Tag Archives: biomedical research

Biomedical research as a career

April 1, 2014 Jonah Sinick 1 Comment

I did some preliminary research on biomedical research as a career. The case for becoming a biomedical researcher looks to be weak for most candidates for the career. Are there important points in favor of pursuing a career in biomedical research that I’m missing?

Summary

Some people find biomedical research very rewarding, but the job involves a lot of grant writing, not only research.
Job security for biomedical researchers in academia is extremely poor before tenure. We still have to research exit options for those who leave academia.
Biomedical researchers make substantially less money over a life time than they could in other fields.
The job involves ~60 hours of work per week
While biomedical research has historically produced a great deal of value, the situation today is more ambiguous, and it appears that the average biomedical researcher does little to advance the field.

The nature of the work

According to How to succeed in science: a concise guide for young biomedical scientists. Part I: taking the plunge by Yewdell (2009)

for individuals with a hunger for knowledge and an insatiable curiosity about how things work, science offers a constant challenge and, best of all, the intense thrill of discovery. What can match being the first person who has ever lived to know something new about nature? And not just the big, infrequent, paradigm-making (or breaking) discoveries, but the small, incremental discoveries that occur on a daily or weekly basis too. If this doesn’t give you goosebumps and if you are not in a rush to get to the laboratory in the morning to find the results of yesterday’s experiment, then you should seriously consider a non-laboratory career.

However, research is not the only part of the job: Yewdell writes

For your entire career as a PI, you will put inordinate efforts into writing grants

This is in consonance with GiveWell’s post Exploring Life Science Funding which says

The existing system focuses on time-consuming, paperwork-heavy grant applications for individual investigators.

GiveWell’s post also hints at researchers being constrained with respect to the research that they’re able to get funding for:

The existing system favors a particular brand of research – generally incremental testing of particular hypotheses – and is less suited to supporting research that doesn’t fit into this mold. Research that doesn’t fit into this mold may include: (i) Very high-risk research representing a small chance of a big breakthrough. (ii) Research that focuses on developing improved tools and techniques (for example, better microscopy or better genome sequencing), rather than on directly investigating particular hypotheses. (iii) “Translational research” aiming to improve the transition between basic scientific discoveries and clinical applications, and not focused on traditionally “academic” topics (for example, research focusing on predicting drug toxicity).

Job security

Our writeup on job security in academia gives some general considerations.

Concerning biomedical research specifically, The Scientific Workforce Policy Debate: Do We Produce too Many Biomedical Trainees? reports that

During the period from 1993-2003, the probability that a postdoc in the U.S. was in a tenure-track PI position 5-6 years after obtaining their PhD ranged from 15-23% (Garrison and McGuire, 2007).

This graphic says that after finishing graduate school / postdoc, of biomedical research PhDs, 18% go into non-research science jobs, 6% go into government research, 43% go into academia or teaching, 18% go into industrial research, 13% do work outside of science and 2% are unemployed. Roughly 50% of those who complete a postdoc and go into academia get tenure, and the career outcomes for those who don’t get tenure are unreported.

Some of the jobs that biomedical researchers get outside of academia are jobs that they could have gotten without doing a PhD or postdoc.

An important question is that of how correlated research ability is with job security. If luck plays a sufficiently large role then high ability doesn’t guarantee a job, whereas if skill can overcome luck, then those who are skilled can be confident that they’ll be able to get jobs. An interview with Prof. Andrew McMichael at the 80K blog seems to suggest that sufficiently high quality researchers can get jobs and funding. However, going into graduate school, one’s ability level may not be clear.

It’s unclear how job security is changing over time. In 2010, the Bureau of Labor Statistics reported that the number of jobs was expected to grow 36% over 10 years (much faster than average). But in 2012, the Bureau of Labor Statistics reportedthat the number of jobs is expected to grow 13% over 10 years, and in the intervening time the number of jobs had grown only 3%. So there appears to have been a substantial change in outlook in only two years. The job growth rate forecasts have to be viewed in juxtaposition with the expected change in number of new PhDs. According to one source, the National Institutes of Health found that the number of new PhDs increased by 50% between 2002 and 2009. If this rate were to be sustained, the ratio of jobs to job candidates would decrease even more.

I plan on researching exit options

Work-life balance

According to Yewdell (2009)

As a graduate student, you should be spending a minimum of 40 hours per week actually designing, performing or interpreting experiments. As there are many other necessary things to do during the day (for example, reading the literature, attending seminars and journal club, talking to colleagues both formally and informally, and common laboratory jobs), this means you will be spending 60 or more hours per week in science-associated activities.

This is corroborated by career coach Marty Nemko, who wrote

You spend most of your 60-to-70-hour workweek alone in a lab or at your desk, with little people contact.

Biomedical researchers who stay in academia are often constrained with respect to the geographic location where they can get jobs. See our writeup on job location options for academics.

Earnings

Getting a PhD in a biomedical research field takes 6 to 7 years, during which one makes substantially less money than one could otherwise make. It’s been reported that the average biology PhD had $45k in debt as of 2004.

Salaries rise afterward, but not rapidly: as of 2009, the starting salary for a postdoc was ~$37k/year (pg. 141), and postdoctoral appointments last 4 years.

According to the Bureau of Labor Statistics

Colleges, Universities, and Professional Schools are next in employment, and pay a mean wage of $61,320 per year. Completing the five areas with the most employment are Pharmaceutical and Medicine Manufacturing ($92,130), General Medical and Surgical Hospitals ($80,090) and Drugs and Druggists’ Sundries Merchant Wholesalers ($93,090).

The “Colleges, Universities, and Professional Schools” category includes postdocs: if one considers professors only, the figure will be more like $80k/year.

According to Yewdell (2009)

If you do achieve the ‘Holy Grail’ of full professorship then you will not be poor, but you will be far worse off financially than nearly all of your peers who have similar levels of talent, energy and dedication, but who chose other careers.

Career coach Marty Nemko wrote

“According to MIT faculty member Philip Greenspun, Adjusted for IQ, quantitative skills, and working hours, jobs in science are the lowest paid in the United States….”

A small number of biomedical researchers command high salaries: for example, one source reports that there are 20 in the country with earnings at the $240k+ level.

Some sources report that biomedical researchers can become very wealthy if as early employees of successful biotech startups, but this is very rare.

Social Value

Historically, a large fraction of increase in lifespan and quality of life has been due to biomedical research (e.g. vaccines). Yewdell (2009) wrote

Society desperately needs your talents […] For rationally thinking people with an altruistic bent, life can be no more rewarding than when practising the scientific method for the benefit of all of the denizens of this fragile planet.

Some points to keep in mind in assessing the social value of biomedical research are

Diminishing returns — Much of the increase in lifespan between 1950 and now was due to cardiovascular disease research, with the gains mostly halting by 1990. There have been significant advances in recent years, such as AIDS treatment drugs, statins, psychiatric drugs. But one should expect the increase in quality of life and lifespan per researcher to go down over time, because of low hanging fruit being plucked, barring radical advances coming from anti-aging research and unexpected sources.
Low replication rates — The fact that large fraction of studies don’t replicate suggesting that much research doesn’t move science forward.
Power law distribution of research contributions A small fraction of researchers produce 100x+ as much value as the average researcher. To the extent that success is driven by skill rather than luck, prospects for impact depend heavily on your ability.

80,000 Hours plans to publish an overview of biomedical research that will address the social value of going into biomedical research in more detail.

Biomedical research, superstars, and innovation

March 14, 2014 Vipul Naik Leave a comment

By Vipul Naik

Cross-posted from Less Wrong. Related information wiki content: biomedical research as a career option, social value of biomedical research.

As part of my work for Cognito Mentoring reviewing biomedical research as a career option (not much at the link there right now), I came across an interview with biomedical researcher John Todd of Cambridge University published by 80,000 Hours.

The whole interview is interesting, but one part of it struck me as interesting and somewhat hard to believe:

John would prefer a good person in his lab to an extra £0.5mn in annual funding. Generally, there are enough grants, so finding good people is a bigger constraint than money.

Here’s the full context:

Our candidate does data analysis in finance, earning over $100,000 per year. They have an Economics degree for Chicago, and an Masters in Financial Engineering from University of California, LA, and reasonable programming skills. They’re planning to do an MD then PhD.

“This guy looks great. I’d love to hire him.” (when he has his MD, or even before).

“The MD and programming/statistics combo is lethal. Top of the world. There’s major demand.”

He probably wouldn’t need to do a PhD, because of the programming. After his MD, he could just apply to a lab. He should go into genomic medicine, which is what I do. Tailored therapeutics or stratified medicine will be played out for major health and economic benefits over the next 30 years. Check out Atul Butte at Stanford. He’s the perfect profile for this guy. He could be the new Butte”

£0.5mn is about USD 830,000 according to current foreign exchange rates. In other words, John Todd, the interviewee, indicated that a sufficiently good researcher was worth that much. Now, the question was framed in terms of additionalfunding, rather than reallocation of existing funds. But assuming that the existing funding for the biomedical research lab is at least one order of magnitude greater than the amount (£0.5mn) under discussion, I don’t think it matters whether we’re talking of using additional funding or reallocating existing funds. Essentially, I read John Todd as saying that he’d be willing to pay £0.5mn to attract a “good person” to his lab (actually, as framed, it could be interpreted as even more: he’s willing to pay an ordinary salary for the person, plus forgo £0.5mn in additional funds, to hire the person). Note: I clarified with Ben Todd, the interviewer, that the additional grants were per-year rather than one-time grants, so the relevant comparison is indeed between the grant amount and annual income.

I haven’t surveyed the biomedical research community, so I’m not sure how representative John Todd’s opinion here is. Andrew McMichael offers a more guarded response, suggesting that 200,000 pounds are not as good as a great researcher, but he’s less sure at half a million pounds, and in any case, good researchers bring in their own grant money, so it’s a false dichotomy. But I’ve heard that there are other people at biomedical research labs who place even higher value on hiring good people than John Todd does. So in the absence of more detailed information, I’ll take John Todd’s view as a representative median view of a segment of biomedical research labs.

So, question: why don’t there exist high-paid positions of that sort in biomedical research for entry-level people? For comparison, one list of the top ten professors in the US lists the tenth highest paid professor as earning slightly under US$500,000. The list is probably far from complete (Douglas Knight points in the comments to Chicago having at least 5 salaries over $700K, one in the business school and four in the medical school). Glassdoor list salaries at the J. Craig Venter Institute, and the highest listed salary is for professors (about $200,000), with all other salaries near or below $100,000.

I asked a slightly more general version of the question in this blog post. I’ll briefly list below the general explanations provided there, with some comments on the applicability of those to the context of biomedical research as I understand it.

Talent constraint because of cash constraint: I don’t think this applies to biomedical research. It’s not that I think they are adequately funded, but rather, they do have enough funds that there shouldn’t be a great different between how they would use additional funds and how they would reallocate existing funds.
Genuine absence of talented people: I think that this does apply in the very short run — it’s hard for somebody to acquire a M.D. and experience with programming at short notice. But this raises a whole host of questions: why not advertise for such positions prominently, promising high pay, so that people can use the existence of such positions to make more long-term plans of what subjects to study while they’re still in college?
Talented people would or should be willing to work for low pay: While this argument works well in the context of effective altruism (because of the altruistic orientation needed for top work), I’m not sure it works for biomedical research. I don’t see biomedical research as qualitatively different from computer programming or finance in terms of how altruistic people need to be to work productively.
Workplace egalitarianism and morale: There may be friction in labs if some people get paid a lot more, particularly if other workers aren’t convinced that the people getting paid more are really working harder. This is a problem everywhere, including in the programming world. One solution that the programming world has come up with is to offer different levels of stock compensation. Another solution is acquihires: rather than paying huge salaries to star programmers, companies buy startups that have collected a large number of star programmers under their roof, and the programmers cash in on the huge amount of money reaped through the sale. Neither of these specific solutions works in the context of nonprofit, university, or government research.
Irrationality of funders: Employers and their funders are reluctant to pay large amounts. Biomedical research labs are often affiliated with universities and need to use the payscales of the universities. Even those that rely on other donations may be afraid that their donors will balk if they pay huge salaries.

Of course, one possibility is that none of these explanations really matter and I’m overinterpreting offhand remarks that were not intended to be taken literally. But before jumping to that conclusion, I’d like to get a clearer sense of the dynamics at play.

The nature of the explanation could also affect the social value of going into biomedical research in the following sense: if (3), (4), or (5) are big issues, that could be an indicator that perhaps superstars aren’t valued much by their peers and funders (relative to the need to make people conform to norms of taking low pay). This suggests (though it doesn’t prove) that perhaps the workplace doesn’t offer enough flexibility for the sort of ambitious changes that superstars may bring about, so the marginal value of superstars in practice isn’t as high as it could be in principle. In other words, if your bosses don’t value your work enough in practice to pay you what they say you’re worth, maybe they won’t give you the autonomy to actually achieve that. On a related note, this GiveWell blog post hints that many experts think that bureaucracy, paperwork, and a bias in favor of older, established scientists, all get in the way of accomplishment for young, talented researchers:

The existing system favors researchers with strong track records, and is not good at supporting young investigators. This was the most commonly raised concern, and is mentioned in all three of our public interviews.

The existing system favors a particular brand of research – generally incremental testing of particular hypotheses – and is less suited to supporting research that doesn’t fit into this mold.Research that doesn’t fit into this mold may include:

Very high-risk research representing a small chance of a big breakthrough.

Research that focuses on developing improved tools and techniques (for example, better microscopy or better genome sequencing), rather than on directly investigating particular hypotheses.

“Translational research” aiming to improve the transition between basic scientific discoveries and clinical applications, and not focused on traditionally “academic” topics (for example, research focusing on predicting drug toxicity).

The existing system focuses on time-consuming, paperwork-heavy grant applications for individual investigators; more attention to differently structured grants and grant applications would be welcome. These could include mechanisms focused on providing small amounts of funding, along with feedback on ideas, quickly and with minimal paperwork, as well as mechanisms focused on supporting larger-scale projects that require collaboration between multiple investigators.