In my untrained opinion, I don't think that will be as much of a cheat as it might seem. Or more accurately, creating a simulation accurate enough to where it would work for this purpose would be where all the breakthroughs would have to be made. Building a perfect simulation requires an understanding of the system being simulated, that I don't think we fully have of molecular biology -- if we did, I suspect we'd already have many of the answers we are seeking when we do this kind of research.

But I'm no biologist so if someone else is, feel free to correct me.

You may recall Google published AlphaFold in the last few years -- its main goal is precisely this. Combining up that tech with these pipelines is likely to speed things up. It looks like things are already speeding up a lot based on the press release, though. This seems likely to be an area where we'll see some compounding returns over the next couple years.

By the time we can simulate a human body to the degree that clinical trials aren’t necessary I think we have solved disease a long time ago.

All valid points on being able to simulate well enough meaning we would have nearly solved everything to begin with.-

I wonder if, at some point, AI's will perform to such degree they are able to construct "black box" simulations as needed, that nobody understands BUT that are sufficient to empirically experiment on ...

... much in the same way LLM's function now: In an aggregate sense, they are bloack boxes.-