This is only one side of the question. There are thousands upon thousands of potential therapies, all with varying degrees of evidence that they work, with varying degrees of match between the available evidence and the true reality of the potential of that therapy.
We need some process to distinguish between what works and what doesn't work.
The question isn't merely "how quickly can we get this one thing to market" it's "how can we prove that it works as quickly and cheaply as possible, without biasing us to treatments that don't actually work, and with giving all options their proper due."
For a while in machine learning there was a field called "active learning" (might still be ongoing?) that was all about how to choose the most informative questions to ask to learn as quickly as possible.
We face that same question with cancer therapies. Every patien that is on one trial can not be on a trial for a different therapy, so that's one limited resource for how quickly we can learn. But the other limited resource is of course how much we want to spend on validating therapies versus deploying existing, working therapies to a broader group of humans.
We need some process to distinguish between what works and what doesn't work.
The question isn't merely "how quickly can we get this one thing to market" it's "how can we prove that it works as quickly and cheaply as possible, without biasing us to treatments that don't actually work, and with giving all options their proper due."
For a while in machine learning there was a field called "active learning" (might still be ongoing?) that was all about how to choose the most informative questions to ask to learn as quickly as possible.
We face that same question with cancer therapies. Every patien that is on one trial can not be on a trial for a different therapy, so that's one limited resource for how quickly we can learn. But the other limited resource is of course how much we want to spend on validating therapies versus deploying existing, working therapies to a broader group of humans.