Readers will enjoy a thoughtful blog post from professor Ken Weiss in response to - “Lets Discuss Is it Time to Shut Down NHGRI?”. With his permission, we are reblogging it entirely below, but please feel free to comment in his blog.
As an aside, while discussing this topic privately with other scientists, I noticed an attitude that there is no harm in NHGRI wasting money as long as it also funds good projects (i.e. their projects). In their (implied) view, the money comes from taxpayers, who are born suckers anyway. I do not agree with this notion, and can argue that NHGRI’s funding of poor quality science actually damages good science. I will share one such example in the following blog post.
Reblogged from The Mermaid’s Tale blog.
The NIH-based Human Genome Research Institute (NHGRI) has for a long time been funding the Big Data kinds of science that is growing like mushrooms on the funding landscape. Even if overall funding is constrained, and even if this also applies to the NHGRI (I don’t happen to know), the sequestration of funds in too-big-to-stop projects is clear. Even Francis Collins and some NIH efforts to reinvigorate individual-investigator RO1 awards don’t really seem to have stopped the grab for Big Data funds.
That’s quite natural. If your career, status, or lab depends on how much money you bring into your institution, or how many papers you publish, or how many post-docs you have in your stable, or your salary and space depend on that, you will have to respond in ways that generate those score-counting coups. You’ll naturally exaggerate the importance of your findings, run quickly to the public news media, and do whatever other manipulations you can to further your career. If you have a big lab and the prestige and local or even broader influence that goes with that, you won’t give that up easily so that others, your juniors or even competitors can have smaller projects instead. In our culture, who could blame you?
But some bloggers, Tweeters, and Commenters have been asking if there is a solution to this kind of fund sequestration, largely reserved (even if informally) for the big usually private universities. The arguments have ranged from asking if the NHGRI should be shut down (e.g., here) to just groping for suggestions. Since many of these questions have been addressed to me, I thought I would chime in briefly.
First, a bit of history or perspective, as informally seen over the years from my own perspective (that is, not documented or intended to be precise, but a broad view as I saw things):
The NHGRI was located administratively where it was for reasons I dont know. Several federal institutes were supporting scientific research. NIH was about health, and health ‘sells’, and understandably a lot of fund is committed to health research. It was natural to think that genome sequences and sciences would have major health implications, if the theory that genes are the fundamental causal elements of life was in fact true. Initially James Watson, discoverer of DNA’s structure, and perhaps others advocated the effort. He was succeeded by Francis Collins who is a physician and clever politician.
However, there was competition for the genome territory, at least with the Atomic Energy Commission. I dont know if NSF was ever in the race to fund genomic research, but one driving force at the time was the fear of mutations that atomic radiation (therapeutic, from wars, diagnostic tests, and weapons fallout) generated. There was also a race with the private sector, notably Celera as a commercial competitor that would privatize the genome sequence. Dr Collins prominently, successfully, and fortunately defended the idea of open and free public access. The effort was seen as important for many reasons, including commercial ones, and there were international claimants in Japan, the UK, and perhaps elsewhere, that wanted to be in on the act. So the politics were rife as well as the science, understandably.
It is possible that only with the health-related promises was enough funding going to be available, although nuclear fears about mutations and the Cold War probably contributed, along with the usual less savory for self-interest, to AEC’s interests.
Once a basic human genome sequence was available, there was no slowing the train. Technology, including public and private innovation promised much quicker sequencing in the future, that was quickly to become available even to ordinary labs (like mine, at the time!). And once the Genome Institute (and other places such as the Sanger Centre in Britain and centers in Japan, China, and elsewhere) were established, they weren’t going to close down! So other sequences entered the picture–microbes, other species, and so on.
It became a fad and an internecine competition within NIH. I know from personal experiences at the time that program managers felt the need to do ‘genomics’ so they would be in on the act and keep their budgets. They had to contribute funds, in some way I don’t recall, to the NHGRI’s projects or in other ways keep their portfolios by having genomics as part of this. -Omics sprung up like weeds, and new fields such as nutrigenomics, cancer genomics, microbiomics and many more began to pull in funding, and institutes (and the investigators across the country) hopped aboard. Imitation, especially when funds and current fashion are involved, is not at all a surprise, and efficiency or relative payoff in results took the inevitable back seat: promises rather than deliveries naturally triumphed.
In many ways this has led to the current of exhaustively enumerative Big Data: a return to 17th century induction. This has to do not just with competition for resources, but a changed belief system also spurred by computing power: Just sample everything and pattern will emerge!
Over the decades the biomedical (and to some lesser extent biological) university establishment grew on the back of the external funding which was so generous for so long. But it has led to a dependency. Along with exponential growth in the number of competitors, hierarchies of elite research groups developed–another natural human tendency. We all know the career limitations that are resulting from this. And competition has meant that deans and chairs expect investigators always to be funded, in part because there aren’t internal funds to keep labs running in the absence of grants. It’s been a vicious self-reinforcing circle over the past 50 years.
As hierarchies built, private donors were convinced (conned?) into believing that their largesse would lead to the elimination of target diseases (‘target’ often meaning those in the rich donors’ families). Big Data today is the grandchild of the major projects, like the Manhattan Project in WWII, that showed that some kinds of science could be done on a large scale. Many, many projects during past decades showed something else: Fund a big project, and you can’t pull the plug on it! It becomes too entrenched politically.
The precedents were not lost on investigators! Plead for bigger, longer studies, with very large investments, and you have a safe bet for decades, perhaps your whole career. Once started, cost-benefit analysis has a hard time paring back, much less stopping such projects. There are many examples, and I won’t single any of them out. But after some early splash, by and large they have got to diminishing returns but not got to any real sense of termination: too big to kill.
This is to some extent the same story with the NHGRI. The NIH has got too enamored of Big Data to keep the NHGRI as limited or focused as perhaps it should have been (or should be). In a sense it became an openly anti-focused- research sugar daddy (Dr Collins said, perhaps officially, that NHGRI didnt fund hypothesis-based research) based on pure inductionism and reductionism, so it did not have to have well-posed questions. It basically bragged about not being focused.
This could be a change in the nature of science, driven by technology, that is obsolescing the nature of science that was set in motion in the Enlightenment era, by the likes of Galileo, Newton, Bacon, Descartes and others. We’ll see. But the socioeconomic, political sides of things are part of the process, and that may not be a good thing.
Will focused, hypothesis-based research make a comeback? Not if Big Data yields great results, but decades of it, no matter how fancy, have not shown the major payoff that has been promised. Indeed, historians of science often write that the rationale, that if you collect enough data its patterns (that is, a theory) will emerge, has rarely been realized. Selective retrospective examples don’t carry the weight often given them.
There is also our cultural love affair with science. We know very clearly that many things we might do at very low cost would yield health benefits far exceeding even the rosy promises of the genomic lobby. Most are lifestyle changes. For example, even geneticists would (privately, at least) acknowledge that if every ‘diabetes’ gene variant were fixed, only a small fraction of diabetes cases would be eliminated. The recent claim that much of cancer is due just to bad mutational luck has raised lots of objections–in large part because Big Data researchers’ business would be curtailed. Everyone knows these things.
What would it take to kill the Big Data era, given the huge array of commercial, technological, and professional commitments we have built, if it doesn’t actually pay off on its promises? Is focused science a nostalgic illusion? No matter what, we have a major vested interest on a huge scale in the NHGRI and other similar institutes elsewhere, and grantees in medical schools are a privileged, very well-heeled lot, regardless of whether their research is yielding what it promises.
Or, put another way, where are the areas in which Big Data of the genomic sort might actually pay, and where is this just funding-related institutional and cultural momentum? How would we decide?
So what do to? It won’t happen, but in my view the NHGRI does not, and never did, belong properly in NIH. It should have been in NSF, where basic science is done. Only when clearly relevant to disease should genomics be funded for that purpose (and by NIH, not NSF). It should be focused on soluble problems in that context.
NIH funds the greedy maw of medical schools. The faculty don’t work for the university, but for NIH. Their idea of ‘teaching’ often means giving 5-10 lectures a year that mainly consist of self-promoting reports about their labs, perhaps the talks they’ve just given at some meeting somewhere. Salaries are much higher than at non-medical universities–but in my view grants simply should not pay faculty salaries. Universities should. If research is part of your job’s requirements, its their job to pay you. Grants should cover research staff, supplies and so on.
Much of this could happen (in principle) if the NHGRI were transferred to NSF and had to fund on an NSF-level budget policy. Smaller amounts, to more people, on focussed basic research. The same total budget would go a lot farther, and if it were restricted to non-medical school investigators there would be the additional payoff that most of them actually teach, so that they disseminate the knowledge to large numbers of students who can then go out into the private sector and apply what they’ve learned. That’s an old- fashioned, perhaps nostalgic(?) view of what being a ‘professor’ should mean.
Major pare-backs of grant size and duration could be quite salubrious for science, making it more focused and in that sense accountable. The employment problem for scientists could also be ameliorated. Of course, in a transition phase, universities would have to learn how to actually pay their employees.
Of course, it won’t happen, even if it would work, because it’s so against the current power structure of science. And although Dr Collins has threatened to fund more small RO1 grants it isn’t clear how or whether that will really happen. That’s because there doesn’t seem to be any real will to change among enough people with the leverage to make it happen, and the newcomers who would benefit are, like all such grass-roots elements, not unified enough.
These are just some thoughts, or assertions, or day-dreams about the evolution of science in the developed world over the last 50 years or so. Clearly there is widespread discontent, clearly there is large funding going on with proportionately little results. Major results in biomedical areas can’t be expected over night. But we might expect that research had more accountability.