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

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

#41
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.

This comes across as exceptionally naive. Protein-engineering is a fundamental technology, and we've been constrained computationally for decades. Few things would have as far-reaching an impact on society as being able to accurately predict protein structure would.

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

#42
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.

This comes across as exceptionally naive. Protein-engineering is a fundamental technology, and we've been constrained computationally for decades. Few things would have as far-reaching an impact on society as being able to accurately predict protein structure would.

Relay is not doing protein engineering or working on predicting protein structure. They are making models of protein dynamics to assist in drug discovery (often using already determined structures). We both disagree with the parent commenter that it's a waste, and to claim that Murcko and D.E. Shaw are going in "blindly" would be ignoring decades of research on protein dynamics of some of the hardest drug targets out there. The fact remains that there aren't many success stories of using simulations of protein dynamics to accelerate drug discovery. Computational chemistry protocols used routinely in pharma drug discovery typically do not include this type of detail.

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

#43
post #42

Earlier quoted context omitted.

This comes across as exceptionally naive. Protein-engineering is a fundamental technology, and we've been constrained computationally for decades. Few things would have as far-reaching an impact on society as being able to accurately predict protein structure would.

Relay is not doing protein engineering or working on predicting protein structure. They are making models of protein dynamics to assist in drug discovery (often using already determined structures). We both disagree with the parent commenter that it's a waste, and to claim that Murcko and D.E. Shaw are going in "blindly" would be ignoring decades of research on protein dynamics of some of the hardest drug targets out…

I know, just an example.

I wouldn't bet against relay right now - historical precendent is irrelevant here. There's an enormous opportunity for application of ML techniques in protein engineering (as an umbrella term...) - I've really been itching to take a crack at it but it's a moonshot...

A well-positioned player with the right people could make a killing in this market right now.

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

#44

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…

> This goes to show that fundamental research in biochemistry is still needed and we are nowhere near having "cracked the code", genomics notwithstanding. Personalized medicine is the future. You will find medication that is tweaked slightly at the molecular level to optimize therapeutic effects for the individual as opposed to a population of individuals.

I don't see how this conception of personalized medicine would work. For many drugs, the binding sites aren't terribly different or different at all between individuals. I can see this being different for larger populations. More likely you'll see drugs created that very specifically target something so that the personalization will be at the level of the drug cocktail as opposed to synthesizing some new molecule. This isn't to mention the possibly wildly different effects you can get from changing something seemingly minor about the molecule. A sort of good example of this is methamphetamine (yes, I know chirality isn't minor but its a good layman's example).

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

#45

Earlier quoted context omitted.

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…

The real cost occurs in Phase 2 clinical trials, where 70 % of promising-looking compounds turn out to be no better than placebo. The body is a complex system with a huge number of enzymes and feedback circuits, this outcome isn't much of a surprise then. You can't blame the FDA. But thanks to Trump's "right-to-try" phase 2 will be a smaller hurdle now. Good luck, let's see how costs develop.

No. Phase 3 is where all the cost of clinical trials comes from, not phase 2. P2 usually involves fewer than 100 patients and lasts for only a few months; P3 often runs to thousands of patients and can last for years, and then can be followed by supplementary P3 and even P4 trials, multiplying costs further.

Phase 2 rises to a high fraction of clinical trial cost only in diseases with a very high mortality rate, like cancer. Then the drug may undergo a variant of P2/P3 trial where the general patient populace serves as early P3 trial participants, thereby reducing P3 trial cost normally paid entirely by the drug manufacturer. But even then, such a phase 3 trial will greatly outcost any phase 2, and will much more definitively answer the questions of drug safety and efficacy.

The rules of those kinds of clinical trials (mostly cancer) where the "right-to-try" law is applicable thus will depart considerably from standard drug safety standards for almost all other kinds of drugs. That's because safety concerns are strongly deemphasized when investigating new cancer treatments due to 1) the high toxicity of alternative cancer therapies (usu. chemo), 2) the low survival rate and lifetime typical of most cancers, and 3) the lack of better alternative treatments.

The lower standard for efficacy (and lower statistical power) inherent in phase 2 trials will certainly play a greater role in "right-to-try" than is usual for typical drugs. But this does NOT imply that taking the greater risks that will arise with these more speculative unproven therapies (like the Laetrile dud cancer therapy ca. 1975) are likely to return greater rewards. In all likelihood, by the time "right-to-try" comes into play for a patient, all hope will have been lost medically. Thus the fraction of cases where a patient will actually benefit from such a "hail Mary" therapy that's been facilitated via this law is essentially zero. Nor is the lack of methodical treatment regimen endemic to these still half-assed therapies likely to teach us much in the process of calling upon them just one second before midnight.

No, "right-to-try" seems mostly an invitation for charlatans to charge megabucks for nutty therapies that have shown no level of success. If they had, "right-to-try" wouldn't have been needed. The era of hoping for a magic elixir is over, except in Hollywood and Trump's Washington, that is.

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

#46
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.

This comes across as exceptionally naive. Protein-engineering is a fundamental technology, and we've been constrained computationally for decades. Few things would have as far-reaching an impact on society as being able to accurately predict protein structure would.

You can call me naive, or you can read my papers. For example, https://www.nature.com/articles/nchem.1821 is a massive simulation of a GPCR that my team designed and ran. It's a similar idea to the Relay work (simulate the dynamics of the protein, make a markov model of the subsets with transition parameters) With that tech, we could easily implement computational mutagenesis. I agree 100% that protein engineering is a great technology and I wish we could do it rationally. But to be honest, none of my computational work can beat what Jim Wells did at Genentech in the late 90s (converting subtilisin to subtiligase through amino acid mutations).

Here's another paper I wrote, https://www.ncbi.nlm.nih.gov/pubmed/24265211 which demonstrates there was a systematic error in protein force field implementations; our work was a major breakthrough in improving structure prediction.

Also, being able to predict structures isn't sufficient to engineer protein function.

Please don't call people naive; especially if they are experts in their field.

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

#47
post #42

Earlier quoted context omitted.

Relay is not doing protein engineering or working on predicting protein structure. They are making models of protein dynamics to assist in drug discovery (often using already determined structures). We both disagree with the parent commenter that it's a waste, and to claim that Murcko and D.E. Shaw are going in "blindly" would be ignoring decades of research on protein dynamics of some of the hardest drug targets out…

I know, just an example. I wouldn't bet against relay right now - historical precendent is irrelevant here. There's an enormous opportunity for application of ML techniques in protein engineering (as an umbrella term...) - I've really been itching to take a crack at it but it's a moonshot... A well-positioned player with the right people could make a killing in this market right now.

Can you describe just how they would make a killing? I mean, in terms of making a product that sold, and produced drugs of value.

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

#48
post #46

Earlier quoted context omitted.

This comes across as exceptionally naive. Protein-engineering is a fundamental technology, and we've been constrained computationally for decades. Few things would have as far-reaching an impact on society as being able to accurately predict protein structure would.

You can call me naive, or you can read my papers. For example, https://www.nature.com/articles/nchem.1821 is a massive simulation of a GPCR that my team designed and ran. It's a similar idea to the Relay work (simulate the dynamics of the protein, make a markov model of the subsets with transition parameters) With that tech, we could easily implement computational mutagenesis. I agree 100% that protein engineering is…

I'm confused as to why you're addressing this commenter using "argument from authority" when you seem to be weakening your position, suggesting that studying protein dynamics has led to significant advances in the field. It doesn't change the fact that you made a flippant remark that a team of some of the most experienced drug discovery scientists in the industry are wasting their time using this approach (despite not having worked in drug discovery, i.e. not an expert in the field), instead of just explaining why you believe this. Didn't mean to make it personal, that's just how I interpret your comment.

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

#49
post #48
post #46

Earlier quoted context omitted.

You can call me naive, or you can read my papers. For example, https://www.nature.com/articles/nchem.1821 is a massive simulation of a GPCR that my team designed and ran. It's a similar idea to the Relay work (simulate the dynamics of the protein, make a markov model of the subsets with transition parameters) With that tech, we could easily implement computational mutagenesis. I agree 100% that protein engineering is…

I'm confused as to why you're addressing this commenter using "argument from authority" when you seem to be weakening your position, suggesting that studying protein dynamics has led to significant advances in the field. It doesn't change the fact that you made a flippant remark that a team of some of the most experienced drug discovery scientists in the industry are wasting their time using this approach (despite no…

[deleted]

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

#50
post #48
post #46

Earlier quoted context omitted.

You can call me naive, or you can read my papers. For example, https://www.nature.com/articles/nchem.1821 is a massive simulation of a GPCR that my team designed and ran. It's a similar idea to the Relay work (simulate the dynamics of the protein, make a markov model of the subsets with transition parameters) With that tech, we could easily implement computational mutagenesis. I agree 100% that protein engineering is…

I'm confused as to why you're addressing this commenter using "argument from authority" when you seem to be weakening your position, suggesting that studying protein dynamics has led to significant advances in the field. It doesn't change the fact that you made a flippant remark that a team of some of the most experienced drug discovery scientists in the industry are wasting their time using this approach (despite no…

There have been plenty of amazing discoveries and advances in the area of protein Dynamics. but I don't think that anybody has any authority to claim that this particular approach is going to revolutionize pharmaceutical discovery.

If you'd like I can also show you a few of my drug Discovery papers. I'm actually one of Shaw's biggest competitors in the field and advise Venture Capital companies who consider investing in companies like relay

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