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I found NIH data listing principal investigators (PIs) by the amount of awarded NIH grants in 2010 and decided to visualize them. Unfortunately, the distribution is too broad to be visualized meaningfully on a linear scale, so I scaled the bins logarithmically:

NIH_USD_per_PI_Distribution

The vertical red line is at 1 million USD per PI and the numbers indicate the total awards to PIs having more and less than 1 million in NIH awards.

Most problems in the biomedical research system and their causes are very difficult, some perhaps impossible, to quantify rigorously. Predicting unintended consequences of policy changes can be equally hard. However, I cannot think of drawbacks of some measures, such as funding policies that discourage labs in which PIs are responsible for more graduate students and post-doctoral fellows than they have time to train. PIs managing smaller labs are likely to need less money, have more time to think creatively and conceptually, provide better training to their students, and graduate fewer (and better prepared students) aspiring for academic positions. The key question for me is: What funding policies can encourage such changes with the lowest probability of unintended adverse consequences ?

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