Noah Flynn

Noah Flynn is a research scientist at Amazon with a PhD in Computational Biology from Washington University in St. Louis. He has developed deep learning applications to screen drugs for bioactivation, reactive metabolite formation, drug-drug interactions, and other types of toxicity problems. He has worked at AbbVie and Merckon analysis of gene regulatory networks and protein-protein interactions and applications of generative models to construct and optimize novel compound libraries. He now researches applications of large language models at Amazon.

books by Noah Flynn

Machine Learning for Drug Discovery

  • MEAP began February 2024
  • Publication in Fall 2025 (estimated)
  • ISBN 9781633437661
  • 275 pages (estimated)
  • printed in black & white

Machine Learning for Drug Discovery introduces the fundamentals of drug discovery and cheminformatics along with the machine learning techniques used by leaders in the pharmaceutical industry. Each chapter guides you through an engaging hands-on project that explores a real medical issue. You’ll build a full screening pipeline to assess a compound’s potential for treating malaria, reproduce published methods for HIV drug design, learn to use deep generative models for novel drug optimization, and see how LLMs can overcome common problems of protein folding