One thing that stands out about the history of chemotherapy is that what made it broadly effective in leukemia and lymphoma were not drugs but protocols. Cytotoxic chemo drugs in the 1940’s-60’s had real anti-tumor effects but short-lived remissions until clinicians began administering chemo for longer periods and with _combinations of drugs. _
Until working protocols had been set up, chemotherapy was highly controversial. “As Alfred Gellhorn recently recounted to the authors, the otherwise great clinician Loeb, a giant in the field at the time, had a blind spot when it came to caring for cancer patients and testing chemotherapy. He was fond of saying to Gellhorn, rather openly, “Alfred, you belong to the lunatic fringe.” This “lunatic fringe” of early chemotherapists persisted in trying different protocols until they got success, despite a heavy death toll.
I’m not sure if someone has made this distinction before, but there seems to be a difference between the “discovery phase” when you observe that some treatment has a desirable property (e.g. a drug has anti-tumor activity) and the “engineering phase” when you figure out how to optimize delivery of that treatment.
In the tech industry, the conventional wisdom is that you need rapid iteration for the “engineering phase” of optimizing the performance of something that already sort of works.
The problem is that rapid iteration on human patients is hard to do, and more so today than in the past.
Rapid iteration is also not particularly suited to the structure of controlled trials. Trying lots of relatively small changes is harder at large scale and with formal standards of experimental design. It’s more the sort of thing that makes sense for case series. But it takes a lot of independence on the part of researcher-clinicians, and I suspect that it’s not done enough.