This book describes the state‑of‑the‑art methods and applications for de novo design of drug candidates using generative chemistry models as well as the ethical aspects of this technology. It will provide a foundation for those new to the field as well as those that may already have some experience of its utility. With contributions from scientists in both academia and industry ‘Introduction to Generative Drug Discovery’ may represent one of the earliest if not the first book to focus on this topic.
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Sean Ekins is founder and CEO of Collaborations Pharmaceuticals, Inc. (CPI) which is focused on using machine learning approaches for rare and neglected disease drug discovery. Sean graduated from the University of Aberdeen, receiving his M.Sc., Ph.D. in Clinical Pharmacology and D.Sc. in Science. He was a postdoctoral fellow at Eli Lilly, before working as a senior scientist at Pfizer and then returning to Eli Lilly. He went on to join several startup companies at increasingly senior levels. Since 2005 he has been awarded numerous grants as PI for a wide array of start-up companies totaling over $12.2M as well as performing as a consultant on others. Since 2016 he has additionally won over 20 additional grants from NIH and DOD (STTR/SBIR grants, R21, UH2 and R01) totaling over $21.2M for CPI. He has a passion for advancing new technologies for drug discovery and is a prolific collaborator. He has authored or co-authored over 370 peer reviewed papers, book chapters, edited 5 books on different aspects of drug discovery research and topics and written one book on winning grants. Coverage of his recent research has also appeared in the Economist, Financial Times, Washington Post, Wired, Scientific American, CNN and Netflix as well as several podcasts. When he is not writing he enjoys cycling and record collecting.
This book focuses on the latest advances in computational de novo drug discovery methods, also known as generative drug discovery. This book describes the state-of-the-art methods and applications for de novo design of drug candidates using generative chemistry models as well as ethical aspects of this technology.
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