One of the most common questions we receive about the Maximizing Investigators’ Research Award (MIRA) program is the likelihood of an application’s funding given a certain overall impact score.
Frequent readers of this blog may note that we typically provide statistics as they relate to our R01 portfolio, but we’ve yet to provide a similar “funding curve” for the MIRA program. One reason that MIRA applications haven’t been included in these analyses is that, unlike most R01 applications, MIRA R35 applications don’t receive a percentile score. The percentile score allows for normalization of overall impact scores across study sections to account for any differences in scoring behavior that are observed in review panels. See the Office of Extramural Research’s comprehensive blog post for more information about overall impact scores and percentiles.
Because all MIRA applications up to this point have been reviewed in special emphasis panels, which can change in composition and focus from round to round, they haven’t been percentiled. Instead, they receive an overall impact score that’s considered along with a number of other factors when making funding decisions. Bearing this in mind, the following analyses focus on the distributions of overall impact scores and funding outcomes for the MIRA program from Fiscal Year (FY) 2016 to 2019 for both early stage investigators (ESI) and established investigators (EI).
ESI MIRA Applications: FY 2016-2019
Figure 1: Distribution of Funded and Unfunded ESI MIRA Applications by Overall Impact Score, FY 2016-2019. Funded applications are designated with solid bars, while unfunded applications are designated with striped bars. Applications with a priority score >60 were assigned a score of 60 in this chart.
Figure 1 shows the distribution and funding of ESI MIRA applications. Relatively few ESI MIRA applications received overall impact scores below 20, and most applications scoring under 40 received funding. All ESI MIRA applicants with unfunded applications scoring below 20 received a comparable research project grant (RPG), such as a DP2 or R01, instead of a MIRA.
EI MIRA Applications: FY 2016-2019
Figure 2: Distribution of Funded and Unfunded EI MIRA Applications by Overall Impact Score, FY 2016-2019. Funded applications are designated with solid bars, while unfunded applications are designated with striped bars. Applications with a priority score >60 were assigned a score of 60 in this chart.
Figure 2 shows the corresponding data for EIs, which were reviewed by different study sections than the ESI MIRAs. Overall, EIs scored better than ESIs. To some extent, this is expected because EIs have additional experience writing proposals and have longer track records for the panels to assess. (Note that in order to be eligible for the EI MIRA program in this time period, principal investigators had to already have NIGMS funding.) The observation of similar review differences in R01-equivalent applications by career stage was one reason that NIGMS chose to issue independent funding opportunity announcements for ESI and EI MIRA applicants and to review the groups separately from one another. With awardees from the ESI MIRA program now coming in for renewals of their first grants alongside EI MIRA renewals, those on their first renewals will be clustered together in review and scored relative to others at a similar career stage. We’re paying close attention to their review outcomes because we and others have observed that the first grant renewal is a particularly challenging hurdle for early career investigators.
MIRA Funding Curves: FY 2016-2019
Figure 3: Funding Curves for EI and ESI MIRA Applications, FY 2016-2019. Applications for both EI MIRA (solid line) and ESI MIRA (dashed line) tend to be funded at overall impact scores of 40 and below, with declining likelihood of funding at high scores. The curves are smoothed by including applications and awards with impact scores within 2 points of the value displayed, creating a rolling average for the fraction of funded applications. The dip in funded ESI MIRA applications below impact scores of 20 reflects applicants who received funding from an alternative RPG mechanism such as a DP2 or R01 instead of the MIRA.
Figure 3 demonstrates the likelihood of an application’s funding outcome given the overall impact score for both programs. Although, as described above, the underlying distribution of scores differs, both EI and ESI MIRA programs have similar funding curves, with a decrease in funding rate beginning with scores around 40, and applications with scores above 50 unlikely to receive funding.
At some point in the future, if standing MIRA study sections are established and generate a sufficient history of review scores, we may begin using percentiles for MIRA applications. We’ll continue to periodically update the community on the outcomes of the MIRA program.
One Reply to “Funding Trends: MIRA Applications and Overall Impact Scores”
This is very helpful. Is a similar distubution expected for FY 2021 and 2022? Could you please do updated graphs for FY 2020 data?