Sebastian Schneeweiss, MD, ScD, professor of medicine and epidemiology, Harvard Medical School and Brigham and Women's Hospital, and co-founder of Aetion, discusses current use of rapid-cycle analytics and what efforts are needed to improve understanding and uptake.
Sebastian Schneeweiss, MD, ScD, professor of medicine and epidemiology, Harvard Medical School and Brigham and Women's Hospital, and co-founder of Aetion, discusses current use of rapid-cycle analytics and what efforts are needed to improve understanding and uptake.
Is rapid-cycle analytics currently used regularly? Or is greater uptake needed?
I think greater uptake is definitely needed. As you know, there is this large initiative for real-world evidence by the FDA to see to what extent these types of data can be used to demonstrate the effectiveness. With the traditional approaches of line programming, you will only go so far with regard to scalability. How many of those studies can you do per year? Can you really wait 9 months or 12 months until you have the findings of the study? And, the advantages of platforms to be fast, to be scalable, to be transparent, and to be scientifically validated, speaks for itself, I think. When I go to conferences, I always make a point to make the prognosis that in 5 years time, 50% to 60% of all analyses will be done with rapid cycle analytics platforms.
What efforts are needed in order to improve understanding and uptake of rapid cycle analytics?
To increase the uptake of these platforms, the stakeholders need to see the benefit of these platforms, which is why we are doing demonstration projects with payer organizations, we are doing a demonstration project with the FDA, we are doing demonstrations with pharma clients in order to show the value of this rapid cycle analytics platform. Once people have seen the platforms, they are in awe, and they don’t want to go back anymore to line programming. So, we are at the beginning of a wave, I think, where as I said, my prognosis is in 5 years the road will look very different with regard to real-world evidence, and the majority of analyses will be done with platforms like that because the advantages are so obvious.
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