For decades, BMI has been the most widely used tool for measuring obesity. But recently, the medical community has begun to move away from using it as the main way to measure and define obesity. So in this episode, we’re opening up a nuanced discussion about why this popular tool… was never really built for the job. Why do we still use BMI? What are its limitations? And is there a better way to understand and measure obesity? Host Joe Hanson dives in.

Featured guests:
– Dr. Lisa Tarasenko, Obesity Global Medical Affairs Leader, Pfizer
– Dr. Giles Yeo, Professor of Molecular Neuroendocrinology, University of Cambridge
– Dr. David Cummings, Professor of Medicine, University of Washington, and Founding Director, Weight Management Clinic and Program, Seattle-Tacoma VA System

Dive into the episode here:
00:00 – Wait, what is BMI?
02:58 – Why understanding obesity is crucial
05:05 – The problems with BMI
13:11 – A new definition of obesity

Check out our YouTube channel (@Pfizer) to watch full interviews with Joe & special experts and guests for more on obesity.

Season 7 of Science Will Win is created by Pfizer and hosted by Dr. Joe Hanson. It’s produced by Acast Creative Studios. Hosts in this podcast series were compensated for their time.

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Why do we weigh what we weigh? The answer to that question is surprisingly complicated. On season seven of Pfizer's award-winning podcast Science Will Win, host Joe Hanson, a science storyteller and host of PBS’s Be Smart, explores the cutting-edge research that’s changing the way we think about hunger and weight. Understanding that research means diving into history, genetics, hormones, comorbidities, and real patient experiences. And, just like last season, you can find full length video discussions led by this season’s host on Pfizer’s YouTube channel. Season 7 of Science Will Win is coming soon—subscribe to stay tuned in!

Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Cancer research is moving faster than ever—but too many patients never feel the impact of that progress. Artificial Intelligence (AI) is emerging as one tool that could help change that.

In the Season 6 finale of Science Will Win, Dr. Raven Baxter follows the human journey behind AI in oncology—from the moment of diagnosis to the real‑world barriers that determine access to care.

Along the way, we explore how thoughtfully designed artificial intelligence is reshaping trial design, enrollment, eligibility, and access—helping patients regain agency and bridging the gap between scientific breakthroughs and real‑world cancer care.

As the season concludes, one thing is clear: progress matters most when it reaches the people who need it.

Featured guests:
– Dr. Lionel Kankeu Fonkoua, Medical Oncologist and Translational Researcher, Mayo Clinic
– Jeff Legos, Chief Oncology Officer, Pfizer
– Dr. Ravi Parikh, Medical Oncologist; Director, Human‑Algorithm Collaboration Lab
– Maya R. Said, Founder and CEO, Outcomes4Me

Dive into the episode here:
00:00 – Past episodes introduce us to an emerging tech advancement
04:16 – What is a clinical trial?
07:35 – AI accelerating the pace of oncology
12:42 – Clinical trials and AI: How can it help?
16:17 – A gap between innovation and patient access
19:16 – Maya's story
23:47 – Clinical trials for AI tools
27:54 – Conclusion: building pathways alongside scientific innovation

Check out our YouTube channel (@Pfizer) to watch full interviews between Raven & some of the patients featured.

Season 6 of Science Will Win is created by Pfizer and hosted by Dr. Raven Baxter. It’s produced by Acast Creative Studios. Hosts in this podcast series were compensated for their time.

*The content in this episode is for informational purposes only and does not provide medical advice. Pfizer does not endorse or sponsor third‑party tools referenced. Patients should not use the tools described as a replacement for discussions with a healthcare provider. Patients should consult their healthcare provider regarding medical decisions.

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