Sample NIH Summary Statement: Impact Score 23 - What a Strong Application Looks Like

SBIR Grant Writers · March 6, 2026

An impact score of 23 is an excellent result. For most NIH Institutes, this falls well within the payline for SBIR Fast-Track applications and will likely be funded. But even strong summary statements contain useful information. Understanding what made this application successful helps you replicate those elements in your own proposals.

Note: This summary statement is entirely fictional. All company names, investigator names, and project details are fabricated for educational purposes. Names have been redacted to simulate a real document.

The Application at a Glance

This fictional Fast-Track SBIR application proposed a tablet-based cognitive screening platform for early detection of age-related cognitive decline. The technology uses gamified cognitive tasks and machine learning to provide daily monitoring that detects changes months earlier than annual clinical screening.

What the Resume Tells Us

The Resume and Summary of Discussion is unusually positive for this application. The committee was described as "uniformly enthusiastic" - language you rarely see in summary statements. Minor concerns about recruitment timelines and technological literacy stratification were noted but "did not significantly dampen enthusiasm." When you see that phrasing, the application is in strong shape.

The Reviewer Scores

All three reviewers scored this application consistently well. Look at the pattern:

Reviewer 1

Reviewer 2

Reviewer 3

What Made This Application Strong

Reading across all three critiques, several themes emerge that explain the strong score:

Compelling preliminary data. The pilot study demonstrating detection of cognitive changes 4.2 months earlier than standard screening appeared in every reviewer's Innovation strengths. Real, quantified preliminary data transforms a theoretical claim into a credible one.

Team depth. Multiple reviewers praised not just the PI but the breadth of the team, including the advisory board. One reviewer noted the team had "prior experience developing and validating digital health diagnostics" - evidence of execution capability, not just scientific knowledge.

Clear go/no-go criteria. Every reviewer noted well-defined milestones with quantitative thresholds. This tells the panel you know what success looks like and have planned for the possibility that the technology may not perform as expected.

Rigorous study design. The multicenter RCT design, appropriate sample size calculations, and statistical plans were consistently praised. Even the Approach scores of 3 were driven by minor concerns (recruitment timeline, stratification variables) rather than fundamental design flaws.

Even Strong Applications Have Weaknesses

This application was not perfect. Reviewers flagged several concerns that, while minor in this context, could become major problems in a weaker application:

• Recruitment timelines were called "ambitious" by two of three reviewers. If the team had not provided strong letters of support from clinical sites, this could have been scored more harshly.
• Stratification by age alone was noted as insufficient - baseline cognitive function and technological literacy should have been included. This is the kind of methodological detail that separates a score of 2 from a score of 3 on Approach.
• The company's early-stage status was mentioned by Reviewer 3. For SBIR applications, reviewers expect lean startups, but they also want to see a credible path to organizational growth as the project scales.

What This Applicant Should Expect Next

With a score of 23, this application is almost certainly within the payline. The applicant should contact their Program Officer to confirm funding expectations and discuss any administrative requirements. Since there were no Unacceptable findings on Human Subjects or other review elements, the path to award should be straightforward.

See Other Score Examples