The disjointed and incomplete picture garnered from clinical trial data so eloquently detailed by Dr. Thacker in his post bears particular relevance in the case of oncology drugs, which address a disease with a vast array of underlying molecular pathologies that are specific to each patient. There is no way to systematically evaluate the safety and efficacy of medicines that are used for a disease state characterized by varying levels of metabolic, genetic, immunological, and physiological dysregulation.
The ”secret sauce” of cancer treatment is to find the right drug for the patient at the right time of their disease. It sounds far easier than it is, and for good reason: cancer is the most complex of human ailments. Due to the unique genetic background of each patient, and the specific history of their cancer, each patient’s disease is a “one-of-a-kind” affair. There is no way to systematically evaluate the safety and efficacy of oncology medicines across wide populations without considering the nature of the cancer itself. This is why precision oncology is so desperately needed to address each patient's cancer on a case-by-case basis.
But it isn’t hopeless. Far from it. While precision oncology is just in its infancy, there is little doubt that by applying our burgeoning capabilities in genetic sequencing and AI-based modeling using huge datasets, we can now determine which patients are most likely to benefit from specific medicines. In many (hopefully most) cases we can genetically determine if the target of a therapeutic are present and playing a role in disease etiology.
When I started graduate school in the late 70’s, I don’t think anyone could have imagined that in a half century we would be engineering human cells and viruses to fight cancer. Over a single career, we have gone from a therapeutic arsenal of cytotoxic medicines to one that includes targeted agents such as monoclonal antibodies and “living drugs” comprised of human cells and viruses. Yet we are still in the early days of the immunotherapy revolution. There are more great things to come.
Great to hear some optimism about precision oncology! Lately, I've stumbled across a lot of criticism. At some point, I was planning on putting together a rebuttal of a number of the critiques that are circulating in public discourse. Fortunately, most of the criticism is not emerging from within the field. I do hope we find a way to speed up progress.
Stetson, I am trying to figure out the basis for criticism of precision oncology. Surely we aren't better off using the same treatment protocols for different patients without considering the characteristics of each patient's cancer. I suspect this criticism that is not
"from within the field" is based on hype and not expertise.
There was a 2023 book by James Tabery called 'Tyranny of the Gene' that immediately comes to mind as an example of the critique I see. The critique, which is borderline conspiratorial, is that "Big Pharma" tricked funding agencies and research science with slick marketing and hype into an over-investment in somatic mutation theory. They argue there's been a relative disinvestment in social and environmental determinants of complex disease because of this. The critique is silly of course.
There are more marginal and reasonable critiques not of precision oncology per se but of the evidentiary standards enforced by the FDA on precision therapeutics, the research practices common to precision oncology trials (few randomized designs, convenient censoring, subpar comparators, etc), and corporate COI issues from voice like Vinay Prasad and Bishal Gyawali. I have my own rejoinders to some of these critiques (i.e. selective requests for rigor and tradeoffs should favor innovation) but ultimately critiques focused on improving research science practices I look upon as beneficial to the overall project.
The disjointed and incomplete picture garnered from clinical trial data so eloquently detailed by Dr. Thacker in his post bears particular relevance in the case of oncology drugs, which address a disease with a vast array of underlying molecular pathologies that are specific to each patient. There is no way to systematically evaluate the safety and efficacy of medicines that are used for a disease state characterized by varying levels of metabolic, genetic, immunological, and physiological dysregulation.
The ”secret sauce” of cancer treatment is to find the right drug for the patient at the right time of their disease. It sounds far easier than it is, and for good reason: cancer is the most complex of human ailments. Due to the unique genetic background of each patient, and the specific history of their cancer, each patient’s disease is a “one-of-a-kind” affair. There is no way to systematically evaluate the safety and efficacy of oncology medicines across wide populations without considering the nature of the cancer itself. This is why precision oncology is so desperately needed to address each patient's cancer on a case-by-case basis.
But it isn’t hopeless. Far from it. While precision oncology is just in its infancy, there is little doubt that by applying our burgeoning capabilities in genetic sequencing and AI-based modeling using huge datasets, we can now determine which patients are most likely to benefit from specific medicines. In many (hopefully most) cases we can genetically determine if the target of a therapeutic are present and playing a role in disease etiology.
When I started graduate school in the late 70’s, I don’t think anyone could have imagined that in a half century we would be engineering human cells and viruses to fight cancer. Over a single career, we have gone from a therapeutic arsenal of cytotoxic medicines to one that includes targeted agents such as monoclonal antibodies and “living drugs” comprised of human cells and viruses. Yet we are still in the early days of the immunotherapy revolution. There are more great things to come.
Great to hear some optimism about precision oncology! Lately, I've stumbled across a lot of criticism. At some point, I was planning on putting together a rebuttal of a number of the critiques that are circulating in public discourse. Fortunately, most of the criticism is not emerging from within the field. I do hope we find a way to speed up progress.
Stetson, I am trying to figure out the basis for criticism of precision oncology. Surely we aren't better off using the same treatment protocols for different patients without considering the characteristics of each patient's cancer. I suspect this criticism that is not
"from within the field" is based on hype and not expertise.
There was a 2023 book by James Tabery called 'Tyranny of the Gene' that immediately comes to mind as an example of the critique I see. The critique, which is borderline conspiratorial, is that "Big Pharma" tricked funding agencies and research science with slick marketing and hype into an over-investment in somatic mutation theory. They argue there's been a relative disinvestment in social and environmental determinants of complex disease because of this. The critique is silly of course.
There are more marginal and reasonable critiques not of precision oncology per se but of the evidentiary standards enforced by the FDA on precision therapeutics, the research practices common to precision oncology trials (few randomized designs, convenient censoring, subpar comparators, etc), and corporate COI issues from voice like Vinay Prasad and Bishal Gyawali. I have my own rejoinders to some of these critiques (i.e. selective requests for rigor and tradeoffs should favor innovation) but ultimately critiques focused on improving research science practices I look upon as beneficial to the overall project.