NIH Proposes Changes to Research Grant Scoring System

The US National Institutes of Health (NIH) is considering a major change in how it evaluates research grant proposals. For the past 50 years, the agency has shared precise numerical scores given by peer reviewers with researchers. Under the new plan, projects would be ranked into three categories: top, middle, and bottom based on their quality.

This shift aims to give NIH more flexibility in awarding grants according to agency priorities, rather than relying solely on peer reviews. The new system encourages NIH’s 27 institutes to balance factors like scientific merit, health priorities, and overall research needs when deciding funding.

Proponents argue the current scoring system creates a false sense of precision since it averages scores from just three reviewers. However, some scientists worry the lack of transparency could allow political appointees to influence grant decisions, especially under the Trump administration where such interference has been more common.

Critics like Jenna Norton, who protested NIH changes during Trump’s tenure, say researchers might not challenge funding rejections if they don’t know their scores. Michael Lauer, a former NIH official, acknowledges the plan has merits but highlights concerns about political bias.

Under the current system, proposals are scored by expert panels and only top 50% advance for full discussion. With the new plan, applications would be grouped into three categories: most competitive (top 25%), competitive (next 25%), and not discussed (bottom 50%). This change aims to reduce bias against innovative projects.

While some support this approach, others suggest targeted solicitations on specific research topics could better promote innovation. Critics also note that even the highest-scoring grants often don’t lead to significantly more citations than those just below them, suggesting the system’s arbitrary nature.

Some researchers propose a lottery-style funding system for top-ranked proposals, which is gaining traction in Europe. This approach would award funds randomly among high-scoring applications, potentially reducing bias and encouraging more diverse research.