Jeya Chelliah B.Vsc Ph.D
Why do well-designed, innovative proposals still fail before peer review discussion ever begins? The answer increasingly lies outside the science itself. Modern NIH funding decisions are shaped not only by merit, but by portfolio balance, trend saturation, and strategic prioritization at the Institute level. Investigators often discover—too late—that their “novel” idea closely resembles multiple recently funded projects, or that an entire subfield is being deprioritized without any explicit announcement. In such cases, rejection reflects misalignment, not poor science.
What has changed recently is not the competitiveness of funding alone, but the feasibility of performing systematic funding intelligence before writing. Advances in large language models (LLMs) now allow researchers to analyze NIH award portfolios at scale—detecting patterns that are invisible through manual review.
The Grant Compass, the first volume in the eScienceInfo Intelligence Series, documents this data-driven approach.