Open Mike

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FY2016 By The Numbers

Over the past few days, we released our annual web reports, success rates and NIH Data Book with updated numbers for fiscal year 2016. Overall, we see steady increases. In addition to looking back over the numbers we typically highlight in this post, we want to point out several new research project grant (RPG)-specific activity codes used to support extramural research. FY 2016 saw the launch of some new activity code uses, such the Phase 1 Exploratory/Developmental Grant (R61 – in lieu of the R21), of which 14 new projects were funded. Large-scale RPGs with complex structures like the RM1 increased substantially from 2015 (when we first began to fund RM1s), from slightly over $4 million in grant money to over $15 million. These activity codes, as well as those more familiar to you such as the R21, collectively supported a variety of specific scientific areas such as the improvement of outcomes in cancer research, support pilots for Alzheimer’s research, genomic research centers, and clinical studies for mental disorders.

Over the past year, NIH grants supported almost 2,400 research organizations, including higher education, independent hospitals and research institutes. We received 54,220 competing research project grant applications in fiscal year 2016, a steady increase. Of these, 30,106 were applications for R01-equivalent grants (as a reminder, R01-equivalents are mostly R01s, but also include activity codes for similar independent RPG programs such as the R37 MERIT award). Although, organizations have seen increased support for RPGs in 2016 totaling $17,137,754,907, for competing and noncompeting grants, the average size of awards continued to increase to $499,221, a historical high for both competing and non-competing awards.

The success rate for competing FY 2016 RPG applications was 19.1% compared to 18.3% in FY 2015. The 2016 success rate for competing R01-equivalent applications was also slightly higher than last year (19.9% compared with 18.9% in 2015). Success rates continue to remain far below the 30% levels we saw 15-20 years ago, during the NIH doubling; the low success rates reflect the hypercompetitive environment we continue to face.

I’ve included a highlight of some additional numbers below from the 2016 fiscal year as well the two prior fiscal years.

 

  2014 2015 2016
Research Project Grants
Number of research project grant (RPG) applications: 51,073 52,190 54,220
Number of new or renewal (competing) RPG awards: 9,241 9,540 10,372
Success rate of RPG applications: 18.1% 18.3% 19.1%
Average size of RPGs: $472,827 $477,786 $499,221
Total amount of NIH funding that went to RPGs (both competing and noncompeting): $15,635,912,476 $15,862,012,059  $17,137,754,907
R01-equivalents
Number of R01-equivalent grant applications: 27,502 28,970 30,106
Number of new or renewal (competing) R01-equivalent awards: 5,163 5,467 6,010
Success rates for R01-equivalent applications: 18.8% 18.9% 19.96%
Average size of R01-equivalent awards: $427,083 $435,525 $458,287
Total amount of NIH funding that went to R01-equivalents (both competing and non-competing): $10,238,888,890 $10,279,687,172 $11,077,251,191
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7 thoughts on “FY2016 By The Numbers

  1. Does the nearly 20% success rate for R01’s include non-competing renewal? Because my Program officer told me that my Institute was funding R01’s to the 8th percentile.
    In fact, clarifying this specific number – “Where does my R01 need to rank in order to get funded” – is the question most relevant to investigators and is very difficult to determine from most of the statistics that NIH puts out.
    Another way of asking this question is, “Why are these success rates so dramatically discordant with Institutional paylines?”

    Thanks

  2. I echo Dr. Reeves’ question. Although an explanation for the discrepancy is published periodically through this and other NIH media, the explanation is more arcane than trying to figure out the Dewey Decimal System in High Elvish. Can a simple explanation be given that one can understand and easily explain to our colleagues?

    Heber Nielsen, MD

    • A percentile, defined in its broadest sense, is a relative ranking of an application within a set of applications. Not all applications are percentiled. Whether an application is percentiled depends on the grant mechanism, the institute, and the funding opportunity. Check out this Rock Talk post that walks through an example of how a percentile is calculated: More on Percentiling

      Many NIH institutes and centers, but not all, establish a payline, which is a percentile rank up to which nearly all R01 applications can be funded.

      A success rate is a year-end calculation based on the number of applications funded divided by the number of applications reviewed, and expressed as a percent.

      For more information, you might find this prior Rock Talk blog post helpful, as well: Revisiting the Relationship Between Paylines and Success Rates

  3. I find the rates of ~18-20% discordant from the 8%ile rates we are quoted by program staff, as well.

    So, to be clear and simple, without referencing another site/publication/source:
    (i) What is the average funding rate of first time (v.01) R01s;
    (ii) What is the average funding rate of resubmissions (v01A1); and
    (iii) What is the average combined funding rate (v.01 and v01A1) in aggregate.

    These are the crucial numbers.

    • The percentile payline is an estimate of what applications could be funded if we paid in strict percentile order at the full requested amount. These estimates are made by Institutes/Centers before the start of the fiscal year, and are not adjusted as conditions change (more or less money available for competing projects). They are applicable only to applications with percentile ranks.

      The success rate is a measure of the funding of projects, calculated by dividing the number of funded, competing applications by the summation of the number of reviewed, competing applications and funded carryovers. For a more thorough explanation of the success rate calculation, please refer to https://report.nih.gov/FileLink.aspx?rid=558. Applications replaced by later resubmissions (amendments) are not part of the equation.

      The average success rate of first-time R01-equivalent grants (A0) was 14.5 percent, while the average success rate of the first resubmission (A1) was 32.5 percent for an overall success rate of 20.0 percent in 2016. We have published several tables comparing the success of original applications and resubmissions. These tables can be found at https://report.nih.gov/success_rates/index.aspx
      Tables 7 – 10 under Research Project Grants, providing information on the comparative success by submission number.

  4. I agree- this slight of hand with the funding statistics is something that keeps coming up and I was hoping you would at least get past this practice and be more transparent. Your audience here is not like the general public who may understandably not see past this. And that is why we have so much trouble with the general public in getting support for science. How do you think the public views us when you say we are funding at above 20% when we know for sure that is not the case. We need a clear statement – of X applications submitted by study section, Y% were funded. My guesse is in the past few years funding rates in the study sections I go to has been 6%, which is driving the destruction of NIH as we know it. If you will not tell the story the way it truely is, then who else can we turn to?

    • In addition to the links posted in the replies above, the NIH Data Book contains data on funding rates (the per-investigator measure of whether funding was received), and other blog posts show the award rate by submission number – most recently here.

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