Intelligent Generator of Research (IGoR)

The Advanced Research Projects Agency for Health (ARPA-H), within the National Institutes of Health, is soliciting proposals for the Intelligent Generator of Research (IGoR) program. This initiative seeks to eliminate research inefficiencies and accelerate the development of therapies for complex diseases by establishing an AI-enabled interoperable research ecosystem. The program's scope involves developing mechanistic disease models that encode causal biological relationships, an AI orchestration layer for identifying knowledge gaps and designing experiments, a layered protocol architecture for reproducible experimentation, and a distributed marketplace of validated laboratories providing standardized, gold-standard data. These integrated components are intended to create a cycle of hypothesis generation and model refinement that produces validated knowledge at least ten times faster than conventional methods.

This solicitation, identified by number ARPA-H-SOL-26-155, is classified under NAICS 541715 for Research and Development in the Physical, Engineering, and Life Sciences (except Nanotechnology and Biotechnology) and PSC AN13 for Health R&D Services; Health Care Services; Experimental Development. There is no set-aside designated for this requirement. Performance will take place within the United States, and the response deadline is August 6, 2026. The agency has provided twelve attachments to guide submissions, including technical and management proposal instructions, task description documents, price proposal templates, and a draft model Other Transaction (OT) agreement.

ARPA-H is managing the acquisition through its ISO point of contact and intends to host a hybrid Proposers Day in the Washington, D.C. metro area in early June 2026. Recent updates to the notice include the addition of a draft model OT agreement and revisions to the solution summary format and instructions. By utilizing an automated and standardized approach to experimentation, the IGoR program aims to empower researchers to pursue complex or resource-intensive research directions that are currently hindered by existing technological or procedural constraints.