Low-Hanging Fruit in Automating Biology

I read this essay with interest as I work at the intersection of biology and engineering; I was disappointed. The essay fails to identify low-hanging fruit in automating biology and fails to explain how their company (Transistor Bio) is "picking" those low-hanging fruit. In retrospect it reads more like a poorly argued marketing pitch than an exposition on interesting and achievable problems in biology automation.

The company's website also leaves much to be desired; though they have reinvented the liquid handling robot [1].

[1] https://publish.obsidian.md/serve?url=transistor.bio/busines...

As with all such ventures, the chances of success are, I daresay, one in one hundred, or even lower. But since I would very much like to see at least 10 of those ventures succeed in my lifetime, because as the author said, "Assuming it is true that you want to live longer, healthier lives — a position not shared by the dull and dreary", I think we must do everything we can to have thousands of these startups all over the world. Even if all we can do is give them moral support.

We have thrown far more money to adware-crap-companies of what we have thrown to systems biology startups, even if only the later can have a meaningful impact on human health.

As someone who used to think a lot of the stuff in here, and definitely no longer does, I can say that this is not someone who is a practitioner.

Adam, if you’re reading this, I would definitely encourage you to take a step back and go deep on how you might prove that the problems are where you think they are. The stuff you’re describing has all been done many times at this point and just either hasn’t turned out to be valuable to solve, or now has big effective companies doing it, or is extremely difficult for non-obvious reasons. Your characterization of total doom in modern experimentation is inaccurate.

Sure, that’s fair.

An API driven vivarium as a service with instrumented cages was tried to tens of $M by Vium. That didn’t take off, though there are lots of vendors of sophisticated cage instrumentation now, including based on computer vision. DeepLabCut is amazing and open source.

In terms of general progress in experimental tools, there has been tons. The modern super resolution confocals; affordable femtosecond light sources like the Coherent Monaco enables all kinds of awesome stuff; or newer methods like MERFISH and PatchSeq (or hell, just the total commodification of sequencing generally).

Microfludics are now widely used and super valuable as “ASICs”, though I think the lack of a general purpose “CPU” lab of a chip has misled people not in the field.

In terms of molecular tools, it’s just night and day from 10 years ago. iPSCs, CRISPR, expansion microscopy, tons of new labels and stains etc.

Ginkgo and Zymergen have enormous scale, invest heavily in software and robotics, and are working “in vivo.” Recursion also invests heavily in automation, and while I don’t think they run animals in house, it’s not clear what Transistor is proposing that would outperform them.

Lots of companies run lots of studies in tons of different species all the time. Less so in academia, but I don’t think saying “well everyone else is working in vitro and we will work in vivo” is the kind of arbitrage opportunity Transistor seems to think it is. Where there are bottlenecks that I think could be improved, they are either unsexy (an easy Stripe-product-quality 3rd party IACUC would be super useful) or hinge on showing up with an enormous bucket of money so you can do things like set up your own breeding colonies.

And of course scientists really do care about being right and finding lasting results that are big effects. It is so much harder than it looks to do that well, but the people working in it are super smart and, at least outside of academia, generally have good incentives.

Edit: I clicked through to their “Business” page, which reads in part:

> Transistor will instead build a system designed with speed and scale in mind from the beginning: an automated wet lab with an API interface. Current CROs require bureaucratic back and forth which can extend into the months and are extraordinarily expensive for results that one crosses their fingers and hopes are correct.

May I point them to a company I founded 9 years ago, which raised a $56M series B last week: https://strateos.com/

Does this mean an opportunity exists? Maybe. But I think Transistor has some education to do on where the true problems that would be valuable to solve lie.

Putting a layer of robotics over an in vivo organism still has the extreme complexities of an in vivo system at the core. Im not exactly sure what the breakthrough is supposed to be here. I guess I was maybe hoping for a more technical explanation of the bio of what they're doing but maybe this seems more meant as a marketing pitch?