Skip to main content
Premium Trial:

Request an Annual Quote

What Price Innovation?


When three economists decided to compare the success of grant funding by the National Institutes of Health with that of the Howard Hughes Medical Institute, they never intended the results of their work to be an attack on the NIH model. But many consider that view to be the take-home message of the study.

In a paper due to be published late this year or early next in The RAND Journal of Economics, co-
authors Pierre Azoulay, Joshua Graff Zivin, and Gustavo Manso use the different funding approaches of HHMI and NIH as a testbed for their theories on how to craft an incentive program that encourages innovation. The organizations' funding models differ dramatically — compared to NIH, HHMI offers much more flexibility in research, focuses on people instead of projects, and has a grace period of funding for investigators whose grants aren't renewed — allowing the authors to dig into whether one system is more supportive of cutting-edge research.

The study looked at a group of HHMI-funded scientists along with two control groups — one composed of award-winning scientists early in their careers, and the other made up of the best of the best NIH-funded scientists. All sorts of variables were considered to make the groups as comparable as possible: For instance, HHMI has far fewer scientific areas for which it issues grants, so the control groups were restricted to those same scientific fields.

And the findings were definitive. By all measures — novelty of research area, publication rates, citation rates, number of prize-winning trainees, elections to the National Academy of Sciences or the Institute of Medicine, and so on — HHMI-funded scientists dramatically outpaced their NIH-funded peers in performing truly innovative research.

Seems awfully cut and dried, doesn't it? All Francis Collins has to do is mirror the HHMI grant-issuing model and he'll have succeeded in ramping up innovation practically overnight.

It's not so simple. Which is exactly what the study authors want to make sure people understand. The reality is that the scientific community needs both of these approaches — along with other models — to form a complete funding ecosystem. HHMI's approach "works because it's the elite of the elite," says Azoulay, an associate professor at MIT. "It wouldn't work for thousands and thousands of scientists across many different fields." Put another way, HHMI's success in spurring innovation is actually rooted in (and contingent upon) a firm foundation of NIH funding.

"We're very concerned that our paper is going to be misconstrued as a charge against NIH," Azoulay says. "That's not what it is." He points out that the goals of the two groups are very different: Where HHMI aims to reward a small group of successful scientists with longer-term investigative freedom, NIH has a mandate to underwrite the research capacity throughout the US. "That's a very different form of knowledge production," Azoulay says, noting that any system dealing with the breadth of science that NIH does would need to focus on deliverables and shorter-term strategies. "There's nothing wrong with incremental innovation."

That's not to say NIH can't improve its model. With scarce funds, everyone should be looking at ways to optimize the system. But let's not throw the baby out with the bathwater in the process.

Meredith Salisbury is editor in chief of GenomeWeb. Feel free to disagree with her at [email protected] The views expressed in this column are not necessarily those of Genome Technology.

The Scan

Lung Cancer Response to Checkpoint Inhibitors Reflected in Circulating Tumor DNA

In non-small cell lung cancer patients, researchers find in JCO Precision Oncology that survival benefits after immune checkpoint blockade coincide with a dip in ctDNA levels.

Study Reviews Family, Provider Responses to Rapid Whole-Genome Sequencing Follow-up

Investigators identified in the European Journal of Human Genetics variable follow-up practices after rapid whole-genome sequencing.

BMI-Related Variants Show Age-Related Stability in UK Biobank Participants

Researchers followed body mass index variant stability with genomic structural equation modeling and genome-wide association studies of 40- to 72-year olds in PLOS Genetics.

Genome Sequences Reveal Range Mutations in Induced Pluripotent Stem Cells

Researchers in Nature Genetics detect somatic mutation variation across iPSCs generated from blood or skin fibroblast cell sources, along with selection for BCOR gene mutations.