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Updated: Aug 17, 2025

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
Published on: June 13, 2025
Reviewing knowledgebase and database grant proposals in the life sciences: the role of innovation
1SRI International, Artificial Intelligence Center, 333 Ravenswood Ave, AE206, Menlo Park, CA 94025, USA.
Abstract:
This article offers thoughts on reviewing grant proposals for biological knowledgebases and databases (KDs) in the hope of aiding grant reviewers and applicants in addressing the issue of innovation. Assessing such grant proposals involves a number of subtleties that are worthy of discussion, particularly for new reviewers and applicants. In part, this article is motivated by the release of two funding opportunity announcements by the US National Institutes of Health concerning KDs. We find that the amount of innovation required for different KD projects can vary significantly, particularly depending on where in its life cycle a given project is. Strong innovation is not necessarily required to have an impactful KD project. For example, PubMed has low innovation but high impact. The importance of innovation should be weighted differently for different KD projects depending on the challenges they face and their maturity. The score for the overall impact of a grant proposal might have little dependence on the innovation score, such as for a mature project that is already delivering strong impact.
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