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Modeling Research Project Grant Success Rates from NIH Appropriation History: Extension to 2020

Berg, J.

2020-11-25 scientific communication and education
10.1101/2020.11.25.398339 bioRxiv
Show abstract

Communication of the likelihood that a grant proposal is funded is important for individual researchers and academic institutions. For research project grants (RPGs) funded by the US National Institutes of Health (NIH), this is measured by the success rate, the fraction of grants reviewed in a given fiscal year that are funded. In 2016, I posted a relatively simple computational model that allowed estimation of these success rates from historical data of NIH appropriations and associated data, based largely on the fact that commitments to fund NIH grants are typically made over four fiscal years rather than coming from a single fiscal years appropriations. Data for appropriations and success rates for fiscal years 2016-2020 are now available, allowing this model to be tested without no adjustable parameters. Over this period, the NIH appropriation increased by 29.7% to $39.313 billion, yet the RPG success rate increased from 0.183 to 0.201, a relative increase of only 9.8%. This difference is accurately reproduced by the model, indicating that the modest changes in success rate despite large appropriation increases reflect the consequences of the funding grants from multiple fiscal years and the response of the biomedical research community in submitting an increased number of proposals. The model can also be extended to estimate the success rates for individual institutes with reasonable accuracy.

Matching journals

The top 2 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.