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Comment by bee_rider | Hacker News Reader

Is it possible that computer tech was just weirdly susceptible to startup funding, and it is a really poor fit for biotech?

Computers mostly are

* well understood at every step (well, at least it was all designed by humans and the bits and bobs do what they say on the tin).

* mostly involve producing some kind of output for everyday normal people to use, in the end.

So they are easy to understand and evaluate. Even some investors can manage it.

Biotech stuff seems to mostly involve making tools for other technicians and scientists. And the process by which is works is some ridiculous, quirk-laden byzantine madness that evolution happened to throw together. At least from an outsider point of view it seems like an absolute nightmare.

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It’s actually the other way around: it’s surprising software investing works so well compared to biotech.

While biotech companies carry a lot of all-or-nothing R&D risk, their “product market fit” is all but guaranteed. Their addressable market size is well known based on patient numbers and how much they can charge nationalized healthcare agencies and insurance companies based on quality of life improvements is well understood. Once they have premarketing approval, they’re all but guaranteed an exit to one of the pharmaceutical giants. The most promising ones get acquired in phase II before efficacy is even 100% demonstrated.

Look no further than IPOs: on HN we lament all the unprofitable public tech companies but the average biotech IPOs pre-revenue! Before it’s even legal for them to sell a product! That’s increasingly been the case since the 80s due to the exhaustion of small molecules and other low hanging fruit.

In practice, scientific due diligence is harder to fake than aspirational user growth numbers which are far easier to game (case in point: Reddits ongoing bullshit). The FDA isn't going to let anyone put a dozen people at risk of death in phase I trials without a level of due diligence that puts all VCs to shame.

I have a friend who plays the stock market by reading papers published by publicly traded biotech companies and shorting the ones that seem to be fabricating evidence. This works well enough that he doesn't need a job.

Is your friend Nathan Anderson?

https://en.wikipedia.org/wiki/Nathan_Anderson

That's a really interesting approach. The trick would be knowing the indicators of fabricated data. Or perhaps just knowing when the data isn't good enough to pass the next clinical trial.

yeah, he says it's obvious but I've read some of the same papers and I just don't have the background to be confident

How does he afford a short position for such a long time until the market caught up to him?

Perhaps he’s buying deep out of the money puts instead of actually shorting

Wow that’s truly fascinating. I’d love to hear your friend tell the story of how he got into it and how he makes it work, if he ever finds himself in an autobiographical mood.

Part of the trick of having an edge over the rest of the market is to not tell anybody, at least not widely.

That's why all those "I tell you about my secret to making 5 grand a day if you click the link below, for free" youtube ads are obviously all scams.

It is an absolute nightmare. Biology is fundamentally fuzzy and our knowledge is incomplete. Biological actors, DNA and RNA and proteins, can act in surprising ways in feedback loops that are extremely difficult to track and quantify.

Imagine every time you needed to troubleshoot something in a computer, you had to break out the multimeter. But the multimeter only works for one specific thing, which is an indirect measurement of the phenomena you’re actually interested in and trying to troubleshoot. Also the multimeter has some serious flaws and biases that make it seem like it’s working, but everything you get out of it is wrong and leads you to misinterpreting your results. That’s what its like to do biology.

A lot of innovation and progress is made when new tools to probe what’s going on in biology are invented. For example, cell viability assays used to be conducted by literally counting the number of live cells vs dead cells. Now, you can use a photometric test that’s extremely easy and takes a lot of guesswork out of the assay and makes it routine.

Researchers fundamentally need more of those types of assays to make life easier. And that’s where the dream and the profit people in biotech are chasing after.

Also, due to ethics rules, you aren’t allowed to open a computer to probe it with your broken multimeter unless it has already died. With a lot of paperwork, you may be allowed to probe an abacus and extrapolate the results to a computer.

This reminds me of a school project (building a sound card) where I noticed that when I plugged the oscilloscope at one point it changed the output at another point --> I threw out the board and decided to never do hardware again..

If the probe was single ended (e.g. not a differential probe or handheld unit), you may have shorted something to ground without realizing it. Was a long time before I figured that one out.

Nope it was a differential probe. I suspect that we broke something in the board when plugging the probes..

> Imagine every time you needed to troubleshoot something in a computer, you had to break out the multimeter.

What disturbs me sometimes is that many people in software engineering approach debugging like empirical science. Run experiments, gather data, fit some curve, essentially. In the end, a program is a product of the mind. It's pure logic, and fundamentally it's understandable, unlike the real world which can at every turn have new surprises for you. We should think more and measure less.

Gold rushes and pickaxe sellers comes to mind.

https://www.investopedia.com/terms/p/pick-and-shovel-play.as...

No, I think software companies work well with startup funding simply because of the strange effect that unit costs have on software profits.

The way computer (and especially internet) companies work is that once you have a working product, you can sell it a practically infinite number of times for practically zero marginal cost.

This means that the successful software/internet companies are INCREDIBLY profitable, since they can sell the same product millions of times.

Are startup investors good at predicting which company is going to be successful? Oh god no, they are awful at it. 90% of the companies they invest in fail completely.

It doesn't matter, though, because they only need one success to make all those failures worth it. The cost of investing in a failure is WAY lower than the cost for NOT investing in a success.

This means they don't really care that they can't evaluate which companies will be successful, they just cast a wide enough net to not miss the successes.

How is this different from an investment in, say, BioNTech?

In other words, if this single product the company is working on succeeds, then the unit cost can be brought down so much that it's still a gold mine.

Near zero unit cost is fundamentally different than “bringing down unit cost”. It just isn’t the same.

I'd call $0.18 for a Covid-19 vaccine dose a "near zero cost".

Lots of Biotech stuff does fine, and plenty of tech startups are basically frauds (WeWork for example). I don’t think you can extrapolate that startup funding doesn’t work for Biotech.

I'm not sure what makes WeWork a tech startup. Renting short term office space is not a high-tech endeavor. But it's true that there are plenty of tech startup frauds, like Nicola.

Their argument paraphrased from the failed S-1

https://www.vox.com/recode/2019/8/14/20804029/wework-ipo-tec...

FWIW, the WeWorks I've worked in have better tech than most traditional offices I've worked in. The printing and room booking experiences are pretty great.

Because we work isn't a short term office rental it is a company that aims to "revolutionize global consciousness" which is clearly a growth industry.

Revolutionizing global consciousness sounds more like a religion or something, but whether it was a, uh, niche religion or a real estate company, surely neither of those things is tech.

Tell that to Softbank

I’m sure there are other great examples, but WeWork doesn’t really seem like one; they were a real estate company, right? Cryptocurrency stuff maybe could be a better example though.

I feel like Crypto generally delivers on what it promises in terms of technology. If I go to investors to found Holebucket to produce the worlds first bucket manufactured with a one inch hole straight through the bottom, it isn't exactly hard to accomplish my goal. Crypto startups have a product, it's just a really dumb product. But Theranos for instance just straight up never had a product in the first place.

A few years ago, I posted an anecdote from my family on faked science in a biotech lab

https://news.ycombinator.com/item?id=25926188

The problem appears to be that our present text conversation climate is such that you must either pick Team Science or Other Team, and should you mention that there are faked results hiding in plain sight, people get upset because they think perhaps what you're saying is "Maybe vaccines do cause autism" and "Maybe HCQ does cure COVID-19".

But that's not the truth. There is no monolithic Science entity. It is a property of every organization that reward-alignment is a stronger long term mechanism than fact-alignment. And it is impossible to direct the two in the same direction. This means that among the science establishment, there will be those who have ruthlessly optimized for the reward.

This is part of why the general Internet arguer's approach of "There is some evidence that X is Y look at this study url://url.url/url.pdf" is often the blind leading the blind.

Non omnis scientia est scientia.

Yes. Most people bring it up because they have an interest in a specific study or result being wrong, which I suspect has trained people to be dubious of anyone questioning The Science.

And some people treat it as a quasi belief system, which makes sense, with precepts like 'the world is deterministic, causes precede effects' and so on. You could do worse. But they aren't scientists and they don't generally grok that science is an activity whose output is sometimes useful models and not 'Truth'.

My mental model here is that you thus get people who trust in science as a paradigm, who then see doubt or skepticism as aimed against the whole edifice that is part of their fundamental understanding of the world, resulting in discomfort and leading to expected results.

In other words pretty normal stuff that resembles when you come across an argument whose implications are opposed to your principles, that you suspect of trickery, but lack the rhetoric to dismantle yourself.

"You can't trust anything" (with an implied "But you can trust me.") is, however, the battle cry of the charlatan.

Part of the exasperation of "Team Science" is that so many from "Team Other" are not acting in good faith. Most of "Team Other" doesn't actually care about getting to truth--they only care about winning (for some value of that--the leaders grifting and the followers "sticking it" to the other team).

> The problem appears to be that our present text conversation climate is such that you must either pick Team Science or Other Team, and should you mention that there are faked results hiding in plain sight, people get upset because they think perhaps what you're saying is "Maybe vaccines do cause autism" and "Maybe HCQ does cure COVID-19".

Assume that you consider yourself unable to evaluate the truthfulness of scientific claims.

Being told that claims you'd thought were properly vetted are actually wrong, then means that you have no way to know if other claims are accurate or not.

If your process doesn't work, then any knowledge based on that process is called into question.

It is just a way for large biotechs to offload some of the risk / cost of R&D to VCs in exchange for some of the upside. People are always willing to make those types of bets.

I don't think it's about the type of tech. Calling both groups "tech companies" is misleading to start with. The California start-up ecosystem is based on applying tech to create consumer products and once market fit and growth potential are evidenced it's straightforward to scale it globally.

Biotech companies are developing new technology, in a highly regulated environment where, like other comments point out, there's a predictable economic niche. They only share a denomination, the dynamics are wholly different.

It's susceptible for funding because the marginal cost is (typically) close to zero after the first unit is sold.

Computers have fast build times, and very very fungible inputs

You can experiment quickly, and you aren't super susceptible to lock in on any particular vendor that would eat your profits

Making copies is also basically free

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