Predicting how a person’s heart will respond to a new medication remains one of the most persistent challenges in drug development. Despite decades of scientific advancement, cardiotoxicity—adverse effects on the heart—can still emerge unexpectedly during clinical trials or after a drug reaches the market, leading to costly failures and, more critically, serious harm to patients. Today, this long-standing obstacle is being addressed through a groundbreaking initiative: CARDIOVERSE, a $30 million project led by InSilicoTrials in collaboration with The Jackson Laboratory (JAX), and funded by the Advanced Research Projects Agency for Health (ARPA-H). The initiative aims to revolutionize cardiac drug safety by creating highly accurate, personalized virtual heart models. These digital twins will simulate how individual patients—accounting for genetic, biological, and physiological differences—may react to new therapeutics, enabling earlier and more reliable detection of potential heart risks. Dr. Matt Mahon, a key leader in the project and a pioneer in computational biology, is guiding the effort. The team is leveraging cutting-edge technologies, including artificial intelligence, multi-scale modeling, and data from diverse human populations, to build a platform that can predict cardiac responses with unprecedented precision. By integrating genomic data, real-world clinical information, and high-resolution biological models, CARDIOVERSE will help pharmaceutical companies and regulators make better-informed decisions earlier in the development process. This could significantly reduce the number of late-stage drug failures, cut development costs, and accelerate the delivery of safer, more effective treatments to patients. The project is part of ARPA-H’s broader mission to fund high-impact, high-risk research that addresses critical gaps in health innovation. With its focus on predictive modeling and patient-specific outcomes, CARDIOVERSE represents a transformative step toward a future where drug development is not only faster and more efficient, but also safer and more personalized.