Funders › Foundation for Innovative New Diagnostics › 2020
Grants paid by Foundation for Innovative New Diagnostics, tax year 2020
EIN 98-0407553 · Switzerland · Form 990, Schedule I · NTEE H80
In tax year 2020, Foundation for Innovative New Diagnostics (EIN 98-0407553) reported 28 grants paid totaling $5,080,841. Dataset version 2026.09.0, built 2026-09-03.
Every grant, 2020
| Tax year | Recipient | Match | Amount | Type | Purpose | Source filing |
|---|---|---|---|---|---|---|
| 2020 | Diagnostic Consulting Network Inc Carlsbad, CA | U | $2,583,053 | paid | 202113199349315546 | |
| 2020 | The Regents of the University of California La Jolla, CA | A | $283,592 | paid | 202113199349315546 | |
| 2020 | Drugs & Diagnostics for Tropical Diseases San Diego, CA | A | $279,900 | paid | 202113199349315546 | |
| 2020 | Vitalant DBA Vitalant Research Institute San Franscisco, CA | A | $260,658 | paid | 202113199349315546 | |
| 2020 | Dimagi Inc Cambridge, MA | U | $243,082 | paid | 202113199349315546 | |
| 2020 | Scanwell Health Los Angeles, CA | U | $240,268 | paid | 202113199349315546 | |
| 2020 | Chai -Clinton Health Access Initiation Inc Boston, MA | A | $180,741 | paid | 202113199349315546 | |
| 2020 | Llamasoft Inc Ann Arbor, MI | U | $157,400 | paid | 202113199349315546 | |
| 2020 | The Center for Affordable Health Bethesda, MD | U | $139,872 | paid | 202113199349315546 | |
| 2020 | Rutgers the State University of New Jersey Piscataway, NJ | A | $102,300 | paid | 202113199349315546 | |
| 2020 | The Broad Institute Inc Cambridge, MA | B | $77,500 | paid | 202113199349315546 | |
| 2020 | Exponent Natick, MA | D | $70,000 | paid | 202113199349315546 | |
| 2020 | Broadreach Consulting LLC Washington, DC | U | $65,258 | paid | 202113199349315546 | |
| 2020 | Johns Hopkins University Baltimore, MD | A | $57,899 | paid | 202113199349315546 | |
| 2020 | Washington University in St Louis St Louis, MO | A | $47,808 | paid | 202113199349315546 | |
| 2020 | Zeptometrix Buffalo, NY | U | $39,067 | paid | NONE | 202113199349315546 |
| 2020 | Sachin Silva Cambridge, MA | U | $37,720 | paid | analysis of diagnostics | 202113199349315546 |
| 2020 | Boston Children's Hospital Boston, MA | A | $32,578 | paid | 202113199349315546 | |
| 2020 | Colorado State University US Fort Collins, CO | A | $31,530 | paid | 202113199349315546 | |
| 2020 | Treatment Action Group New York, NY | A | $27,951 | paid | 202113199349315546 | |
| 2020 | Mriglobal Kansas City, MO | A | $25,224 | paid | Lab testing & system assistance | 202113199349315546 |
| 2020 | University of Washington Seattle, WA | A | $21,706 | paid | 202113199349315546 | |
| 2020 | Diabetes Technology Society (dts) Burlingame, CA | A | $20,250 | paid | Consolidation of publications | 202113199349315546 |
| 2020 | Mmu Ann Arbor, MI | U | $16,228 | paid | assessment of molecular ID assay | 202113199349315546 |
| 2020 | Biomedical Research Institute Rockville, MD | A | $14,556 | paid | 202113199349315546 | |
| 2020 | Boston University Boston, MA | A | $12,450 | paid | 202113199349315546 | |
| 2020 | Meso Scale Diagnostics LLC Rockville, MD | U | $6,250 | paid | 202113199349315546 | |
| 2020 | Serimmune Inc Goleta, CA | U | $6,000 | paid | 202113199349315546 |
Match tier: A Reported EIN · B Exact name and place · C Strong name match · D Probable name match · U Unresolved. Tiers C and D are inferred, not reported; see how matching works.
Recipient matching for this dataset version has not yet completed its independent precision check. Tier A rows carry the EIN the filer reported; tiers B–D are the matcher's inference and should be read as leads until the check is published on the methodology page.
Derived from IRS Form 990 e-file XML. Dataset version 2026.09.0, built 2026-09-03. All years for this funder.
The same organization elsewhere in the program: exempt status and filing health · federal awards · grant guidance · open opportunities.
This is informational only, derived from public data on the dates shown. It is not an eligibility determination, and not legal, tax, or accounting advice. Verify against the official source before relying on it.