PhaseV Applies Machine Learning for Successful Clinical Trials

PhaseV harnesses machine learning to optimize clinical trials, a costly endeavor in drug development. Dr. Raviv Pryluk, CEO of PhaseV, asserts that machine learning can reduce subject recruitment needs by 30 to 50 percent. By conducting millions of simulations, AI aids in risk assessment, subject selection, and defining clinical endpoints. During trials, AI enables dose adjustments based on subject data, akin to a GPS recalculating routes. Adaptive enrichment identifies patient subsets benefiting most from the drug. AI expedites time to market, identifies failing trials for early termination, and aids financial forecasting. Pryluk's insights illustrate how AI revolutionizes drug development, potentially saving costs and expediting therapeutic innovations.