Sanjay Juneja: Leveraging AI to address Care Gaps and predict outcomes in Oncology
Sanjay Juneja, shared a post on LinkedIn:
“You know, it’s always been a point of stress and uneasiness that the demand and need for cancer education and updates is so…voracious. The fact that a fleeting post on a home screen can result in now…hundreds…of comments months down the line that therapeutic candidacy / management was optimized as a consequence of education updates is, unsettling, to say the least.
The reason I leaned heavily into understanding AI the past two years is because it was the only conceivable ‘lifebuoy’ to help address what social and digital media / newsletters & journals were trying to ‘bandaid’. AI, by two definitions, does two things POWERFULLY well: (1) recognize patterns and (2) predict the future / outcomes, based on said multi-variable pattern analyses. One can imagine, then, the leaps and bounds that can be achieved in oncology–where care gaps and unexplained / hard to predict reasons for responses and lack there of, exist. And that too, in a world where precision therapy–molecular testing, pharmacogenomics, to name a few–broaden the variability explaining said outcomes.
Over the last few months, I have come to appreciate the extraordinary efforts Eric Lefkofsky, Ezra Cohen, Jonathan Ozeran, Chris Scotto DiVetta and several others on the Tempus AI team have been making over the past several years, appreciating this immense possibility. I am deeply grateful that the universe’s wizardry orchestrations have led to me to a true threading of multiple passions–inequities and care gaps, from older trials to geographical and socioeconomic factors; TRUE personalized and precision management plans; and leverage AI and tech to ‘speed up’ our success against the emperor of all maladies–and afforded me an opportunity to assist their mission-driven team as VP of Clinical AI Applications. It’s an exciting time, in medicine, y’all. Beyond grateful to be a part of it.”
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