The paylines at the various institutes making up the NIH are near historical lows, making it increasingly competitive to obtain funding. This is partially due to the recent budget sequesteration, but is also a result of flat government funding levels coming on the heels of years of double digit growth, as well as an unexpected funding “bump” from the fiscal stimulus package.
There have been many media reports, editorials, and even rallies bemoaning the 2013 cuts and the lack of funding increases in recent years. A major concern is the possible impact that the current constraints on grants will have on young scientists as they start their careers. Even with new investigator initiatives and suggested caps on the number of grants for established scientists, there is concern that important research efforts will go under-funded, or even unfunded, due to the current budget woes. So, the question of the day would seem to be whether or not the payline needs to be moved to improve the probability of grant success for all researchers and, even more critically, how this might be accomplished.
Eight percent funding (ten for new investigators) at some institutes does seem very small indeed. But in the end, could we be thinking about this in the wrong way? Might that number in fact be too high, at least for established investigators? The payline, and subsequently the number of funded scientists, comes down to a question of resource allocation and, to an extent, a question of whether or not the NIH should be setting stricter rules on the number of grants or the amount of money any single investigator can receive. Here, I argue that it is important to more closely examine cost-benefit ratios for all awards.
If we look at a small, random sampling of NIH grant awardees during 2013 (excluding program projects and small business grants) and compare these awards to production as measured by article output, an interesting trend can be observed. Averaging the awards and output for 3 randomly selected investigators whose 2013 grants total over $1 million dollars, we find an average dollar amount of $1.65 million and an average article production output of 30 for 2013 thus far. When looking at 3 random grantees awarded less than $1 million, we find an average funding amount of $573,000 and an average of 3 articles published in 2013, thus far. The numbers (although obviously my data set does not include the most robust sample size) would seem to indicate that more funding produces more articles.
Now, before you say this is obvious, the more interesting point here is that more funding would in fact appear to produce disproportionately more articles, implying that labs with more funding are significantly more productive than their smaller counterparts. This could be attributed to sheer resources. On the other hand, maybe study sections are doing the right thing—identifying investigators with the ability to rapidly shape scientific progress and awarding them appropriately. While a larger sampling of grants and a more detailed analysis of productivity now or in the coming years could alter these conclusions, it is important to start thinking about grants in this fashion— especially if funding continues to lag behind the rate of inflation.
So, is it fair to place restrictions on investigators making such significant contributions to science? Unfortunately, I think the answer is clear—restrictions could only serve to further reduce scientific output and therefore run against the needs and desire of the NIH. However, such a lack of restrictions on grant awards would also create more competitive conditions for all established investigators.
Obviously, it is important to support young researchers as they start their careers, and this should be accomplished by raising paylines significantly when it comes to first time submissions and awards. But beyond that point, grants should be made on the basis of merit alone, without regard for the amount of money awarded to any one investigator. This will prove challenging to many, but could ultimately produce the necessary change and accountability needed to push life science research forward.
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