About the data

• Grants.gov Search2 API (federal) — open and forecasted opportunities across NIH, plus NSF, DOE, NASA, DARPA, NIST, USDA, SAMHSA, CDC, ACL, DOD/CDMRP, and VA. We search each category’s keywords, then keep only opportunities that classify into a tracked category and read as research (a relevance gate drops care/service, workforce, and deployment programs). U.S. government works are public domain (17 U.S.C. §105); the API is public and keyless.
• Curated foundation & nonprofit programs — major research funders that publish no API, manually curated with a source link: disease philanthropies (American Cancer Society, AACR, Damon Runyon, American Heart Association, ADA, the Michael J. Fox Foundation, amfAR, the Alzheimer’s Association, ADDF) and science philanthropies (Sloan, Simons, Packard, Schmidt Sciences, Moore, Open Philanthropy). No scraping, no legal ambiguity.

• Opportunities, not awards. Every listing is a call you can apply to — not a record of money already awarded.
• Research areas are auto-classified from each title and description using keyword rules. They are multi-label and best-effort — treat them as a guide.
• Foundation entries are curated and may go stale. Amounts and cycles reflect commonly published terms; deadlines that rotate annually are shown as “no set deadline.” Always confirm details on the funder’s page.
• Some federal records are sparse. Grants.gov often omits award amounts or the administering NIH institute; those fields are shown as unavailable rather than guessed.

By default the list shows opportunities you can act on now — open and closing soon. We never show a fabricated date: federal deadlines come straight from Grants.gov, rolling programs say “apply anytime,” and recurring programs whose next cycle isn’t posted are marked Anticipated with an expected-timing note instead of a date. Use the “upcoming & anticipated” filter (or the Status facet) to surface those. Letter-of-intent (LOI) due dates are shown when present and still upcoming.

NIH opportunities show aggregate application success rates by mechanism — e.g., NIH-wide R01 applications were funded at ~16% in FY2024 — pulled from the public NIH Data Book and shown with the fiscal year, applications/awards counts, and a source link. Institute-specific rates fall back to the NIH-wide figure for that mechanism. On paylines: NIH discontinued percentile paylines for 2026 under its Unified Funding Strategy, so we surface that context rather than a stale cutoff. These figures are historical aggregates — context for planning, not a prediction for any single application.

Listings are filterable by funding category (grouped into disease areas and research fields), research area, NIH institute, mechanism (activity code), career stage, clinical-trial requirement, status, funder, eligibility, funding cycle, minimum award, deadline, and whether NIH funding-rate data is available. Filters live in the URL, so any filtered view is shareable and bookmarkable.

• Letter-of-intent dates from NOFO documents — Grants.gov’s feed omits LOI dates; parsing the full NIH NOFO pages would surface them (note: many NOFOs require no LOI).
• Institute-specific success rates & historical paylines — Wayback-verified NIA AD/ADRD figures, beyond the NIH-wide rates shown today.
• Saved searches and deadline alerts (email / RSS).
• Historical “typical award size” benchmarks from NIH RePORTER.
• Upgrading the keyword relevance classifier (research vs. care/service, on-topic vs. tangential) to an embedding/LLM model — the deterministic rules in scripts/normalize/relevance.ts occasionally keep an adjacent grant.
• Deeper research-field coverage (space, advanced manufacturing, biotech) and the Grants.gov broad-sector taxonomy for maximum breadth.