7/23/14-MIRA MIRA on the wall, who’s the fairest funding system of all?

The Maximizing Investigators Research Award (MIRA) program recently proposed by the National Institute of General Medical Science (NIGMS) at the NIH is a huge step in the right direction to increase the fairness and efficiency of funding scientific research. See this link.

http://loop.nigms.nih.gov/2014/07/comment-on-proposed-pilot-to-support-nigms-investigators-overall-research-programs/comment-page-1/#comment-7121

The basic idea is that researchers will be funded based on their past productivity and general research plans AS OPPOSED to a grant application to fund a specific research topic. No specific aims pages will even be required! In January, I argued for just such a system in my blog “New NIH Funding Model-Fund people, not projects”:

http://watersheding.wordpress.com/new-nih-funding-model-fund-people-not-projects/

Hey, maybe they listened to me! This blog details the advantages of such a system so I will not rehash them here, but rather I will describe what MIRA intends to be.

MIRA is currently gathering information. There are still many details that need to be worked out, and NIGMS is seeking the scientific communities’ opinions about this new funding paradigm. The three most important topics to me are:

  1. What metric will be used to measure past productivity. I think there are some metrics that we can all agree on, papers and total citations being primer examples. But what about intellectual property? Mentoring? Presentations at conferences and other universities? And how do you judge the impact a researcher has had on the public well-being. The ultimate goal of the NIH, which is supported by the US taxpayer, is to provide solutions to medical problems of the country. How do we quantify the value of practical applications such as new diagnostics or treatment strategies that have actual clinical use but may not move the scientific needle as much as the latest hot paper on basic research published in Science?
  1. Removing bias from the funding decision as much as possible. It is essential that we determine a mechanism to quantify past productivity AS MUCH AS POSSIBLE. Quantitative descriptions of the above metrics can be developed to remove bias. If the system simply becomes study sections of experts “picking” the most productive people to receive these awards then we have made no progress. The specifics of how these metrics will be quantified will be open for debate, and of course no perfect system will be found. But even an imperfect system that is quantitative is a vast improvement over a qualitative system of selecting members in the scientific “popularity crowd”.
  1. Past productivity must be normalized to total research funding. This point seems obvious to me, but I question whether normalization will occur. It is not sufficient to simply measure productivity but this must be normalized to total federal funding including all grants AND fellowship funding for graduate students and postdocs. Obviously, researchers with increased funding should be expected to have increased productivity and be held to a higher standard. If productivity levels are similar to a researcher with much less funding, then funding should be reduced for the “rich” researcher and increased for the “poor” researcher. If normalization does not occur, then the system will quickly evolved into a positive feedback loop whereby the “rich get richer”.

 

MIRA is looking for comments in the following areas:

  1. The merits of this funding program for established and early stage investigators.
  2. The likelihood that established and early stage investigators would apply for NIGMS MIRAs.
  3. Concerns about the NIGMS MIRA proposal.
  4. Suggestions for changes to improve the NIGMS MIRA proposal or associated processes

I encourage you to check out the MIRA link above and give NIGMS your opinions, or better yet you can repeat mine. This is a fantastic move and I applaud the Institute for thinking outside of the box. This type of funding program will encourage that from all of us!

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