We are presenting fiscal year (FY) 2021 extramural grant data.
In times of stress and uncertainty, such as what we are all experiencing now, seeing something different may be welcome. With that in mind, we are taking a few moments to continue our annual tradition spotlighting NIH’s research investments, grant funding, and success rates from the previous fiscal year (FY).
We recently released our annual web reports and success rate data with updated numbers for fiscal year (FY) 2018. These web products represent annual snapshots of NIH research investments, which are highlighted in this post.
For the New Year, we resolve to make NIH data, reports, and analyses more accessible, interactive, and easy to use. For over a decade, the NIH Data Book has served as a helpful resource for describing funding trends on grants and contract awards, success rates, small business programs, peer review, as well as the scientific workforce. These data, presented as graphics and tables, have allowed you to get a better understanding of decisions made here at NIH. We are proud to announce a new edition is available for your 2019 reading list.
A few weeks ago, we touted the value of the NIH’s Research, Condition, and Disease Classification (RCDC) system to give us consistent annual reporting on official research budget categories and the ability to see trends in spending over time. RCDC’s robust scientific validation process, which allows for such consistency, provides public transparency into over 280 different NIH budget categories.
RCDC categories do not encompass all types of biomedical research. So, how can we get this type of data for other research areas that are not encompassed in RCDC categories, especially those which are newly emerging fields? Are we able to use the same thesaurus-based classification system to explore other research trends?
In May 2016, we posted a blog on “How Many Researchers” NIH supports. We cited the findings of a University of Wisconsin workshop, which concluded that the biomedical research enterprise suffers from two core problems: too many scientists vying for too few dollars and too many post-docs seeking too few faculty positions. We also noted that NIH leadership and others were increasingly interested in describing the agency’s portfolio not only in terms of the numbers of awards and dollars (as we do each year in our “By the Numbers” reports), but also in terms of the numbers of researchers those awards support. Today we show updated figures on how many researchers are vying for NIH support and how many are successful.
We recently released our annual web reports, success rates and NIH Data Book with updated numbers for fiscal year 2017. Looking at data across both competing and non-competing awards, NIH supports approximately 2,500 organizations. In 2017 about 640 of these organizations received funding for competing Research Project Grants (RPGs) which involved over 11,000 principal investigators.
As described on our grants page, the R21 activity code “is intended to encourage exploratory/developmental research by providing support for the early and conceptual stages of project development.” NIH seeks applications for “exploratory, novel studies that break new ground,” for “high-risk, high-reward studies,” and for projects that are distinct from those that would be funded by the traditional R01. R21 grants are short duration (project period for up to 2 years) and lower in budget than most R01s (combined budget over two years cannot exceed $275,000 in direct costs). NIH institutes and centers (ICs) approach the R21 mechanism in variable ways: 18 ICs accept investigator-initiated R21 applications in response to the parent R21 funding opportunity, while 7 ICs only accept R21 applications in response to specific funding opportunity announcements. As mentioned in a 2015 Rock Talk blog, we at NIH are interested in trends in R01s in comparison to other research project grants, so today I’d like to continue and expand on looking at R01 and R21 trends across NIH’s extramural research program. ….
In one of my earlier blog posts, I described an analysis looking at whether attempts at renewal are successful. We looked at data from fiscal years 2013-2015, and found that renewal applications have higher success rates than new applications, and that this pattern is true for both new and experienced investigators. In response to your comments and queries, we wanted to follow up on the analysis with some historical data that looks are whether success rates of competing renewals decreased disproportionately compared to new grant applications’ success rates. ….
On my first day on the job as NIH Deputy Director for Extramural Research, one of my colleagues asked me a question: Is it true that it is more difficult to renew a grant than it is to get one in the first place? Some people wonder whether NIH’s interest in supporting new investigators who are trying to get their first grant negatively impacts the other investigators’ attempts to renew their grants.
To address this question we gathered data on R01-equivalent success rates for new and experienced investigators seeking funding in fiscal years (FY) 2013 through 2015. ….