Sep 22, 2026 · 19 min · 10 segments
Earlier this year, the FDA released draft guidance endorsing Bayesian methods and simulation-based evidence in clinical trials in a significant shift in how regulators think about predictive…
Nicole RaleighHost
So if we focus, though, on this idea that you don't know how patients will respond to treatment in clinic and we think about the fact that each patient essentially is unique.
Cancer biology is very much dynamic and heterogeneous, but regulatory frameworks were built for static one test, one answer diagnostics.
And it's just a matter of navigating which are the drugs for the right patients.
And because of the historical regulatory pathways, that means that we very often don't take a lot of information by individual patients into account to make that decision.
And I think overall, the field is moving towards taking more and more information by the patient.
integrated into that decision making about therapy, which is fascinating because it's blurring the lines between therapeutics and diagnostics.
But if we kind of get stuck in the static sort of way where we need to have a single test, a very vertical application, a very narrow specific application, that means that we will just have to keep approving a new test for every eventuality, which means that it's a highly inefficient and a very expensive way to do things.
And that also means proliferation of a lot of diagnostic tests, which means that healthcare systems have to navigate this and then they face the challenge of, well, which tests should we be using? And cost effectiveness comes into play.
And every country of course deals with differently, but it does have ripple effects all the way from research into healthcare provision.
So if we focus, though, on this idea that you don't know how patients will respond to treatment in clinic and we think about the fact that each patient essentially is unique.
Cancer biology is very much dynamic and heterogeneous, but regulatory frameworks were built for static one test, one answer diagnostics.
And it's just a matter of navigating which are the drugs for the right patients.
And because of the historical regulatory pathways, that means that we very often don't take a lot of information by individual patients into account to make that decision.
And I think overall, the field is moving towards taking more and more information by the patient.
integrated into that decision making about therapy, which is fascinating because it's blurring the lines between therapeutics and diagnostics.
But if we kind of get stuck in the static sort of way where we need to have a single test, a very vertical application, a very narrow specific application, that means that we will just have to keep approving a new test for every eventuality, which means that it's a highly inefficient and a very expensive way to do things.
And that also means proliferation of a lot of diagnostic tests, which means that healthcare systems have to navigate this and then they face the challenge of, well, which tests should we be using? And cost effectiveness comes into play.
And every country of course deals with differently, but it does have ripple effects all the way from research into healthcare provision.
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