An investigator’s long-term success depends not only on securing funding, but on maintaining a stable funding stream. One way to assure continued funding is to submit a competing renewal application. However, as we noted earlier this year, while new investigators were almost as successful as experienced investigators in obtaining new (type 1) R01s, the difference between new investigator and experienced investigator success rates widens when looking at competing renewals (type 2s), and success rates of new investigators’ first renewals were lower than those of experienced investigators. In addition, we know that since the end of NIH’s budget doubling in 2003, success rates for competing renewals of research project grants overall have decreased. To further understand trends in success rate for R01 competing renewals (“type 2s”) I’d like to share some additional analyses where we look at characteristics of type 2 R01 applications, and the association of their criterion scores with overall impact score and funding outcomes.
In order to develop and implement data-driven policy, we need to carefully analyze our data to understand the “stories behind our metrics.” Without analyzing our data to know what’s going on, we’re essentially flying blind! A group of authors from the NIH Office of Extramural Research sought to investigate the stories behind peer review scoring and why some grant applications are more likely to be funded than others. They extended analyses previously reported by NIH’s Office of Extramural Research and National Institute of General Medical Studies. Last month, they published their analysis of over 123,000 competing R01 applications and described the correlations of individual component peer review scores – significance, investigator(s), innovation, approach, and environment – with subsequent overall impact score, and funding outcome. ….