Thank you for joining us at Drug Discovery Chemistry.
Recordings of the CAS presentations from this meeting are now available for viewing (see below).
Looking to optimize your small molecules for tomorrow’s therapeutics? We can help, contact us to learn more.
Abstract: Pharmaceutical research teams increasingly rely on SciFindern, the most advanced research solution in the SciFinder family, to help them improve productivity, inspire innovation and feel confident in advancing their projects and programs forward.
This talk will demonstrate, with practical examples, how SciFindern helps solve problems in small molecule drug discovery. (from the Small Molecules for Immunology & Oncology track)
Abstract: More and better data is an obvious need, but have you considered how impactful descriptors can be on predictions? Join us to see how better descriptors can improve AI algorithm performance on predicting biological activity across multiple algorithmic approaches with over 150K compounds. This case study by Dr. Alpha Lee (University of Cambridge), which was just recently peer reviewed and accepted for publication in the Journal of Chemical Information and Modeling, showcases the impact of better descriptors on prediction accuracy. If your AI initiatives aren’t meeting expectations, learn how better quality descriptors can immediately improve accuracy vs. existing fingerprints. (from the AI for Early Drug Discovery track)
See how enhancing the quality of the input data alone, without changing the algorithm, impacts prediction accuracy of an algorithm designed to assess the biological activity of compounds relative to different targets in this quantitative study by CAS data scientists.