Comment by entee

Some trials fail because we didn't have a "better" drug for a given target, many fail because we don't know the right biology. Biology and knowing precisely how to modulate the right thing is more gating than "design a better compound".

Better for what is the question and while sometimes the answer is "solubility, metabolism, off target toxicity", more often it's "you misunderstood something about the biology of this disease".

Maybe you needed more potency than your assays said you needed.

Maybe you missed something else the target does.

Maybe you had the right effect on the target but the body found a way to compensate (in an undesirable way).

Maybe the target looks like it matters in all sorts of model systems, but in real life it doesn't matter at all!

Many such cases. AI might marginally help in these scenarios, but doesn't look like it will eliminate the problem. AI can't help us with what we fundamentally don't know and have zero data for, or for which data is extremely hard to get.