VeriSIM Life Awarded Federal Grant from National Institutes of Health for Substance Use Disorder Drug Discovery and Development

SAN FRANCISCO–(BUSINESS WIRE)–VeriSIM Life (VeriSIM), the leading artificial intelligence (AI)-enabled, unique R&D decisions de-risker for breakthrough drug development, announced today it has been awarded a $312,310 grant from the National Institute on Drug Abuse (NIDA), part of the National Institutes of Health (NIH), to fund AI-driven development of medications for substance use disorder (SUD). VeriSIM and UF Scripps Biomedical Research scientist Courtney Miller, Ph.D. will collaborate on the research and drug discovery project. Research reported in this announcement was supported by the National Institute on Drug Abuse of the National Institutes of Health under award number 1R43DA056084-01.

VeriSIM will leverage its proprietary BIOiSIM™ software platform and Translational Index™ to support the successful translation of drug candidates to develop effective SUD patient therapies more rapidly and accurately than traditional methods that depend on the experimental uncertainty of modeling for data, a long-standing impediment for further scientific progress.

“We are honored to receive the financial support from NIDA at NIH to collaborate with Professor Miller to prioritize clinically relevant drugs for substance use disorders using our AI-driven BIOiSIM™ platform,” said Dr. Jo Varshney, founder and CEO of VeriSIM Life. “Our aim is to enhance our data-driven drug development engine to uncover highly promising drug assets in a cost and time-effective manner. Dr. Miller is an accomplished researcher in the substance use field and so we look forward to developing what we both hope will be a commercially viable asset for the industry.”

SUDs represent a set of complex-chronic diseases with an interplay between genetic and environmental factors. The cost and time to develop a new molecular entity (NME) from the discovery phase to a successful registration has been increasing steadily over the years. With the recent advances in Machine Learning (ML) and Deep Learning (DL) drug development, there has been a greater interest from industry and academia in de-risked translational roadmaps as validated systems to streamline and accelerate development of the most promising therapeutic leads.

“Stimulant use is skyrocketing on the heels of the opioid overdose epidemic, but there are no FDA-approved therapies for stimulant use disorder,” said Dr. Miller, a professor in the UF Scripps Biomedical Research Department of Molecular Medicine. “In this new era of applying artificial intelligence and machine learning to the life sciences, it is my hope that working with VeriSIM and their unique capabilities will accelerate stimulant use disorder treatments to the clinic.”

According to the National Survey on Drug Use and Health, more than 8 million Americans have a drug use disorder. Amid the crisis of COVID-19, studies show there is a clear trend in increased drug use in the U.S. Deaths due to drug overdose spiked, primarily driven by potent synthetic opioids.