Throughout discussions of the NIH peer review system, it has been clear (and not at all surprising) that different individuals and groups have quite different perspectives on the NIH enterprise. This goes back to the "Enhancing Peer Review" process (and well before) and continues to the present with changes in policies and active discussions in a scientific society membership magazine (here,  here, and here) and in blogs (e.g. here),. For example, scientists who are early in their careers at present, in general, have different experiences, perspectives, and concerns than those of more established investigators. Much of the data that are presented reflect the entire NIH investigator pool although, in some cases, data for more limited subsets such as new investigators are discussed. Here, I analyze the outcomes for a different subgroup, namely the members of one section of the National Academy of Sciences.

The National Academy of Sciences is divided into sections, based on scientific field. The section I examined has 122 members at present. Let us first examine the characteristics of the group. The distribution of the members over the years in which they were elected to the National Academy is shown below:

The median for this distribution is 1995-1996.

The birth years for approximately 50% of these members were available online. In other cases, birth years were estimated from the year of receipt of his/her bachelor's degree or Ph.D. degree assuming an age of 22 for the receipt of a bachelor's degree and an age of 27 for a Ph.D. degree. Based on these estimated birth years, the median age at the time of election was 51 years old with a range of 38 to 71.

Of the 122 members, 108 had received substantial funding from the NIH extramural program during the period covered by NIH RePORTER (1991-present), 8 are or were members of the NIH intramural program and 6 did not receive substantial NIH funding during the period covered by NIH RePORTER.

The age distributions of research-active and research-inactive scientists is shown below:

Of the research-active investigators with estimated ages over 76, three are funded by the NIH extramural program, three are in the NIH intramural program, and one is active in industry.

Examination of the R01 funding records of the 108 investigators with extramural funding revealed some striking characteristics. Many of these investigators have had long-running R01 grants with the median for each investigator's longest running grant (largest suffix) of 26 years with a range of 4 to 49. 64 of 108 (59%) of the extramurally funded investigators had received one (or more) MERIT (R37) awards (extending an R01 grant for an additional cycle without a competing renewal) during the course of their career. 27 of 108 (25%) of these scientists have been HHMI investigators with all but two of these currently in such positions.

How have these investigators fared with regard to having applications funded in their initial (A0) versus amended (A1, A2) submissions? I recently posted data showing the percentage of A0, A1, and A2+ applications in the NIH-wide funded R01 grant pools from 1991 to 2014. The results for competing renewal (Type 2) grants for the 108 National Academy investigators are compared with the NIH-wide curves below:

The average percentage of funded R01 grants in the A0 pool for the National Academy members averaged 94% from 1991 to 2003 compared with 60% for all NIH investigators. The A0 curve for the National Academy members roughly follows the NIH-wide curve with a dip from 2004 to 2011. Overall, these two curves show an average difference of approximately 35%.

The results for new (Type 1) grants are shown below:

These data are somewhat noisy since those from the National Academy members come from only 130 new R01 grants. Again, however, the pool of R01 grants from the National Academy members include more A0 awards. From 1991 to 2003, the average percentage of A0 awards was 80% compared with 57% for the NIH-wide pool . The percentage of A0 awards for the National Academy members dipped from 2005 to 2008 and then recovered, tracking the NIH-wide curve. Overall, the average difference between the two A0 percentage curves is 30%.

The members of the National Academy of Sciences examined are a remarkable group of scientists, with important contributions throughout their careers and impressive recognition of their work including several Nobel Prizes. The purpose of this analysis was to put some quantitative context around the differences in experiences of these investigators with an average member of the overall NIH R01 grantee pool.

It is very important to note the positive feedback loops at work here. Success in getting funded and doing exciting science makes it easier to get additional funding without as much time commitment to grant writing. The time saved can then be spent doing more and better science, feeding back into the process again.

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