Hacker News Board Hacker News, browsed like a classic message board
Live data from Hacker News

The Quant King, the Drug Hunter, and the Quest to Unlock New Cures

bloomberg.com

Post reply on HN
Print view View original

21–30 of 51 posts

Re: The Quant King, the Drug Hunter, and the Quest to Unlock New Cures

#21

Post by aaavl2821 »

reasonattlm wrote: post #6
dekhn wrote: post #2

It really remains to be seen whether these approaches will make any difference in efficacy or cost of pharmaceuticals. Blindly thinking that having better simulations of proteins and drugs is going to solve any of the hard problems has led to a great deal of waste.

Most of the cost is regulatory. But there is a meaningful difference between a world in which it costs $1M to screen and a world in which it costs $100k to screen. In the latter world, startups become viable with intent to find a drug candidate, rather than only being viable if they already have one. That's a big important difference, and one that was only otherwise going to be solved by everyone transitioning from s…

You can do a screen with a CRO for low six figures

Re: The Quant King, the Drug Hunter, and the Quest to Unlock New Cures

#22

Post by dekhn »

HarryHirsch wrote: post #13
dekhn wrote: post #2

It really remains to be seen whether these approaches will make any difference in efficacy or cost of pharmaceuticals. Blindly thinking that having better simulations of proteins and drugs is going to solve any of the hard problems has led to a great deal of waste.

A great deal of waste? 25 years ago we thought that genomics would boost drug discovery and development. It didn't pan out quite like that but thanks to the Human Genome Project costs for sequencing have dropped to almost nothing, and we have learned a great deal about protein evolution. Talk about waste!

I wouldn't really say the HGP taught us a lot about protein evolution. The original few genomes were snapshots of indivduals or amalgams. We do know a bit more about evolution from sequencing many more people (post-HGP), but it hasn't really been super-productive compared to previous work (note, my postdoc work was on protein functional evolution) from before the HGP.

For example, Carl Woese, using only 16s RNA from a wide range of species and mostly hand-computed similarity clustering, managed to find a previously unrecognized kingdom. I don't think we've really had any truly revolutionary discoveries like that from HGP and post-HGP sequencing that focuses on humans.

Re: The Quant King, the Drug Hunter, and the Quest to Unlock New Cures

#23

Post by dekhn »

davidkuhta wrote: post #4
dekhn wrote: post #2

It really remains to be seen whether these approaches will make any difference in efficacy or cost of pharmaceuticals. Blindly thinking that having better simulations of proteins and drugs is going to solve any of the hard problems has led to a great deal of waste.

The breadth of your second statement gives me pause, but as I'm not well versed in computational biology, I'll just ask: What are the hard problems?

The single hard problem in pharma is predicting which drugs will get through to full approval, and how much it will cost from initial results.

If you could do that reliably, it would completely transform pharma.

Re: The Quant King, the Drug Hunter, and the Quest to Unlock New Cures

#24

Post by dekhn »

melling wrote: post #3
dekhn wrote: post #2

It really remains to be seen whether these approaches will make any difference in efficacy or cost of pharmaceuticals. Blindly thinking that having better simulations of proteins and drugs is going to solve any of the hard problems has led to a great deal of waste.

I’m not sure why you consider it a great deal of waste. Building better models that simulate a human biological process must have some sort of payoff? It increases human knowledge, and should provide a foundation on which others can build.

I didn't say that building better models didn't have a payoff. I'm saying this particular approach shows little to no evidence that it's truly revolutionary or even a marginal/incremental improvement over random guesses.

Re: The Quant King, the Drug Hunter, and the Quest to Unlock New Cures

#25

Post by arandr0x »

For this stage of drug discovery (finding potential hits off of ligand databases, finding potential targets, and refining ligands in silico without running real high-throughput lab work) machine learning may work better at lesser cost. It's the direction (some) research is going right now.

Of course the real cost of drug development is running clinical trials, and losing something like 90% of ligands because they don't make it into the bloodstream, can't be synthesized at scale, or wind up having no efficacy in vivo for no reason anyone can fathom.

(Even making "copycat drugs" where you pick a known target, known ligand class, and try to minimally alter the synthesis process to get a newly-patentable product can sometimes have odd surprises, including the kind of odd surprise where being more specific to the identified target leads to diminished efficacy.)

This goes to show that fundamental research in biochemistry is still needed and we are nowhere near having "cracked the code", genomics notwithstanding.

Re: The Quant King, the Drug Hunter, and the Quest to Unlock New Cures

#26

Post by jjoonathan »

cowsandmilk wrote: post #14
jjoonathan wrote: post #9

Earlier quoted context omitted.

A waste for society? No. A waste for the people doing it who are never going to be appropriately compensated for the value of their failure to society? Yes. The churn that arises as a consequence of the fact that we don't know how to reward failure (or even merely punish it less) is the real waste.

???? I assure you, Mark Murcko (and others at Relay) are paid competitively to similar people in pharma.

> Mark Murcko

He's on the admin / capital side of the equation and will do fine, I'm sure.

> paid competitively

That's not an endorsement and hardly an excuse. Unless things have changed dramatically in the last year or two, pay for computational / structural biologists is 1/2 to 1/3 of what a person with the same skills gets for helping build Uber for Poodles, which is in turn 1/2 to 1/3 of what a person with the same skills gets at AppleGooFaceZon or on Wall St.

The field, like many scientific fields, runs on passion, naivete, and green cards, and is quite abusive to the people doing the actual work, even though it showers adjacent concerns with money.

If science didn't suffer from such a severe value capture problem, scientists could win a seat at the table, but it does, so practicing scientists get shut out and the money goes instead to capital/risk, showmen (often "graduated" scientists themselves), lawyers, etc.

Re: The Quant King, the Drug Hunter, and the Quest to Unlock New Cures

#27

Post by vapemaster »

Tehchops wrote: post #20

I see you there, Ubuntu desktop :) Interesting he's using a mbp box as a monitor stand. On to a more serious note: is this kind of computing work sped up with GPUs?

Custom ASIC hardware for running molecular dynamics. check out Anton [1]

[1] https://en.m.wikipedia.org/wiki/Anton_(computer)

Re: The Quant King, the Drug Hunter, and the Quest to Unlock New Cures

#28

Post by jimmygatz »

vapemaster wrote: post #5

Yup. And judging by their team and strategy they are likely using a highly empirical ligand discovery platform (ie DEL) and using the (admittedly best in class) MD for guiding med chem. Taking the hard problem of drug discovery and then saying you are going to do rational design (a road riddled with dead bodies) on dynamic alloseteric sites of challenging targets is a lofty goal to put it mildly..

Hi Vapemaster and others,

Currently doing some research on the industry and curious if you could link to some of the "dead bodies"? Also curious if you know how Verseon's model (https://www.verseon.com/) stacks up versus some of the others mentioned? Obviously it might be hard to say since all their drugs are currently in the pre-clinical trial phase but would appreciate any info you might have.

Thanks in advance

Re: The Quant King, the Drug Hunter, and the Quest to Unlock New Cures

#29

Post by vapemaster »

dekhn wrote: post #23
davidkuhta wrote: post #4

Earlier quoted context omitted.

The breadth of your second statement gives me pause, but as I'm not well versed in computational biology, I'll just ask: What are the hard problems?

The single hard problem in pharma is predicting which drugs will get through to full approval, and how much it will cost from initial results. If you could do that reliably, it would completely transform pharma.

That's like saying the single hardest problem in AI is having a beyond human intelligent general AI.

Sorry not trying to be pedantic but predicting what xenobiotics (ie foreign molecules) will do in the human body, much less a diverse sample of them is a really really really hard problem. One that will only be approximated and poorly at that. I'm sure there will continue to be approaches to reduce risk but clinical trials only exist because they have to. The only way we can evaluate safety and efficacy is empirically.

Predicting things like hERG toxicity is somewhat doable. And I think the realistic bright future of AI in medicine will include better on target tox prediction and some off target effects. But it's hard enough to design the drug to bind the target, imagine predicting it's affinity for all other proteins and their isoforms in the population...

Re: The Quant King, the Drug Hunter, and the Quest to Unlock New Cures

#30

Post by jjoonathan »

vthallam wrote: post #16
jjoonathan wrote: post #9

Earlier quoted context omitted.

A waste for society? No. A waste for the people doing it who are never going to be appropriately compensated for the value of their failure to society? Yes. The churn that arises as a consequence of the fact that we don't know how to reward failure (or even merely punish it less) is the real waste.

> A waste for the people doing it who are never going to be appropriately compensated for the value of their failure to society? Yes. Judging by their profiles, I don't think they care if they end up being a failure with this Venture.

Yes, but if the scientific value capture problem were solved then science could scale appropriately rather than beg for charity.

I was (and would be) much more valuable to society as a structural biologist than I am as a software engineer, but the market disagrees so vehemently that it's cost prohibitive for me to fight it, and the result is that we all lose. The reason why it disagrees is not hard to understand and not particularly difficult to categorize as a market failure rather than a "hard truth." I can't really think of a good way to actually address the problem, though, so mostly this just amounts to venting.

Post reply on HN