GrantCheck—an AI Solution for Guiding Grant Language to New Policy Requirements: Development Study
GrantCheck demonstrates the feasibility of deploying institutionally hosted, artificial intelligence-driven systems to support compliant and researcher-friendly grant writing. Beyond administrative efficiency, such systems can indirectly safeguard public health research continuity by minimizing grant delays and funding losses caused by language-related policy changes. By maintaining compliance without suppressing scientific rigor or inclusivity, GrantCheck helps protect the pipeline of research that advances biomedical discovery, health equity, and patient outcomes. This capability is particularly relevant for proposals in sensitive domains-such as social determinants of health, behavioral medicine, and community-based research-that are most vulnerable to evolving policy restrictions. As a proof-of-concept development study, our implementation is tailored to one institution's policy environment and security infrastructure, and findings should be interpreted as preliminary rather than universally generalizable.
Authors
- George Matthew (ORCID: https://orcid.org/0000-0003-3225-6951)
- A. Moneim Zaki
- Asil Oztekin (ORCID: https://orcid.org/0000-0001-5741-4261)
- Katherine Luzuriaga (ORCID: https://orcid.org/0000-0002-5561-1787)
- Brian Coleman
- Qiming Shi (ORCID: https://orcid.org/0000-0001-5829-4345)
- Adrian Zai (ORCID: https://orcid.org/0000-0002-2972-6839)
- Paul F. Langlois
- Steven Wong (ORCID: https://orcid.org/0000-0001-8667-0846)
- Heather Jenkins
- Jeffrey Bortle
Institutions
- UMass Memorial Health Care (US)
- University of Massachusetts Lowell (US)
- University of Massachusetts Chan Medical School (US)
- UMass Memorial Medical Center (US)
Publication Details
- Journal
- JMIR Formative Research
- Published
- 2025-10-29
- DOI
- https://doi.org/10.2196/79038
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.00