HHS Proposes to Restructure Biomedical Research With AI

Artificial Intelligence & Machine Learning , Healthcare , Industry Specific HHS Proposes to Restructure Biomedical Research With AI ARPA-H Program Aims to Speed Up Disease Breakthroughs Using AI-Enabled Ecosystem Marianne Kolbasuk McGee (HealthInfoSec) • May 6, 2026     Share Post Share Credit Eligible Get Permission HHS' Advanced Research Projects Agency for Health is launching an AI initiative aimed at ultimately speeding up medical breakthroughs ten-fold. (Image: ARPA-H) Research breakthroughs tackling complex diseases and chronic illnesses can take years. The U.S. Department of Health and Human Services is hoping to speed that up ten-fold with artificial intelligence-enabled ecosystem of shared research and experimental procedures. See Also: Reduce Cloud Risk in Healthcare with Security by Default The Advanced Research Projects Agency for Health, a unit of HHS, is spearheading a five-year Intelligent Generator of Research grant program with the stated intent of disrupting a centuries-old status quo of research spearheaded by individual labs. The proposition for Igor, APRA-H says, isn't to put a biomedical research wrapper around a frontier large language system. The goal is "a cycle of hypothesis generation, experimentation and model refinement" that identifies promising new research, selects a testable proposition, designs an experiment and finds labs to conduct them. No more cross-lab negotiation and protocol adaptation, ARPA-H says. Igor will make transferring an experiment from one lab to another "as straightforward as sending a data file." Irreproducible biomedical research delays effective treatments for chronic and complex diseases. Some estimates find that more than 70% of researchers cannot reproduce another scientist's experiments and up to 89% of preclinical work cannot be fully reproduced. "Families shouldn't wait for breakthroughs while new knowledge trickles through the literature and researchers do experiments that are the most familiar rather than the most informative," said Alicia Jackson, ARPA-H director. "Igor will modernize how evidence is generated, shared and validated - so even research beyond our accelerated science portfolio can deliver breakthroughs in years, not decades." ARPA-H said the Igor program aims to develop an end-to-end autonomous biomedical research infrastructure with four major components: Computational models that move beyond statistical correlation and instead represent how diseases actually function biologically - from molecular and cellular interactions up through tissues, organs and whole-body systems; An AI orchestration layer that identifies knowledge gaps and designs the optimal experiments for researchers to run; A layered protocol architecture that enables any qualified laboratory to execute the same experiment reproducibly; A distributed marketplace of validated laboratories that execute standardized protocols and return "gold-standard" data. Those components will form "a cycle of hypothesis generation, experimentation and model refinement that enables researchers to create validated knowledge" many times more rapidly than conventional approaches today, ARPA-H said. "Ultimately, Igor will empower researchers at every level to pursue bold, unconventional research directions that are currently too slow, too complex, or too resource‑intensive." Some biomedical experts said the Igor effort - especially if combined with other collaborative efforts in medical research - could greatly accelerate medical advancements for some of the most intractable conditions. "One of the greatest opportunities the Igor effort can seize is to move beyond institutional datasets capturing insights in closed loops and for fixed sets of time toward continuously learning ecosystems that integrate longitudinal real-world information, digital biomarkers, molecular data, and clinical outcomes in ways that are actionable and reproducible," said Christian Rubio, executive director at EverythingAL, a non-profit focused on bringing technological innovations and data science to support care and cures for patients with ALS, also known as Lou Gehrig's disease. "Ultimately, we would hope Igor accelerates discovery itself, and the creation of a more connected and collaborative biomedical ecosystem that helps turn a flywheel of innovation," he said. ARPA-H is seeking Igor solution summary proposals until June 25. After submission of a solution summary, proposers "will either be encouraged or discouraged from submission of a full proposal." Full proposals are due Aug. 6. HHS also expects to use AI tools to help vet the Igor proposals it receives. "Because of the anticipated significant interest in the Igor program, Igor is piloting secure large language model tools to assist with the initial review of solution summaries," ARPA-H said. ARPA-H did not publicly disclose the amount of funding planned for the Igor program. Igor is not the first HHS initiative pushing for AI to help ultimately speed up and improve biomedical breakthroughs for patient treatments. The Food and Drug Administration said late last month it is launching an expanded pilot program to increase the efficiency, speed and quality of decision-making in clinical trials through the use of AI. FDA said its aim is for AI to enable "real-time" clinical trials (see: US FDA Piloting Use of AI for Real Time Clinical Trials).