The Validation of Peer Review through Research Impact Measures and the Implications for Funding Strategies

There is a paucity of data in the literature concerning the validation of the grant application peer review process, which is used to help direct billions of dollars in research funds. Ultimately, this validation will hinge upon empirical data relating the output of funded projects to the predictions implicit in the overall scientific merit scores from the peer review of submitted applications. In an effort to address this need, the American Institute of Biological Sciences (AIBS) conducted a retrospective analysis of peer review data of 2,063 applications submitted to a particular research program and the bibliometric output of the resultant 227 funded projects over an 8-year period. Peer review scores associated with applications were found to be moderately correlated with the total time-adjusted citation output of funded projects, although a high degree of variability existed in the data. Analysis over time revealed that as average annual scores of all applications (both funded and unfunded) submitted to this program improved with time, the average annual citation output per application increased. Citation impact did not correlate with the amount of funds awarded per application or with the total annual programmatic budget. However, the number of funded applications per year was found to correlate well with total annual citation impact, suggesting that improving funding success rates by reducing the size of awards may be an efficient strategy to optimize the scientific impact of research program portfolios. This strategy must be weighed against the need for a balanced research portfolio and the inherent high costs of some areas of research. The relationship observed between peer review scores and bibliometric output lays the groundwork for establishing a model system for future prospective testing of the validity of peer review formats and procedures.