Note: Before the launch of the Open Philanthropy Project Blog, this post appeared on the GiveWell Blog. Uses of “we” and “our” in the below post may refer to the Open Philanthropy Project or to GiveWell as an organization. Additional comments may be available at the original post. We’ve been looking for gaps in the world of scientific research funding: areas that the existing system doesn’t put enough investment into, leaving potential opportunities to do unusually large amounts of good with philanthropic funding. We previously wrote about the alleged “valley of death” that makes it challenging to translate academic insights about biology into new medical technologies. This post is about a different issue, one that has come up in the vast majority of conversations I’ve had with scientists: it is believed to be extremely difficult to do what this post will call “breakthrough fundamental science” in the existing life sciences ecosystem. Breakthrough fundamental science is the term I’m using for what I believe many of the people I’ve spoken to have meant when they’ve used terms such as “basic research,” “high-risk/high-reward research” and “revolutionary/path-breaking research.” My subject matter knowledge is extremely limited, so I can’t be confident that I’ve correctly classified the comments I’ve heard as having a consistent theme or that I’m correctly defining the theme, but I’m attempting to do so anyway because the theme has seemed consistent and important. In brief, “breakthrough fundamental science” (in the context of life sciences) refers to research that achieves important, broadly applicable insights about biological processes, such that the insights bring on many new promising directions for research, yet it is difficult to anticipate all the specific ways in which they will be applied and thus difficult to be assured of “results” in the sense of new clinical applications. This type of work stands in contrast to research that is primarily aimed at producing a particular new drug, diagnostic or other medical technology. This definition doesn’t lend itself to fully objective classifications, but a couple of illustrative examples would be: (a) understanding the genetic code and the structure of DNA; (b) (more recently) work on the CRISPR/CAS system and developing it to the point where it can be used to “edit” an organism’s DNA. Each of these has opened up many possible directions for research, while not having immediately clear relevance for a particular disease, condition or clinical application. This post will:
- Give examples of the wide variety of people who have noted the difficulty of securing support for attempts at breakthrough fundamental science in the current system.
- Discuss what the roots of this “gap” might be.
The NIH faces a large number of applicants for a relatively small number of grants. Its current methods for selecting recipients have difficulty ensuring fairness and reliable support for good scientists. In addition, these methods are likely biased toward incremental and established research over higher-risk, higher-reward research. It is particularly difficult for young researchers to secure adequate funding.
Neal Lane, currently Provost at Rice University, who has headed both the National Science Foundation and the White House’s Office of Science and Technology Policy:
The National Science Foundation (NSF), the National Institutes of Health (NIH), as well as the Department of Energy’s Office of Science, NASA and other agencies support basic research. But, increasingly, these agencies have been challenged to ensure that the research they support has potential practical benefits for the country. As a result, support for bold, sometimes called “high risk,” research has suffered. There has been a growing pressure to identify outcomes, and that discourages potentially path-breaking investigations.
Bruce Alberts, currently of UCSF, formerly Editor-in-Chief of Science and President of the National Academy of Sciences:
The current funding system for scientific research is biased toward supporting short-term, translational research (research that looks for practical applications of basic science) … I am painfully aware of the huge gaps in our understanding of fundamental life processes. Many great opportunities to advance this understanding through basic research in biology are not receiving funding from the National Institutes of Health (NIH), the largest funder of biomedical research. Changing incentives to more effectively recognize the critical importance of such understanding would have a strong effect on researchers’ choices and help produce more outstanding basic research.
One of the major issues in biomedical research is that biology is not understood well enough to get to the root of problems … There’s a lot of pressure to push science in applied or clinical directions before it’s ready, which can result in money being poorly spent.
A paper in PNAS co-authored by Bruce Alberts (listed above), Harold Varmus (former Director of the National Cancer Institute and former Director of the National Institutes of Health) and others:
The system now favors those who can guarantee results rather than those with potentially path-breaking ideas that, by definition, cannot promise success. Young investigators are discouraged from departing too far from their postdoctoral work, when they should instead be posing new questions and inventing new approaches. Seasoned investigators are inclined to stick to their tried-and-true formulas for success rather than explore new fields … Many surprising discoveries, powerful research tools, and important medical benefits have arisen from efforts to decipher complex biological phenomena in model organisms. In a climate that discourages such work by emphasizing short-term goals, scientific progress will inevitably be slowed, and revolutionary findings will be deferred (3).
A few notes based on my recollections, though largely not captured in public records:
- My recollection is that many were particularly energized about the difficulty of funding research aiming to improve tools and techniques, which I discussed in a previous post (see classification (A) in that post).
- Nobody claimed that there is a small amount of research projects attempting breakthrough fundamental science, only that there ought to be far more due to the high importance.
- In addition, it’s worth noting that breakthrough fundamental science is often greatly rewarded in the long run; for example, many relevant Nobel Prizes seem to be for work that broadly fits in this category. (That is to say, many of the Prizes seem to have gone to work with broad applications for understanding biological processes in general, but no obvious application to a particular disease, condition or applied medical technology.) But having a chance at a Nobel Prize decades down the line isn’t necessarily helpful for a scientist seeking to do breakthrough fundamental research; the work needs to be funded today in order to be practicable.
- The concept of “risk” is somewhat ambiguous in some of the quotes above. It could refer to the risk that a project will fail on its own terms (e.g. failing to answer its own question or effectively test its own hypothesis). It could also refer to the uncertainty involved in the applications of particular research. My sense is that most attempts at breakthrough fundamental science are risky in both senses, but particularly the second. Regarding the first - it seems likely that attempts to make major breakthroughs will rarely be able to stick with familiar approaches and be assured of useful results. Regarding the second - when one’s goal is to achieve major insights useful for understanding biological processes in general, it may often be difficult to say in advance just what sorts of clinical applications these insights will have. This could be a problem for funders focused on the most direct, high-confidence paths to new drugs, diagnostics and other medical technologies.
There is now a severe imbalance between the dollars available for research and the still-growing scientific community in the United States. This imbalance has created a hypercompetitive atmosphere in which scientific productivity is reduced and promising careers are threatened … Now that the percentage of NIH grant applications that can be funded has fallen from around 30% into the low teens, biomedical scientists are spending far too much of their time writing and revising grant applications and far too little thinking about science and conducting experiments. The low success rates have induced conservative, short-term thinking in applicants, reviewers, and funders.
As this chart from the NIH shows, success rates for research project grants have fallen from ~30% to just under 20% since 1998, and the change has been driven by a growing number of applicants for a fairly constant number of annual awards. One might imagine that more applicants and more competitiveness would be a good thing, if the process consistently funded the most promising projects. However, my impression is that the NIH grant review process isn’t necessarily optimized for identifying the most promising projects and applicants, as opposed to simply eliminating the least promising ones. Thus, it may be poorly suited to such a high level of competitiveness. For example, grant applications are given scores on a 1-9 scale by all reviewers, and then ultimately funded (or not) based on the average; this arguably privileges incremental science (likely to appear clearly worthwhile to large numbers of people) over higher-risk science (which might appear extremely promising to some and not at all promising to others). The PNAS paper lists multiple problems brought about by high competitiveness, in addition to the risk aversion discussed above:
- It argues that competing for publication in top journals has caused scientists to “rush into print, cut corners, exaggerate their findings, and overstate the significance of their work”, contributing to issues with reproducibility that we’ve written about before.
- It points to the increasing domination of the field by later-career scientists, and states that early-career scientists now face poor prospects and long time frames for getting substantial support for their research. I believe this sort of dynamic risks driving out the most promising scientists (who may have other career options) while retaining less promising ones; it also risks mis-allocating support, by funding scientists whose most productive years are behind rather than ahead of them.
- It discusses the “crippling demands on a scientist’s time” brought on by the increasing difficulty of grant applications (it also cites an increasing regulatory burden as being relevant here). It argues that in addition to reducing time for scientific reflection, the increasing administrative burdens on senior scientists reduce the time they have available for peer review, which worsens the quality of the peer review process.
- It explicitly argues that there is excessive interest in translational science, and that this is another “manifestation of [a] shift to short-term thinking,” which in turn may be another outgrowth of increased competitiveness.
In my view, all of the above represent different aspects of distortion caused by the disconnect between what science is most valuable and what science is most straightforward to evaluate. Breakthrough fundamental science is characterized by being highly innovative (making it difficult to form a consistent framework for judging it), and by having far-in-the-future and difficult-to-predict ultimate impacts. It may be possible for top scientists to evaluate it using their judgment and intuitions, but any system that seeks consistent, well-defined, practically important outcome metrics will likely struggle to do so. Instead, such a system risks rewarding those who can game it, as well as those who can show more quick and consistent (even if ultimately less important) results. It’s worth noting that the criticism of “rewarding the measurable, rather than the important” has often been leveled at GiveWell’s work on top charities. I have long felt that focusing on the measurable is quite appropriate when (a) serving individual donors seeking somewhere they can give without having to invest a lot of time in learning; (b) working on issues related to global health and development, where higher-risk/higher-reward approaches have a history of coming up empty. However, the world of scientific research is very different. In this environment, it seems to me that insisting on accountability to meaningful short-term metrics could easily do more harm than good.