In a recent episode of The Genetics Podcast, Patrick Short sits down with Dr. Euan Ashley, Chair of Medicine at Stanford University, author of The Genome Odyssey, and co-founder of various biotech companies. Euan’s work ranges across ultra-rapid genome sequencing, generative AI for drug development, and even the molecular basis of elite athletic performance.
During their wide-ranging conversation, Patrick and Euan dive into stories that show just how far clinical genomics has come, and where it’s heading next.
Saving a newborn’s life with genome sequencing
Euan recalls a defining moment early in his clinical genomics career when a critically ill newborn was suffering repeated cardiac arrests just days after birth. Doctors suspected long QT syndrome, but hadn't been able to identify subtype, and time was running out.
Working with Illumina, Euan’s team sequenced the baby’s genome and rapidly interpreted the data. They found a potassium channel mutation and used that information to tailor treatment, saving her life. That baby is now a healthy seven-year-old.
Being able to identify the molecular basis and deliver precision medicine at the bedside within days of life changed the way his team thought about what genome sequencing could do in practice.
Whole genome sequencing in under 8 hours
This early case sparked a bigger ambition: figuring out how to scale ultra-rapid genome sequencing to help many more patients. Working with Oxford Nanopore, Euan’s team developed a workflow that can deliver results from whole genome sequencing and a diagnosis in under eight hours, fast enough to influence treatment decisions in a single hospital shift.
This involved combining high-speed sequencing on Nanopore’s PromethION, cloud-based data pipelines, and GPU-optimised tools developed in-house. The entire software stack was built to move data seamlessly to the cloud and intelligently match computing resources to each algorithm’s needs.
The result didn't only set a Guinness world record, it was also a repeatable, open-source approach that has since been applied in neonatal intensive care units (NICUs) around the world.
From newborn screening to lifelong care
Euan is equally interested in population-level screening, starting at birth. He sees whole genome sequencing as a natural evolution of today’s newborn tests.
What’s changed is our ability to interpret the data responsibly. With better tools, variant databases, and clearer frameworks around what to return and when, clinicians are better equipped to help families make informed choices.
Euan believes this could lay the groundwork for preventive care across the lifespan, with individuals choosing when and how to access their own genetic information.
A call for new models and better incentives
Despite these scientific advances, there are still significant barriers to widespread accessibility to genetic sequencing. In the US, a fragmented healthcare system and short-term thinking make it difficult for payers to justify long-term investment in genomics. Currently, most individuals change insurance providers too frequently for preventive strategies to be financially lucrative for any one organization.
In more integrated systems like the NHS in the UK, the return on early sequencing is easier to track. As cost continues to drop and sequencing becomes more accessible, Euan sees a growing opportunity to integrate it into newborn care, with an evolved version of traditional screening that can be expanded into long-term health insights.
AI, wearables, and digital phenotyping
As a cardiologist, Euan is also interested in how AI and wearable technology can be used to prevent heart disease. Devices like the Apple Watch can already detect atrial fibrillation passively, offering the potential to prevent strokes before they happen. Euan is exploring how data from wearables can be integrated with clinical genomics and other health data to create more proactive, personalized approaches to cardiovascular care.
He’s also part of major efforts to understand how physical activity reshapes human biology at the molecular level, as in the NIH-funded MoTr-PAC study.
Sequencing the world’s fittest people
Another active project in Euan’s lab is the ELITE study: a genomic investigation into elite endurance athletes. Inspired by athletes like Eero Mäntyranta, the Finnish skier who had a mutation that boosted his red blood cell count, the study focuses on athletes with exceptionally high VO₂ max scores.
The aim is to learn from the outliers, not just to understand what makes them elite, but also to uncover biological insights that could benefit everyone.
Participants are being recruited globally, and selection is now open to those who meet performance thresholds or provide validated data from wearables or race results.
Generative AI for gene and drug design
If he were starting from scratch today, Euan says he’d build a lab around generative AI. Not for writing text, but for designing proteins, gene therapies, and delivery systems.
His lab is already combining wet lab tissue models with AI-based design tools to explore new ways of delivering gene-based therapies. By iterating between experimentation and model training, they’re creating a powerful feedback loop that could accelerate drug discovery in rare disease and beyond.
Listen now:
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