Former OpenAI Exec Fidji Simo Launches ChronicleBio to Tackle POTS and Chronic Diseases Using AI-Driven Subtyping
核心洞察
Fidji Simo, former OpenAI (搜索) executive, founded ChronicleBio (搜索) to identify biological sub-diseases within conditions like POTS (搜索), aiming to improve clinical trial success rates.
The startup has collected over 3,500 blood samples and 153 terabytes of data, already identifying five distinct biological subtypes within POTS (搜索).
ChronicleBio (搜索) will launch mobile phlebotomy services on August 11, offering free advanced blood testing to the first 250 patients to expand its biobank.
Fidji Simo, the former OpenAI (搜索) executive who stepped down from her role as CEO of AGI deployment to focus on her health, is now channeling her experience with chronic illness into a bold new venture: ChronicleBio (搜索), a startup using artificial intelligence to decode the underlying biology of complex chronic diseases like postural orthostatic tachycardia syndrome (POTS (搜索)).
In her first interview since departing OpenAI (搜索), Simo revealed that ChronicleBio (搜索) has already identified five distinct biological sub-diseases within POTS (搜索)—a condition for which there is currently no cure. The company's mission is to solve a persistent problem in drug development: clinical trials that fail because pharmaceutical companies cannot identify which subset of patients a drug might actually help.
"We have seen a lot of clinical trials fail because the pharmaceutical companies aren't able to identify which subset of patients [a drug] could work for," Simo said. "So they end up giving the drug to everyone with the same diagnosis. Let's say it's POTS (搜索). But there could actually be five sub-diseases within POTS, and the drug would work for one of them, but not the other four. So the clinical trial fails when it could have succeeded if we could have identified these people upfront."
The biological data gap
ChronicleBio (搜索)'s approach centers on collecting and analyzing deep biological data—something Simo believes is fundamentally missing from current drug discovery efforts. In its first year, the company has performed 890 blood draws from 709 patients across Utah, Arizona, Texas, and India, amassing over 3,500 tubes of blood in its biobank. From these samples, ChronicleBio has extracted 153 terabytes of data—three times the 45 terabytes used to train OpenAI (搜索)'s GPT-3.5 model in 2022.
"Right now, a lot of the models use a lot of EHR data—medical records. But medical records don't tell you enough about biology. They're incredibly noisy. They don't tell you how the human body works," Simo explained. "If you look at LLMs, they work so well because the internet existed, right? You already had all of this language. We are missing the internet of biology."
The company has raised $15 million to date and is using a combination of AI models from OpenAI (搜索) and Anthropic (搜索) to analyze the massive datasets generated from blood samples.
Mobile phlebotomy and patient access
On August 11, ChronicleBio (搜索) will launch a sign-up link for mobile phlebotomy services, sending trucks to the homes of people with certain chronic diseases. The first 250 participants will receive an in-depth report on their condition at no cost. After that, the service will be priced at $400—what Simo describes as at-cost pricing.
"The whole point for us is not to make money. It's to collect data so we can find cures," she said.
The home-based model is designed to reach patients who are bedridden or in the sickest stages of disease—individuals who are often excluded from traditional clinical research. Participants will receive detailed reports on their biological data and ongoing updates as ChronicleBio (搜索) makes new findings about disease subtypes.
The urgency of chronic disease
Simo, who was diagnosed with POTS (搜索) in 2019, described her current physical state as "the worst I've ever been." POTS causes dizziness upon standing, fatigue, brain fog, headaches, and other symptoms due to an imbalance in the body's autonomic nervous system. She noted that chronic conditions are "becoming a real epidemic," with "hundreds of billions in lost productivity."
She pointed to the stark disparity in research funding for conditions like chronic fatigue syndrome (搜索), which she described as "considered the most disabling disease of all diseases" yet receives disproportionately little funding—a gap she attributes partly to the fact that these conditions primarily affect women and rarely cause death, despite causing severe disability.
"It seems impossible that with the tools we have today, we would continue to conclude that diseases are incurable and that patients should be in a dark room for years," Simo said. "We owe them something better, given the progress that we're seeing in a lot of disciplines."
AI as the enabling technology
Simo emphasized that the multisystem nature of complex chronic diseases—involving the nervous system, immune system, and genetics—creates a data problem that was previously intractable without AI. "Analyzing 150 terabytes of data would have been either impossible or would have taken years, and now it takes us minutes," she said.
ChronicleBio (搜索) plans to begin testing existing drugs on its patient populations before the end of the year, mapping the biological subtypes it has identified to drugs that could address the underlying mechanisms. The company then intends to partner with biotech and pharmaceutical companies to develop new therapeutics.
"When I was at OpenAI (搜索), I said, 'I think if AI accomplishes everything but doesn't cure disease, that would be a very sad state of affairs,'" Simo reflected. "The real promise of AI has always been to cure disease. I think it would be a tragedy if we had all of these amazing tools in our hands, but weren't able to turn them into drugs that can save patients' lives on a time frame that matters."