-score’ pruning process move to the lab for synthesis and screening. Real world screening results allow the update of predictive models for subsequent cycles. Optimization of all objectives continues until the target therapeutic profile is met. This iterative V+R cycle accelerates lead candidate design with improved quality, significantly reducing costs of experimentation and advancing only the most promising candidates to clinical trials.

The Innovation Cycle combining Virtual + Real (V+R) activities

Modeling and simulation methods are essential for improving the quality of compound suggestions. Important methods include pharmacophore scoring, molecular docking and free energy methods for predicting binding affinities.

Comparing molecules in a protein active site. Scientists can use pharmacophore scoring and molecular docking to prioritize the best candidates for selection.

Advance the Innovation Cycle with V+R

RU82129, a novel non-peptidic high affinity inhibitor, bound to the SH2 domain of pp60src

V+R analysis and decision making pairs the unique expertise and intuition of the chemist with AI predictive modeling to shape the decision about which compound to make next. We combine all virtual and real information in an analytics environment that takes into account preferred chemistries and reactions. We then add available resources/knowledge from ‘prior art’ to find the most promising compounds to pursue.

Comparing molecules in a protein active site; pharmacophore scoring and molecular docking can be used to prioritize the best candidates for selection

Collaborate More Effectively in Drug Discovery & Development

Your new Drug Discovery and Development Community will provide updates about BIOVIA technology and events. Share ideas about the use of BIOVIA products and research approaches. Pose questions to the community at large. Share content with others, for example: “How to” videos, BIOVIA Pipeline Pilot protocols and BIOVIA Insight/BIOVIA Draw plug-ins to extend existing product functionality.

The new Community addresses the needs of customers using the following BIOVIA applications: Generative Therapeutics Design, Discovery Studio, Registration, Insight and Insight for Excel, Direct Cartridge, Draw, Pipette Sketcher, Pipeline Pilot Chemistry Collection/SDK, BIOVIA Content and DiscoveryGate.

To become an active participant in this new Community, subscribe to the daily digest by emailing tien.luu@3ds.com.

Digest subscribers will receive an automated email from BIOVIA
each day there is activity in the community.