Jackson Laboratory Receives $30 Million ARPA-H Award to Develop AI-Powered Virtual Hearts for Drug Safety Testing
核心洞察
The Jackson Laboratory received up to $30 million from ARPA-H (搜索) to develop CARDIOVERSE, an AI-powered platform using virtual hearts to predict drug cardiotoxicity (搜索) before human trials.
The initiative combines genetically diverse mouse models and human stem cells with artificial intelligence to create digital twins of the human heart (搜索) that can simulate drug responses across different patient populations.
CARDIOVERSE aims to address cardiotoxicity (搜索), which causes up to 15% of drug withdrawals after FDA approval and represents a leading cause of clinical trial failure.
The Jackson Laboratory (JAX) has secured an up to $30 million contract from the Advanced Research Projects Agency for Health (ARPA-H (搜索)) to develop CARDIOVERSE, a groundbreaking initiative that combines artificial intelligence, stem cells, and genetic variation to predict drug safety before human trials. The project represents a significant advancement in computational toxicology, specifically targeting cardiotoxicity (搜索)—one of the most persistent challenges in pharmaceutical development.
Addressing a Critical Drug Development Challenge
Despite passing early safety standards, more than 90 percent of drugs fail, often due to unforeseen toxicities that emerge late in clinical trials. Cardiotoxicity (搜索), when potential drugs interfere with heart (搜索) function, represents a leading cause of clinical trial failure and is responsible for up to 15 percent of withdrawals of new drugs after FDA approval.
"Too many promising medicines never reach patients because we can't predict early enough who they will help and who they might harm," said Lon Cardon, JAX president and CEO. "With CARDIOVERSE, we're building virtual hearts that more accurately reflect the broad genetic backgrounds of real people."
Revolutionary Virtual Heart Technology
The CARDIOVERSE platform will leverage mice and human stem cells that model the range of genetic backgrounds found in people, combined with advanced artificial intelligence to create computational "digital twins" of the human heart (搜索). These virtual hearts will serve as advanced computational models that simulate electrophysiology, contractility, and metabolic responses.
Matt Mahoney, JAX computational biologist and project lead, described the ambitious scope: "This is a moonshot vision. Imagine a future where computational models predict drug safety so reliably that it becomes ethical to move forward on computational evidence alone. That would revolutionize drug development, making it far more affordable and accessible."
Capturing Genetic Diversity at Scale
JAX's recent acquisition of the New York Stem Cell Foundation (搜索) (NYSCF) enables the team to profile cellular models at unprecedented scale using cutting-edge robotic automation. The team will use the Global Stem Cell Array to generate induced pluripotent stem cells (iPSCs) that represent genetic diversity found across patient groups.
The AI algorithms will be trained using data from mice and human cells that replicate human heart (搜索) function and capture the genetic variability present across patient populations. This approach goes beyond traditional safety predictions by uncovering how genetic differences control individual responses to treatment.
Identifying Rare but Dangerous Reactions
Current computational models estimate the overall chance a drug will be deemed unsafe, but not who might be affected or how severe the response could be. "It's like a weather forecast that predicts a 50 percent chance of rain but doesn't say whether it will be a drizzle or a hurricane," Mahoney explained.
By simulating hundreds or thousands of virtual hearts across different genetic backgrounds, CARDIOVERSE will identify rare but serious reactions before human trials begin. Even if only one in a thousand patients experiences a severe reaction during clinical trials or after approval, regulators must take that risk seriously.
Collaborative Research Framework
Working with partners from the University of Michigan, InSilicoTrials Technologies (搜索), and the University of Connecticut Health Center, Mahoney's team will investigate molecular mechanisms inside the heart (搜索). They will study gene activity and metabolic changes following drug exposure—insights that could reveal biomarkers and genetic risk factors that make certain populations more vulnerable to toxicity.
Project co-leads include JAX scientists Nadia Rosenthal, recognized for her expertise in high-resolution imaging of tiny mouse hearts; Paul Robson, a stem cell biology expert and lead developer of the genetically varied human iPSC panel; and Travis Hinson, a cardiologist whose lab investigates inherited conditions leading to heart failure (搜索). They are joined by Daniel Paull of NYSCF, a pioneer in high-throughput automation for generating iPSCs at scale.
Potential Impact on Drug Development
The CARDIOVERSE platform could significantly reduce the need for large-animal studies, streamline FDA approval processes, and ensure safer, faster delivery of new therapies to patients. "It will be a big win if we can surrogate large-animal studies with a state-of-the-art computational platform," Mahoney said. "That would take an expensive experiment off the table and allow more drug candidates from lean startups that are not well capitalized to get to human trials."
The initiative will assemble one of the largest cardiotoxicity (搜索) datasets of its kind, using mice and human cells that represent a broad range of genetic profiles to generate critical data for training AI models. This comprehensive approach could improve patient stratification in clinical trials and give companies greater confidence in advancing drugs to later stages, enabling safer, more precise decisions about which therapies should move forward.