How CGMs Are Evolving What We Know About Blood Glucose in Metabolic Disease and Everyday Life

Continuous Glucose Monitors (CGMs) were first approved by the FDA nearly 25 years ago, but have seen widespread adoption in the last decade with popular CGM models from leading companies such as Dexcom and Abott. This has also led to discovering the everyday health insights that CGMs can inform beyond diabetes management.

In this episode, we speak to data scientists RJ Elllis, PhD and Robbie Capps, PhD who have gone deep into understanding metabolic patterns in CGM data. RJ and Robbie talk about the benefits of continuous monitoring – where the resolution of data can be 100x over traditional finger-pricking. Robbie jokes that he has the unique qualification of looking at CGM data for almost every day over the last three years.

Together, we discuss the types of insights that are unlocked with CGM data and related trends. We cover the rising applicability in managing Type 2 diabetes, building closed loop systems to deliver insulin, and the journey to artificial pancreas. We also explore what happens with blood glucose when appetite suppression drugs like Ozempic are involved.

Our discussion also takes a philosophical bent. AI and ML systems can learn predictive models of signals like blood glucose in ways that are fundamentally different from how our systems work – “black-box” vs. “explainable” models. Robbie and RJ make a compelling case for why models based on CGM data need to consider everything else that is going on with the person, and why physio-functional models that explain causality may be a better approach when using CGMs in real-world applications.

Mentioned In This Episode:

• RJ Ellis website: https://robjellis.net/index.html 
• Robbie Capps website: https://robcapps.com
• PFun Digital Health website: https://pfun.one

About Our Guests:

RJ Ellis, PhD
RJ has 7+ years healthtech industry experience (Teladoc, Livongo, Omada) and has led projects/teams focused on extracting signals from high-throughput connected monitoring devices. Expertise in biometrics, experimental design, statistical testing, data viz, classical ML, and scientific communication. PhD from Ohio State (Experimental Psychology); postdocs at Harvard Medical School (Neurology) and the National University of Singapore (Computer Science). 

His greatest pr

#autonomoushealth #tech #ai #machinelearning #healthcare

Thank you for listening!
Subscribe here to be notified every time we release new episodes!
You can also find our podcast episodes on YouTube here: https://www.youtube.com/@AutonomousHealth

Learn more at: https://www.autonomoushealth.com/
Come follow us on LinkedIn: https://www.linkedin.com/company/autonomoushealth/
And continue the conversation on Twitter: https://twitter.com/AutonomousHeal

Autonomous Health is...
Produced & Hosted by: Anmol Madan
Edited by: Losa Amara Meru
Marketing: Erin Garcia Miller

About Your Host:
Anmol Madan is an entrepreneur, computer scientist, and executive who has been leading the digital health and AI revolution over the past two decades. Anmol has co-founded or held executive roles at multiple unicorns in the emerging field of digital healthcare; a field which has existed for less than two decades. His professional contributions in the field have received hundreds of millions of dollars in funding from leading VCs, and been featured in such media as CNBC, New York Times, Washington Post, and Wired Magazine. His scientific contributions have been published in dozens of scientific articles in leading computer science and digital health journals, and led to over 30 issued and pending US patents.
...