I think this is the critical aspect. You don't need to own a supercomputer to run simulations in supercomputers. Sometimes you don't even need supercomputers at all. It might be a challenge but it's not prohibitive.
What's clearly a blocker is the verification & validation work to assess if a specific model actually works. You need to run experimental tests to check if your module is any good, and you need to run experimental tests to check if the output of your computational models correlate with reality. That costs both time and money.
And according to experience, such studies are usually conducted simultaneously with Laboratory experiments, or already have Lab results they can compare with. If not, such study acts as a new source of synthetic MD data which can be picked up by the experimental folks.
I do agree that people who write such blogs tends to sell these ideas or studies as finished products which they are far from. The product of such studies are usually a paper or in other cases a patent. An idea others can build upon, like lego bricks.
Physical laboratory time, materials, and workers are also scarce and expensive. And physical lab tests can consume a lot of calendar time.
So, even with the constraints and costs, using the supercomputer to run 1,000 or 10,000 tests and then physical lab tests on only the few most promising results can still less costly in both funds and especially calendar time than the costs and time to run a similar number of physical lab tests to produce the results.
It is literally a balancing of the scarcity and costs of each mode of getting to the results, and those experts in the field, with their own labs, are making the claim that this is the way their research should proceed. Do you have actual information and specific knowledge that in fact proves them wrong (b/c that comment seems a lot more hand-wavey vs theirs)?
A lot of the physical lab tests end up showing effects we did not know exist, which is why they are interesting - simulations are historically terrible at predicting things we don’t know can exist.
See the pharma adventures in simulating potential drugs in the 90’s-early 2000’s. A lot of heat a noise for little actual effect.
But then I realized people screech about asbestos far in excess of the actual risk it poses, and here someone is screeching about CF. So it kind of is like asbestos in that way.
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