AI CoE Webinar: Optimizing Kinase Profiling Programs with Deep Learning

Webinar Summary

Join Genentech and Optibrium for this discussion of Alchemite™, a novel deep learning approach, and its application to optimizing kinase profiling programs. Using Alchemite™ reduces the number of kinase assays required to accurately predict the full kinase selectivity profile, effectively accelerating experimental programs.

The team will demonstrate the method’s performance on a data set of approximately 650 kinases and 10,000 compounds, significantly outperforming state-of-the-art quantitative structure-activity relationship (QSAR) approaches, including multi-target deep learning. Furthermore, we will discuss Alchemite’s unique ability to provide reliable prediction-uncertainty-estimates that enable the selection of the most informative kinase assays and which compounds to test.

Ideal for:

Scientist, Sr. Scientist, Program Manager, Associate Director, Director

Speakers

• Matt Segall, CEO, Optibrium
• Samar Mahmoud, Senior Scientist, Optibrium
• Fabio Broccatelli, Senior Scientist, Genentech

For more information about the Pistoia Alliance’s Artificial Intelligence & Machine Learning Community, please contact us.

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