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How Life Sciences Actually Work (guzey.com)
88 points by DarkContinent 31 days ago | hide | past | web | favorite | 18 comments



Being a life-sciences refugee myself, I read this essay and noted that my intellectual response to it was very discordant with my emotional response to it.

Intellectually, I think the author did a very good job and although like any scientist I could nitpick, grossly speaking I found myself agreeing.

Emotionally, however… Having been through the wringer I would ask any reader to consider not just the “central tendencies” viewpoint but the “this is YOU going through this” viewpoint.

If you are doggedly determined and personally consumed with getting into a fantastic lab to bootstrap your career so that you can slave away for essentially minimum wage with no benefits so that you could get a research position for which you might get a job security at the age of 42 to 45… Seriously?!

For many, that prospect looks very different when you’re closer to twenty than fifty.

Here’s another view point: the system is horribly horribly broken, leaving a trail of collateral human damage… But there are so many people throwing themselves at the meat grinder that inevitably greatness occasionally arises.

Do I sound bitter and cynical? Perhaps. But living the experience, for me and many many others, is rather different than reading summaries of what the life is like.


Thank you for this. I completely agree with you. Unfortunately my essay had a different focus but maybe I should try to interview people just on their personal feelings and see how that -- less cerebral -- perspective would be different...


While I like your article a lot, as I said in another comment, I disagree about some conclusions.

In my opinion, big groups are the cancer of life sciences academia. It's not just me who thinks that. If you look into all the organizational research that HHMI did prior to setting up Janelia Labs, they essentially concluded that CSHL, LMB and Bell Labs were so successful in the past because groups were small and all funding was internal (which implies you no longer need PIs, you can go back to classical professors).

The vast majority of the big PIs I have worked or interacted with (and that includes Cambridge, Oxford, EMBL, Karolinska, MIT and other places) are pure rent seekers, literally. They bet on some postdocs or PhDs and simply stamp their name as last authors if there is a publication. However, they rarely have any insights on what is being done. Sometimes they don't even understand it at all. So no value added, just profit. Unless you count as value chairing conference calls, calling editors to negotiate publication terms or discussing funding with agencies (most grants are actually written by senior postdocs, despite what author lists indicate).

That's when things go well. When personal issues pop up, they can screw up their subordinates big time. I have witnessed this many times. After all, grads and postdocs are just pawns in their chessboard.

Such an organization is at odds with classical academia, where your professor (not PI) was your mentor and you would engage into endless discussions about science with him. Other fields retain some of this approach, but in life sciences it is lost.


For a somewhat sensationalistic take on this, see: How Academia Resembles a Drug Gang[1]

[1]: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2407748


One issue I ran into personally is incremental vs fundamental research. In the drive to get publications, which provides evidence of production so you can get grants, better jobs, more money, better publications in higher journals-- the quest for all that leads to very small steps in research. There are proportionally far fewer biologists than there used to be working on fundamental, big picture type work. One counterpoint may be that the low hanging fruit has been picked. However, I feel it's also a cultural problem. To do well, so many of us biologists get caught in the incrementalism loop rather than thinking bigger.


Author here - this essay is the result of a year (and 100+ interviews) of my figuring out how life sciences work. (there are also discussions of it on reddit [1] and on twitter [2])

[1] https://www.reddit.com/r/slatestarcodex/comments/cqxcey/how_... (16 comments)

[2] https://twitter.com/alexeyguzey/status/1162017187919478784 (28 responses)


Terrific stuff. I'd be interested in hearing your opinion about where additional funds would come from. And the areas most in need of allocation. Life sciences research can be a black hole. Infinite funds and data in, with very little usable output. At least that tends to be the perception ;)

An additional trend I've noticed is that many senior researchers tend to veer away from the pure research and discovery that marked early triumphs. And veer into issues of cruft, turf wars, plumbing, and "technical debt" later in their careers. A kind of "low hanging fruit" mentality sets in. In ML research for example, issues of reproducibility and generalizability need to be solved before trust can be placed in the system. And while I recognize the ethical need for theoretical foundations to be rock solid before deployment at scale. I am wondering if that's the class of problems the most brilliant minds should be working on.

It's only now that we are getting hard metrics about the return on research expenditures. And while its currently in vogue for administrators to use these stats competitively and make claims like "UCL published more Neuroscience papers than MIT last year". We should start to see more wise allocations of research dollars into the areas of development most needed.

Thanks!


As I wrote in https://guzey.com/patronage-and-research-labs/ - my hope is that philanthropists and foundations will be deciding to experiment more and to allow scientists to pursue research differently...

Wouldn't want to point to specific areas - rather I think that we need to find brilliant people and back whatever they're working on.


Congrats. It's the first essay I read that addresses most big issues, including the (broken) PI model and how most senior authors use peer review in a monopolistic way.

I've made a pretty big discovery, which is on its way to Nature and bioRxiv in a couple of weeks, so I think it's a very fertile field compared to pure CS (where I was before).

But working in Life Sciences is also a much worse experience due to the big amount of politics and naivety your article discusses so well.

So I have serious doubts as to whether I should continue my career in academia, despite great offers, pursue my ideas in a startup, or generate some patents and move back to CS.


That's a very nice essay, thank you for putting this all together!

Personally, I think that many of these points are also valid for computer science. However, for CS, I think short-terminism (which the essay mentions as less of a problem than initially thought, although it features heavily for example in point 9) would be well worth investigating as an important additional issue, because building software systems can take so long.

Many interesting and worthwhile long-term CS projects (such as complex compilers for new languages, new operating systems, intelligent teleteaching environments etc.) had to be terminated or significantly changed or restricted, or cannot even be started in an academic context due to this reason.


Thanks so much for doing this original research and writing it out so clearly. I'm not in the life sciences, but about 40% of my funding is NIH, and this does seem to mostly match my impression of the biases people have of biomedical funding as well as the reality of things. There did seem to be some cognitive dissonance about people saying that funding is harder for younger PIs, that students don't have creative flexibility, etc. versus what I was actually seeing, so I'm glad your study captured that. I appreciate the nuance in the claims.

PS: have you thought about writing these findings up to publish? I'm not exactly sure of the venue, but maybe even a slightly more general audience magazine?


I thought a bit about publishing it somewhere but I honestly have no idea where and how this actually happens...


One additional point is needed to complete the picture. Life sciences research is now almost completely dependent on technologies and reagents provided by a small number of commercial entities. Building custom equipment or synthesizing reagents has become almost impossible because institutions have gotten rid of their science support facilities and staff.


Aren't you kind of mixing engineering with science?

We still have plenty of opportunity for optimization of scientific discoveries in biology, what we don't have plenty of is new scientific discoveries.

I am just asking, maybe I am missing something but read like that to me.


There's plenty of space of new scientific discoveries in biology! Wikipedia for example has a good list: https://en.wikipedia.org/wiki/List_of_unsolved_problems_in_b...


Sure there is space but thats not the point though :)


I'd recommend the following book:

How Economics Shapes Science https://www.amazon.com/Economics-Shapes-Science-Paula-Stepha...

It looks into key challenges of the scientific labor market.


Great read. If you ever want to do this for industry life science research, I'd love to participate!




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