Be in a field where tech is the limit

The only way to get around these cultural/institutional barriers is to found your own business. I started a pharma company and ran it like a startup (bc it was a startup). Paid decent salaries, worked really hard (literally, one of our contractors complained, “you guys work so hard”). Exited before our phase I/II completed.

A parallel way is to start a company that only does one part, say a software based part. Pharma will pay more for tools that solve their problems than they would pay for a couple of FTEs to solve their problem directly. The problem is your customer may not know how to put your product to use, or even understand its value. So sales is no slam dunk.

I loved my time in the pharma business but was happy to go back to what’s called “tech.” Culturally the life sciences CES are full of some dreadful pathological practices, and I prefer the pathological practices I’m familiar with :-(.

I was going to include market makers in my previous post, but didn't to keep things simple. I agree the benefits from them seem pretty clear, in the sense that lowering the spread and increasing liquidity helps retail investors (and maybe market stability in general). But there are a few points here that I think make a lot of people uncomfortable.

First, it's not so clear this is meaningful work. If I'm a smart college graduate and go to work in biotech, I get to save lives and cure disease (ideally). If I go to work at a market making firm, I get to ... lower the spread? I think it's quite reasonable for someone to forgo doing this because they feel it doesn't make a meaningful contribution to the world.

Second, I've watched many incredibly talented people disproportionately go work at HFT firms, and it's hard to to avoid the impression this is socially wasteful. Efficient markets are nice, but do the markets really need to be efficient on a microsecond scale? It seems like the talent sink here is unfortunate and society might be better off if some of them worked instead on, say, biotech or alternative energy sources.

I agree the the cause is obvious: finance pays more money. But it's hard to avoid thinking about solutions that reduce the profitability of HFT and don't harm market efficiency significantly, for example eliminating the subpenny rule [0]. It seems clear to me that if the current incentives result in one industry essentially monopolizing the nation's most quantitatively able workers, then those incentives might need to change.

I don't think this point was made explicit in the original post you responded to, but it lurks in the background.

Finally, I really wish you would treat other examples of market participants. Because right now you've done the easy cases, the ones that I, a total outsider, can mount a defense for. Again, it's the other ones that are interesting. And it's clear there are a ton of participants who are a) not aimed at increasing access for retail investors and b) not market makers.

[0] https://www.chrisstucchio.com/blog/2012/hft_whats_broken.htm...

i have so many questions about this comment

> The majority of that headcount spend is just to capture "talent" so others don't have it.

I think people on both sides forget this. You don’t need 300 engineers to solve very many problems, but if you use 300 it means 2 other companies don’t solve it too.

And just because you’re making a ton of money working for a big company, doesn’t mean that what you’re doing is that important. It might just be to humor you. Even at small places, sometimes the established players get thrown a bone, working on something frivolous because it makes them happy, so they stick around.

Sure!

Our domain is precision oncology. In brief, this is about matching cancer patients with available targeted therapies by examining the genome of their cancer. This is different from how the majority of cancer patients are treated today: surgery and {chemo,radio}therapy.

Here is a problem in our domain where tech is one of the limiting factors.

If you look at the DNA of any cell and compare it against the reference genome, you'll find a lot of differences, aka variants. Typically even more so if you're looking at a sequenced tumour (~1e6 variants). This is your hay stack. And a variant that can be medically targeted to treat the cancer is the needle. The definition of what variant is "clinically relevant" is layered, context-dependent, and (partially) regulated. Software is responsible for automating away the majority of variants, say down to 10-100, in a justifiable, traceable way. It's also responsible for giving tools to the clinician to deal with the remaining ones. This manual step typically involves an informed line of questioning about each variant backed by 100s of supporting data points about it.

Without these two tech pieces, interpreting a single molecular pathology report can and does take many hours of (expensive) expert time, instead of minutes. For a rough sense of scale: human genome has ~3e9 nucleotides (ACTG), has ~3e4 known genes, ~1e6 known gene interactions, and ~1e8 known variants. Typical whole genome sequencing produces > 30GB of raw data (compressed).

This is probably the first problem everyone runs into. There are plenty of other ones, some more challenging and interesting than others. Feel free to send me an e-mail if you'd like to discuss this more! amir[at]streamlinegenomics.com