The Dr. Hyman Show: “How OpenAI Is Helping People Take Control of Their Health”

Guest: Fidji Simo, CEO of Applications at OpenAI
Date: February 4, 2026
Host: Dr. Mark Hyman

Episode Overview

In this episode, Dr. Mark Hyman sits down with Fidji Simo, CEO of Applications at OpenAI and founder of Chronicle Bio, to discuss how artificial intelligence—particularly ChatGPT Health—is helping individuals understand and manage their health like never before. Both share their personal struggles with chronic illness, discuss the complex failings of the current healthcare system, and explore AI’s transformational potential for patients, clinicians, and health research. They address the critical importance of connecting siloed health data, empowering individuals, and democratizing access to medical insights.

Key Themes and Discussion Points

1. Personal Health Journeys and Systemic Challenges

• Both Dr. Hyman and Fidji Simo share stories of chronic illness, frustration with conventional medicine, and the lack of integrated diagnosis.
  • Simo’s experience: Sudden health decline after pregnancy, escalation post-endometriosis surgery, ultimately diagnosed with POTS (Postural Orthostatic Tachycardia Syndrome) and chronic fatigue. ([05:25])
  • Recurrent issue: Multiple doctors, each focused narrowly on one system, missing the bigger picture.
  • Dr. Hyman: Passed through elite medical centers with chronic fatigue (due to mercury toxicity), repeatedly told "it’s just stress," before uncovering the root cause himself. ([06:55])

“I saw 20 specialists, everyone looking at just like one particular symptom... But if you look at my disease, it's a mix of immune dysregulation, nervous system dysregulation... But meanwhile you have the GI doctor that's just focused on your GI symptoms, and cardiologist who's just thinking that your heart rate is fast, but not really connecting that...”
—Fidji Simo ([09:41])

• Root Cause Medicine:
  • Both discuss the fundamental concept that medicine is too reductionist, focusing on labels and organs rather than the body as a networked, dynamic system.
  • AI is uniquely capable of integrating complex, multifaceted data.

2. The Promise and Power of AI & ChatGPT Health

• Why OpenAI started with health:
  • 230 million people a week use ChatGPT for health concerns.
  • Enormous untapped potential as individuals are already using these tools to bridge gaps in traditional care. ([24:03])

“When we saw that… we hadn't really done anything super specific for healthcare on the product side… we realized actually there is a lot to do…”
—Fidji Simo ([24:03])

• How Simo uses ChatGPT personally:
  • Aggregates all her health data (medical records, genome, wearables, etc.) into ChatGPT.
  • Gains insights, pattern recognition, and even daily summaries of relevant new studies or untried therapies ([13:35]).
  • Real-world example: Avoided a dangerous antibiotic due to AI alert about past C. diff infection—information her care team didn’t have time to connect ([13:35], [16:15]).

“One of the most important decisions of my life would have been kind of messed up if it wasn't for AI helping connect the dots.”
—Fidji Simo ([13:35])

• Personalized and Proactive Health Recommendations:
  • AI identifies actionable advice based on genome, lifestyle data, and past history (e.g. which B vitamins are needed, how sleep influences HRV and symptoms) ([18:23]).
  • Allows for a truly “personalized health agent”—an unmet promise in conventional personalized medicine.

“Your personalized health agent gets to know you better than anyone else and can really do true personalized advice, which was the promise of personalized medicine. But again, we didn't get there.”
—Fidji Simo ([18:23])

3. Data Integration & Partnerships

• Collaborations with Platforms Like Function Health, Apple Health, and Instacart:
  • Function Health: Upload labs, genomics, wearable data, and medical records into ChatGPT for deeper insights ([11:33], [28:18]).
  • Instacart integration: Connects AI-driven dietary advice directly to grocery delivery, closing the loop between knowing and acting ([28:18], [31:07]).
  • Focus: Making “the full picture” of health accessible, actionable, and easy for users.

“With a partner like Instacart, you can go from, okay, this is what you should be eating to like in one tap order that and it's at your door in an hour. And like, that's a magical closing of the loop…”
—Fidji Simo ([28:18])

4. Broader Impact: Democratizing and Decentralizing Health

• Accessibility:
  • Simo emphasizes that 7 out of 10 ChatGPT health queries occur after hours—a testament to unmet needs, especially in rural areas ([44:10]).
  • ChatGPT Health is available in the free tier, making advanced health insights accessible to everyone ([46:04]).

“…Direct access to, to health information that I think is going to really democratize just, you know, health knowledge in general.”
—Fidji Simo ([44:10])

• Provider Support:
  • OpenAI for Healthcare partnership: Large institutions deploying ChatGPT to assist doctors, streamline administrative work, and inform clinical decisions ([34:38]).
  • AI as a tool to reduce physician burnout, allowing clinicians to focus on thinking and patient engagement—not data wrangling ([60:34]).

5. The Future of AI in Medicine

• Whole-body, Network-focused, and Data-Driven:
  • Transition from “sick care” to continuous, proactive, preventive, and personalized health management ([26:20]).
  • Acceleration of discovery: Faster subtyping of diseases, identification of effective therapies for “incurable” diseases, and individualized recommendations ([34:38], [40:44]).

“That was the impetus behind [Chronicle Bio]. We realized we're not going to find cures for long Covid overall because long Covid is probably 20 biological processes under that... So what we decided to do was actually create the company that partners with clinics to get biological data from patients and analyze everything…”
—Fidji Simo ([40:44])

6. The Laws of Biology & Systems Medicine

• From Labels to Mechanisms:
  • Hyman and Simo agree we need to move beyond “knowing the name of your disease” to understanding causes and mechanisms ([42:35], [52:41]).
  • Using AI and big data to find root causes, subtypes, and optimal interventions, not just symptom management.

“You might say, well, maybe evolution, but there wouldn't be a set of laws that you could say, here's the laws of human biology and human disease. We don't have that... Now with AI… that’s what we’ve done is really try to understand what are the fundamental systems in the body that can explain everything.”
—Dr. Mark Hyman ([52:41])

Notable Quotes & Moments (with Timestamps)

• Fidji Simo on the challenge of fragmented care:

  “I ended up hiring a teaching assistant at Stanford to teach me genetics… I'm like, that's crazy. Who has the resources and the time to do that?” ([09:41])

• On the empowering effect of AI:

  “With ChatGPT, you can have literally a health coach... have that kind of assistant to really help you with your health every day, not just when you're sick, not just when you're seeing the doctor, that's really what gives me hope…”
  —Fidji Simo ([24:03])

• On the transformation provided by integrating data:

  “It's connecting all of the data about me in one place so that it can be analyzed... I was blown away because I'd seen 20 doctors, but not a single one of them had looked at the whole picture…”
  —Fidji Simo ([13:35])

• On the shortcomings of current genetic medicine:

  “It doesn't happen, right? It has happened in cancer. But like for your day-to-day care for a regular chronic illness, your doctor is not analyzing your whole genome and telling you to change your nutrition based on your genome…”
  —Fidji Simo ([18:23])

• On the convergence of technology and true prevention:

  “...It's going to allow better patient care, better connection, more streamlike efficiencies. But, more importantly, I think it's gonna, it's gonna shift the paradigm to where we're really going to... unlock a lot of understanding of human biology and so much suffering for people like you and for people like me who had to deal with stuff that didn't have answers.”
  —Dr. Mark Hyman ([60:34])

Vision for the Near Future

• In 1–5 years:
  • Widespread, proactive, AI-driven health coaching integrated into daily life ([61:45]).
  • Seamless aggregation and analysis of personal data, empowering individuals to optimize health before disease arises.
  • Streamlined, doctor-patient interactions with rich pre-visit insights and shared data—a better, more efficient, humanized healthcare system.

Immediate Next Steps

• Individuals: Start collecting and integrating your own data sets; use tools like ChatGPT Health and Function Health to extract insights.
• Providers: Embrace AI as an aid, not a threat—leverage time savings and pattern-finding power to improve care and reduce burnout.
• Researchers & Innovators: Use aggregated “real-world” big data to subtype conditions, find new therapeutic targets, and democratize discoveries.

Takeaways

• AI is the key to unlocking siloed health data and moving from organ-focused, reactive “sick care” to proactive, network-based, personalized health.
• Empowerment, accessibility, trust, and partnerships are central: AI brings expert-level insights to everyone, anywhere, and anytime.
• The future is “whole-person health” powered by integrated data, evolving both medicine and self-care at unprecedented speed and scale.

Timestamps for Key Segments

• 00:29 — Simo’s personal story: leveraging ChatGPT to prevent antibiotic complication
• 05:25 — Simo’s chronic illness journey
• 06:55 — Hyman’s chronic fatigue and medical journey
• 09:41 — The fragmentation of traditional healthcare
• 13:35 — How Simo uses ChatGPT for her health (data aggregation, pattern finding)
• 16:15 — Real-life example: ChatGPT alerts to dangerous antibiotic
• 18:23 — Genomic insights & personalized recommendations
• 24:03 — The scale of ChatGPT’s health usage and why OpenAI prioritized health
• 28:18 — The importance of partnerships (Function Health, Instacart)
• 34:38 — The potential for AI to accelerate research & provider support
• 40:44 — Chronicle Bio: Subtyping diseases, solving the "incurables"
• 44:10 — AI’s role in democratizing and decentralizing healthcare access
• 52:41, 57:27 — The need for new “laws” of biology, root causes vs. labels
• 58:24 — Building trust, responsibility, and partnerships in AI health
• 61:45 — Simo’s vision for proactive, personalized, actionable AI health agents

This summary is designed to provide both an in-depth understanding for those who haven't listened to the episode and a quick reference for returning to key discussions.