I'm a bioinformatician at a translational cancer research institution & have some sense of the stumbling blocks and opportunities in this space.
First off, doing away with clinical trials as we perform them now would certainly speed up pairing drugs with patients but it's not going to happen unfortunately. Drug trials aren't designed to minimize search paths, they are designed to minimize risk.
With terminal diseases like many cancers the rules are bent a little but what's important to understand is that these are real people making the decisions ultimately. Sometimes the most information can be gained by withholding drug, and isolating another treatment's impact but if you are a patient with a terminal prognosis, or the doctor trying to treat that patient, are you going to choose not to take something that might help you?
This is a point of frustration for many in research fields because it means clinical data is hugely noisy. Patients are often cycled through different drugs quickly to find something that takes hold, while at the same time going in for as much chemo/radiation treatment as they can bare.
I'm not saying these approaches aren't relevant, they just won't happen as a grand reimagining of our drug approval system. What is starting to happen however, is reclassification of cancer 'type' based on genetic profiles meaning ovarian cancer may have certain genetic similarities to lung or pancreatic so instead of treating melanoma, you can treat a cancer with a disturbed MAP pathway.
All the same, I'm glad he's working on this problem because it's huge, and I look forward to seeing the point of view of the HN community.
edit: Though obvious to some, I should also mention this problem is complicated by the fact that genetic information is private and dissemination is highly restricted. Patients can release this info but it does often inhibit massive cross-patient research.
There are many new sorts of trials coming online that are closer to the model he's proposing here. (Which, BTW, is more like A/B testing than like a classical RCT.) See esp. adaptive trials, point-of-care trials, and global cumulative trails. Some of these new models are really being run by real clinical researchers.
This is a great point and I think many doctors are pushing for new ways to perform clinical trials but adaptive trials generally only change a single parameter during the course of a trial (dosage for example). And POC trials open up the number of patients that may be willing to participate by administering tests at local sites but the state of clinical trials still has a long way to go. Once it's firmly in drug companies' and insurance agencies' best interest to open things up then we may see more rapid change.
"opening things up" is definitely going to help, and is a huge part of the philosophy of my nonprofit science research org (our first project will be taking an anticancer through preclinical). There are, however, a ton ton ton of biological issues that still are, open or not, difficult to surmount, sometimes not even having to do with the cancer itself (bioavailability, side effects, etc).
Comments
I'm a bioinformatician at a translational cancer research institution & have some sense of the stumbling blocks and opportunities in this space.
First off, doing away with clinical trials as we perform them now would certainly speed up pairing drugs with patients but it's not going to happen unfortunately. Drug trials aren't designed to minimize search paths, they are designed to minimize risk.
With terminal diseases like many cancers the rules are bent a little but what's important to understand is that these are real people making the decisions ultimately. Sometimes the most information can be gained by withholding drug, and isolating another treatment's impact but if you are a patient with a terminal prognosis, or the doctor trying to treat that patient, are you going to choose not to take something that might help you?
This is a point of frustration for many in research fields because it means clinical data is hugely noisy. Patients are often cycled through different drugs quickly to find something that takes hold, while at the same time going in for as much chemo/radiation treatment as they can bare.
I'm not saying these approaches aren't relevant, they just won't happen as a grand reimagining of our drug approval system. What is starting to happen however, is reclassification of cancer 'type' based on genetic profiles meaning ovarian cancer may have certain genetic similarities to lung or pancreatic so instead of treating melanoma, you can treat a cancer with a disturbed MAP pathway.
All the same, I'm glad he's working on this problem because it's huge, and I look forward to seeing the point of view of the HN community.
edit: Though obvious to some, I should also mention this problem is complicated by the fact that genetic information is private and dissemination is highly restricted. Patients can release this info but it does often inhibit massive cross-patient research.
There are many new sorts of trials coming online that are closer to the model he's proposing here. (Which, BTW, is more like A/B testing than like a classical RCT.) See esp. adaptive trials, point-of-care trials, and global cumulative trails. Some of these new models are really being run by real clinical researchers.
This is a great point and I think many doctors are pushing for new ways to perform clinical trials but adaptive trials generally only change a single parameter during the course of a trial (dosage for example). And POC trials open up the number of patients that may be willing to participate by administering tests at local sites but the state of clinical trials still has a long way to go. Once it's firmly in drug companies' and insurance agencies' best interest to open things up then we may see more rapid change.
"opening things up" is definitely going to help, and is a huge part of the philosophy of my nonprofit science research org (our first project will be taking an anticancer through preclinical). There are, however, a ton ton ton of biological issues that still are, open or not, difficult to surmount, sometimes not even having to do with the cancer itself (bioavailability, side effects, etc).