Leading Chemistry and Drug Development Researchers Alexander Tropsha, Ph.D. and Robert N. Young, Ph.D. Join SAB
Vancouver, BC – April 5, 2022 – Variational AI, developer of state-of-the-art generative AI technology to redefine the economics of drug development by accelerating the discovery of novel and optimized small molecule therapeutics, today announced that it has added industry leaders Alexander Tropsha, Ph.D. and Robert N. Young, Ph.D. to the company’s Scientific Advisory Board.
Dr. Alexander Tropsha is a K.H. Lee Distinguished Professor at the University of North Carolina at Chapel Hill Eshelman School of Pharmacy and Chief Domain Scientist for Molecular Informatics at the Renaissance Computing Institute, UNC-Chapel Hill. He has extensive expertise in computational chemistry, structural bioinformatics and cheminformatics, which brings together chemistry and computer science to assist in the discovery of new drugs. He has authored more than 260 peer-reviewed papers as well as 25 books and chapters. In addition to serving as pharmacy professor, Dr. Tropsha is also an adjunct professor for the UNC Department of Biomedical Engineering and the Department of Computer Science and is a member of the UNC Lineberger Comprehensive Cancer Center. Dr. Tropsha is an elected Fellow of the American Institute for Medical and Biomedical Institute (Class of 2021).
Dr. Robert N. Young worked in various capacities at Merck Frosst Canada & Co., including Vice-President and Head of the Medicinal Chemistry Department and acting site head at the Merck Frosst Centre for Therapeutic Research (Montreal) and at MSD, Terlings Park Neurosciences Centre in the UK. Over his 30-year career, he led discovery efforts resulting in the development of Singulair®, Vioxx®, Arcoxia®, Previcox®, Tredaptive® and Odanacatib. Dr. Young is Professor of Chemistry and Merck Frosst-B.C. Leadership Chair in Pharmaceutical Genomics, Bioinformatics and Drug Discovery in the Chemistry Department, at Simon Fraser University. His current research is focused on the design and synthesis of novel pharmacological probes and proof-of-concept molecules for the discovery of new drug targets. Dr. Young founded Mesentech in 2016, a pre-clinical platform company that is developing therapeutics to treat a range of bone diseases. His many honours include winner of the Prix Galien, American Chemistry Society (ACS) Hero of Chemistry, the Order of Canada (MC), Fellow of the Royal Society of Canada, the Chemical Institute of Canada and President of the Canadian Society of Pharmaceutical Sciences (CSPS).
“The Variational AI team is pleased to be able to tap into the deep scientific expertise of Drs. Tropsha and Young to advance our efforts to revolutionize the development of new therapeutics,” said Handol Kim, co-founder and CEO, Variational AI. “As we seek to identify new drug-like small molecules with the potential to impact multiple disease areas, it is critical to have the input from chemistry leaders to ensure our generative AI platform is informed by leading medicinal and computational chemistry expertise.”
Drs. Tropsha and Young join current SAB member Artem Cherkasov, Ph.D., who was recently awarded the esteemed Tier 1 Canada Research Chair in Precision Cancer Drug Design. He is a professor of medicine at the University of British Columbia (Vancouver, Canada) and head of the Therapeutics Development Core at Vancouver Prostate Centre. Throughout his impressive career, his research has focused on computer-aided drug discovery (CADD), AI-guided drug design, cheminformatics and the development of novel, precision cancer therapies. He has participated in the development of eight out-licensed drug projects and co-authored more than 200 research papers, 80 patent filings and several book chapters to date. In 2021, he received UBC Faculty of Medicine Distinguished Achievement Award for Excellence in Fundamental Science.
Variational AI uses machine learning to discover novel, drug-like small molecules. The company’s algorithm, Enki, learns from a training set of molecules screened against drug targets from both experimental and computational sources and then generates novel molecular structures which are optimized for properties to avoid common causes of drug attrition and accelerate drug development with the goal of reducing early-stage drug discovery to months versus years.
About Variational AI
Variational AI uses state-of-the-art machine learning in a data-efficient method to rapidly generate novel and diverse compounds that are optimized for multiple properties to avoid the most common causes of drug attrition and increase clinical probability of success. Variational AI works with leading biopharmaceutical partners and is developing its own internal pipeline. To learn more, visit http://localhost:8000.