Applying tech frameworks to biotech: key differences | Hacker News Reader

Applying tech frameworks to biotech: key differences

celinehh.com

48 pointsapsec11220 comments

Overall, this is a fantastic article that touches on a lot of the issues in the biotech.

Laypeople hear the term "biotech" and think of bionics, but most firms operate doing wet-lab work or synthesizing reagents/kits. The academic influence slows everything down and there is active discouragement of "outside the box" thinking. Consumer products are an afterthought for most firms.

I think the industry is capable of great things... eventually. But that success will come from a) an area with a much looser regulatory environment than the US, b) a team with a multidisciplinary background (most academics are too narrowly specialized to reliably see the "big picture" that is required to make commercially viable products) and c) a team with funding that far exceeds the current dollar figures we see for some start-ups.

Mass spec and NGS are technologies that have become drastically cheaper in recent years and could be consumer ready soon. It's just a matter of being the first person with the funding and desire to bring them to the mass market.

I don't know what laypeople you're talking to, but when I hear "biotech" I think of drugs and things like CRISPR. Things where it's not the academic influence that slows things down, but the regulatory environment and the general need to have all your ducks in a row w.r.t. safety and efficacy. "Move fast and break things" doesn't cut it for things people put into their bodies.

>Overall, this is a fantastic article that touches on a lot of the issues in the biotech.

It does miss a couple, especially on the FDA regulation side. In addition to safety and efficacy, the FDA also highly regulates how you can market and promote your product. There are literally teams of people who do nothing but ensure that marketing, training, sales, and promotion all comply with FDA requirements.

It remains unclear what, exactly, NGS would do to justify its cost (even if it drove to nearly free). It's been sold as a health panacaea for decades and has proven to not be that, repeatedly. Some gene tests are useful but it's clear that most disease phenotypes require much deepeer analysis than we are currently able to apply.

In general I agree, genetic and even epigenetic testing tends to identify problems at a point where gene therapy is no longer an option, so why bother? But if you can take tissue samples, we're getting to the point were we can detect cancers from SVs and fusions fairly easily. It'd be a easy sale to sell blood tests for leukemia, for example. That alone won't justify the cost, but we're making progress.

None of those require NGS, though- they can all be implemented using far cheaper methods.

> This is in part due to the conservatism of the industry and in part because extensive scientific training is generally necessary to have enough biological insight to correctly identify an opportunity.

I don't think younger practitioners have a problem identifying opportunities in biotech. They have a problem identifying difficulties in biotech. It's pervasive that young founders think everything is easy, or have an understanding that misses "one key detail".

Indeed. Theranos happened not because Elizabeth Holmes wasn't smart, or because she initially set out to deceive people -- she just thought she had a world-changing idea and all that was missing was the implementation, and her strategy for getting from here to there was "fake it till you make it".

Which kinda works much of the time in software -- trowel on enough JavaScript frameworks, polyfills, and glue code and eventually you will have something that resembles your vision (though it runs like a pig). But Theranos ran headlong into physical problems that the biotech industry hadn't found clean answers for yet (and may never find) -- and its leader had vision and ambition, but not the knowledge or experience to see the pitfalls.

This reminds me of the recent Phase 2 failure of UBX's UBX0101 senolytic drug. The highly experienced team's entire strategy was built around eliminating as much risk as possible prior to Phase 2 and yet they still failed miserably. Biotech just seems brutal, from the outside at least.

For a very interesting but pre-failure interview of UBX: https://peterattiamd.com/neddavid/

Has anything changed recently, or is biotech still far less well compensated than software, relative to years of experience and education?

At least in the bay area the gap is enormous - and biotech is not known for paying poorly!

I'm not sure what you mean by this. Are you saying biotech is better paid in the bay area?

No he is saying the other one is overpaid

tier-1 biotech in the bay area (genentech, gilead, etc) pays less than tier-1 tech (google, facebook, etc), but that's mainly because FAAMG pay such absurdly high base salaries.

The difference is less profound for tech folks at biotech companies than it is for biotech people. Certainly when I worked at a biotech startup for a year, after leaving FAAMG, I was able to negotiate the same base salary, but base salary is only a part of total comp...

Hey! I’m the author. Biotech is not as well comp’ed, especially when you compare years of experience. For context, senior (Director, VP) levels make low to mid 200s, PhDs with work experience make mid 100s, and straight out of grad school make 80-120s

This doesn’t take into account equity, which most bio hires have zero context for and are easily taken advantage of when negotiating. I give equity packages in line with tech standards, but I could have cut them by 3-5X and still been competitive with the standard bio co.

unrelated, but I browsed your company website and think the idea is brilliant (especially after reading this: https://onlinelibrary.wiley.com/doi/full/10.1111/acel.12737, which confirmed my initial speculation).

I think we still lack fundamental tools that can allow anyone to say with reasonable certainty that drug X will work. All you can do is eliminate as much as risk as possible, but if you don't know baseline risk and how much each precautionary step actually reduces the risk by, you're still shooting in the dark. The only people that can 'win' in biotech are investors or pharmaceutical companies, namely those who can take a portfolio approach.

Many of these also apply for chip startups.

i've talked to a few biotech startups, usually a ceo or founder. the main issues are a consensus in the startup that (1) it's easier to combine numerous unrelated technologies that may not even run in similar environments/platforms to solve a very specific problem, and (2) it doesn't matter their level of skill in applying the tech to solve the very specific problem.

Yeah, most real work using tech doesn't care about platform/environment. Which is why things like Unix get so much usage.

These biotech people have such a higher appreciation for turning input into valuable output then most "computer scientists" have after 20 year careers.

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