#307 - It Took Months to Interpret His Genome. Claude Did It in 30 Minutes. | Dr. Euan Ashley + Mike Haney

10 snips

Aug 20, 2026

Dr. Euan Ashley, Stanford medicine chair and author who led one of the first clinical genome interpretations. He recounts early genome interpretation and how AI replicated months of work in minutes. He explores the rise of multi-omics, wearables, and the need for better reference datasets. He discusses practical barriers to scaling personalized medicine and the promise and pitfalls of AI in healthcare.

Ask episode

AI Snips

Chapters

Transcript

Episode notes

ANECDOTE

The First Clinical Interpretation Began With A Colleague's Hard Drive

Steve Quake walked into clinic with his whole genome on a hard drive and a suspicious variant, turning a science meeting into a clinical consultation.
Euan Ashley built a months-long pipeline to interpret 6 billion genomic data points in the context of family history and clinical tests.

ANECDOTE

AI Recreated A 15-Year-Old Genome Analysis In 30 Minutes

Claude reproduced the lab's 15-year-old clinical genome analysis in about 30 minutes and for roughly five dollars of cloud tokens.
Euan Ashley uploaded his old variant call file, prompted Claude ~200 words, and it matched most key findings from the original months-long team effort.

INSIGHT

Genomic Medicine Needs A Diverse PanReference

Early genomic references lacked global diversity and created clinical blind spots, so a pan-reference or graph-based reference is needed for medical-grade sequencing.
Euan Ashley argues for deploying diverse, structured references and clinical-grade standards for complex genes and repeat regions.

Get the Snipd Podcast app to discover more snips from this episode

Get the app

Twenty-five years ago, sequencing the human genome seemed poised to usher in an era of personalized medicine. Dr. Euan Ashley helped turn that promise into an actual clinical experiment, leading one of the first efforts to interpret an entire human genome in the context of a real patient’s health. The challenge quickly became apparent: medicine could suddenly generate billions of data points about one person, but making sense of them was painfully slow.

That history feels newly relevant. Ashley recently gave an AI system his own 15-year-old genome data and watched it reproduce most of an analysis that had originally required months of work by a team, in about 30 minutes. Meanwhile, genomics is being joined by wearables, multi-omics, and other technologies capable of tracking far more of our biology over time.

In this episode of NextLevel, we use the genome revolution as a case study for what happens when our ability to measure the body advances faster than our ability to interpret and use the information. The next leap in personalized medicine may depend less on collecting another mountain of data than on building the tools, reference datasets, and healthcare systems capable of turning that information into decisions.

Free course: Improve your metabolic health

Get our free email course on how glucose, nutrition, exercise, sleep, and measurement can help you build habits that support better energy and long-term health: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://levels.link/wnl⁠

🎙️ About the Guest:

Dr. Euan Ashley is Chair of the Department of Medicine at Stanford University and the Roger and Joelle Burnell Professor of Genomics and Precision Health, with appointments in medicine, genetics, and biomedical data science. He’s also the author of The Genome Odyssey: Medical Mysteries and the Incredible Quest to Solve Them.

📍What Dr. Euan Ashley & Mike Haney discussed:

03:33 What happened to the promise of personalized medicine?
06:33 The first clinical interpretation of a human genome
11:26 AI interprets in 30 minutes what once took months
21:25 Why genomics still needs better, more diverse reference data
27:41 Building a molecular map of exercise with MoTrPAC
32:01 Exercise changed nearly every organ researchers measured
39:05 Why your personal baseline can matter more than a "normal" range
42:46 How wearables opened a new era of longitudinal health data
47:48 The biggest barrier to continuous, personalized healthcare
51:39 What medical AI needs to become genuinely useful
57:05 How AI can ace medical benchmarks for the wrong reasons
58:20 The heart measurement Ashley considers a medical "holy grail"

🔗 Helpful Links:

Clinical Assessment Incorporating a Personal Genome, The Lancet, 2010. Landmark integrated clinical analysis of a complete human genome.
Molecular Transducers of Physical Activity Consortium (MoTrPAC), NIH Common Fund. Large-scale project mapping how exercise changes tissues and organs.
MoTrPAC: Human Studies Design and Protocol, Journal of Applied Physiology, 2024. Human study of molecular responses to endurance and resistance training.
The Mitochondrial Multi-Omic Response to Exercise Training Across Rat Tissues, Cell Metabolism, 2024. MoTrPAC study on molecular changes across organs after exercise.
Harmonizing Standards and Resources for the Medical Genome, Nature, 2026. Ashley et al. on genomic reference standards and clinical-grade sequencing.

Watch the conversation: https://youtu.be/bD2YVGdwviE

Find us on YouTube: ⁠⁠⁠⁠⁠https://youtube.com/levelshealth?sub_confirmation=1⁠⁠⁠⁠

👋 Who we are:

Levels helps you understand your metabolic health with personalized data, expert guidance, and tools that connect your daily choices to measurable changes in your body. Our goal is to help you make better decisions about food, exercise, sleep, and long-term health.

Look for new shows every month on A Whole New Level, where we have in-depth conversations with thought leaders about metabolic health.