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Comment by busyant | Hacker News Reader

> every kid can draw up novel structures. Then: how do you actually fabricate these (in the case of real novel chemistry and not some building-block stuff). Noone has a clue!

Yep. I worked at a biotech startup in the early/mid 2000s.

We had a 2-pronged approach to finding small molecule drugs: 1) traditional medicinal chemistry based on simple SAR (structure-activity relationships) and 2) predictive modeling (before ML was hot).

The traditional med chemists were, in my opinion, rightfully skeptical of the suggestions coming out of the predictive modeling group ("That's a great suggestion, but can you tell me how to synthesize it?").

As one of my co-workers said to me: "The predictions made by the modeling group range from pretty bad to ... completely worthless."

It's possible that things have gotten better, though, as I haven't done that type of work since about 2008.

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It's gotten better. The future looks like generative or screening models that feed structures to ADMET/retrosynthesis models which close a feedback loop by penalizing/rewarding the first-pass models. Then there's machine-human pair design flows that are really promising, basically ChemDraw with the aforementioned models providing real-time feedback and suggestions. It wouldn't surprise me if in a decade you could seed generative models with natural language, receive a few structures, alter them in a GUI with feedback, and then publish a retrosynthetic proposal + ADMET estimations with the candidate structure.

With high-throughput screening and automation, even small/medium-sized players can start building internal databanks for multi-objective models.

> The traditional med chemists were, in my opinion, rightfully skeptical of the suggestions coming out of the predictive modeling group ("That's a great suggestion, but can you tell me how to synthesize it?").

Start by plugging it into askcos.mit.edu/retro/ then, do your job?

> As one of my co-workers said to me: "The predictions made by the modeling group range from pretty bad to ... completely worthless."

Workers feeling threatened by technology think the technology is bad or worthless, news at 11.

Chemical synthesis is much more than just retrosynthesis. Even if it was, you can not just plug in the novel previously unsynthesized molecule and expect any reasonable results. Furthermore, the tool is based on Reaxys which in turn uses already established reaction routes and conditions from literature and patents. Good luck optimizing yields for something you don't know even how to synthesize, let alone what conditions to use.

> Chemical synthesis is much more than just retrosynthesis.

Of course, but we are talking about chemical discovery - after which you want to test if the compound theoretical capabilities work on cells. Yields are not yet a concern!

> expect any reasonable results

No it won't do all the work, but it will direction, and suggestion for which pathways could be used.

> Workers feeling threatened by technology think the technology is bad or worthless, news at 11.

I appreciate the sentiment and I think it's understandable to think that. In this particular case, however, my co-worker was one of the smartest / most talented people I've worked with. I can assure you that he did not feel threatened in any way. His comment was sardonic, but not borne of insecurity.

To be fair, the members of the modeling group were also quite talented. They were largely derived from one of the more famous physical/chemical modeling groups at one of the HYPS schools. But even they acknowledged that on a good day, the best they could do was offer suggestions / ideas to the medicinal chemists.

In fact, one of the members of the modeling group said this to me once (paraphrasing): The medicinal chemists are the high-priests of drug discovery. We can help, but they run the show.

As mentioned by someone who responded to my original comment, the usefulness of ML/modeling has likely gotten much better over the past 10 - 15 years.

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