For years, we’ve treated chronic inflammation, allergies, autoimmune disease, and immune dysfunction as separate problems. But it’s becoming clearer that many of these conditions share a common root hiding in plain sight: the gut microbiome.

We now understand that the microbes living inside us shape immune tolerance, inflammation, and long-term disease risk, and even how well medications work.

But despite hundreds of thousands of microbiome studies, most clinicians and patients are still operating in the dark. Because the microbiome isn’t just complex; it’s too complex for the human brain alone.

No clinician can synthesize hundreds of thousands of studies, track millions of microbial data points, and simultaneously account for diet, fiber, sleep, stress, exercise, antibiotics, and immune signaling. That’s where AI-driven platforms like Jona come in.

It can now analyze massive microbiome datasets across hundreds of thousands of studies, and translate that complexity into individualized, actionable insight. We can use it to detect immune-risk patterns early and model lifestyle interventions before they’re ever implemented.

How can we use AI to detect immune-risk patterns early and model lifestyle interventions before they’re ever implemented? How might AI change the way we diagnose and test for immune dysfunction, long before disease becomes obvious?

What happens when microbiome data and AI-guided lifestyle interventions start working together, instead of in isolation?

In this episode, I’m joined by medical AI pioneer and founder of Jona Health, Dr. Leo Grady. He has spent decades building machine-learning systems for medicine and is now applying that same rigor to the gut microbiome.

We talk about how his platform reads the entire body of microbiome science, detects immune-risk signatures before symptoms ever appear, and simulates lifestyle interventions before a person makes a single change.

Things You’ll Learn In This Episode

The microbiome may shape immune destiny

Most immune-related conditions show distinct microbial patterns long before symptoms appear. If we can see immune risk early, why are we still waiting to intervene?

AI turns lifestyle advice into precision medicine

Diet, fiber, exercise, sleep, stress, and supplements all change the microbiome, but not in the same way for everyone. How does Jona allow people to test interventions virtually before trying them in real life?

More probiotics aren’t always better

Some microbes have a “sweet spot,” not a simple more-is-better rule. How often are well-meaning supplements pushing people in the wrong direction?

The future of prevention may start in the gut, not the clinic

From allergies to biologics to chronic disease management, the microbiome may soon guide treatment selection itself. Will AI-powered gut testing become as routine as blood work?

Guest Bio

Leo Grady, PhD, is the founder and CEO of Jona, a health technology company that utilizes artificial intelligence to analyze the gut microbiome and provide personalized health insights. Leo is an internationally recognized AI and healthcare innovator with over 20 years of experience, known for leading the development of FDA-approved AI technologies in pathology, cardiology, radiology, and now spearheading microbiome-based health solutions at Jona. To learn more, visit jona.health and follow @jonahealth.

About Your Host

Hosted by Dr. Deepa Grandon, MD, MBA, a triple board-certified physician with over 23 years of experience working as a Physician Consultant for influential organizations worldwide. Dr. Grandon is the founder of Transformational Life Consulting (TLC) and an outspoken faith-based leader in evidence-based lifestyle medicine.

Disclaimer

​​TLC is presenting this podcast as a form of information sharing only. It is not medical advice or intended to replace the judgment of a licensed physician. TLC is not responsible for any claims related to procedures, professionals, products, or methods discussed in the podcast, and it does not approve or endorse any products, professionals, services, or methods that might be referenced.