Demystifying Machine Learning (AI) in Drug Discovery
Recorded live September 10, 2020
In this webinar, Drs. John Overington (Medicines Discovery Catapult), John Griffin (Integral Health) and Jeff Warrington (Atomwise) discussed various modern machine learning methods applied to drug discovery data in real life organizations.
Download Slides (PDF)
Webinar Summary
Machine learning, artificial intelligence, deep learning. We've all heard of the buzz words as these technologies promise to transform the landscape of drug discovery, but how exactly do they work? What are the limitations and pitfalls of each approach? And what are the requirements for their successful implementation?
Please join our moderator Dr. John Overington and domain experts Dr. John Griffin and Dr. Jeff Warrington for a cutting-edge discussion on modern machine learning (AI) methods applied to drug discovery data. Learn how the various methodologies are being applied in real organizations.
Featuring these leading innovators...
John Overington, Ph.D.
Chief Informatics Officer, Medicines Discovery Catapult
John Overington joined the Medicines Discovery Catapult in 2017 as CIO, where he leads the development and application of informatics approaches to promote and support innovative, fast-to-patient drug discovery in the UK through collaborative projects across the applied R&D community.
John joined from technology company BenevolentAI, where he was involved in the development of novel data extraction and integration strategies, integrating deep learning and other Artificial Intelligence approaches to drug target validation and drug optimization. Prior to this, John worked for Inpharmatica, where he led the development of a series of computational and data platforms to improve drug discovery, including the medicinal chemistry database StARLite.
John has a degree in Chemistry from the University of Bath and a Ph.D. from Birkbeck College, London.
John Griffin, Ph.D.
Vice President, Integral Health
John Griffin is a Vice President at Integral Health, a stealth biotech company. Prior to that he was the Chief Scientific Officer at Numerate where he was responsible for its therapeutic programs and collaborations. He was formerly co-founder and Chief Scientific Officer of Theravance, Inc., a publicly traded biopharmaceutical company.
A former Assistant Professor at Stanford University, John is also the author of 39 scientific publications, an inventor of 27 issued patents, and the recipient of numerous awards including an Arthur C. Cope Scholar Award from the American Chemical Society and a Dean's Award for Teaching from Stanford University. He has also served on the Funding Committee for the Wellcome Trust's Seeding Drug Discovery Initiative.
John received a B.S. in Chemistry from Hope College, a Ph.D. in Chemistry from the California Institute of Technology and was a National Science Foundation Postdoctoral Fellow at Harvard Medical School.
Jeff Warrington, Ph.D.
Senior Scientist, Atomwise
Jeff Warrington is a Senior Scientist at Atomwise, an AI company that uses machine learning for better drug design. Prior to that he worked at the biopharmaceutical company Cytokinetics, where he was involved in developing therapeutics for muscle-related disorders such as amyotrophic lateral sclerosis (ALS). These efforts led to the development of reldesemtiv, a drug candidate currently in phase 2 clinical trials.
Jeff has a Ph.D. degree from the University of Ottawa and a postdoctoral fellowship at Stanford University, where he used natural product synthesis and modification to address a supply problem for an important adjuvant to human immunodeficiency virus (HIV) therapy-prostratin.