#1 The dawn of patient autonomy

“Give us our damn data,” urged Dave deBronkart – also known as e-patient Dave – during his powerful opening plenary talk on the transformative trend towards patient autonomy. This movement, driven by advancements in digital tools and AI, empowers patients to take control of their health, make informed decisions, and manage their care more effectively.

The session opened with a powerful analogy to the Reformation, highlighting how technological breakthroughs, like the printing press then and AI now, can revolutionise access to information. deBronkart, a cancer survivor himself, shared how being an empowered, informed patient helped save his life, emphasising the potential of patient autonomy.

A key example of this empowerment is the use of AI tools like ChatGPT to interpret medical information. To demonstrate, deBronkart showed how pasting a doctor’s notes into GPT transformed complex medical jargon into clear, actionable items. “It makes it easier for me to understand what I need to do,” he explained.

Empowerment, as deBronkart detailed, involves removing constraints and providing resources and social permission. But, while key voices in the industry have been quick to caution against the idea of giving patients access to GenAI and health data more broadly, citing a variety of hypothetical safety and process issues, for deBronkart, patients in the real world are already showcasing the vast potential of AI-powered patient autonomy.

To illustrate this, deBronkart highlighted two key examples. In the first, a father of two children with rare diseases, having recognised the disconnect of information between the children’s different medical specialists, used a GPT to organise and interpret their medical data, providing a unified view that even their doctors’ systems lack. In the second example, after a young man’s father developed a rash, and was hit with the unpleasant reality of waiting months to see a dermatologist for diagnosis and treatment, with few other options available, the man turned to a GPT, for a differential diagnosis, using photos. After a few moments, the GPT was able to supply a table of potential diagnoses, complete with clinical reasoning and action items.

“Notice, he was not ditching the doctors,” said deBronkart. “He was exploring to try to understand what they could do while they waited for the doctor. In 10 days, the rash started improving.

As deBronkart argued, by leveraging AI and digital tools, patients can take proactive steps in their healthcare journey, reducing the burden on the healthcare system and improving outcomes.

“Patient autonomy is the freedom to pursue our health goals on our own terms, even beyond the clinic,” he concluded. “The freedom to keep at it, to persist, to keep asking and inquiring, seeking more and better answers for our own self-defined wants and needs.”

#2 Machine learning feels the rhythm

The human heart holds secrets – microscopic electrical whispers that can signal impending danger long before a patient feels a single symptom. The stark reality is brutal: nearly 23% of atrial fibrillation cases remain hidden from view, silently escalating the risk of catastrophic events like strokes. Traditional monitoring has been a game of medical catch-up, but now, a machine-learning-powered approach to healthcare is learning to listen.

In a joint presentation, corporate chief medical officer for EVERSANA, Dr Pierantonio Russo, and senior director of value and access transformation at iRhythm Technologies, Brent Wright, shared how researchers are deploying machine learning algorithms that can detect cardiac risks with precision. These aren’t broad predictions, but laser-focused insights that can identify potential arrhythmias up to six months before they manifest.

“The current process for a patient is: they feel a symptom, go to their primary care or GP. That primary care GP has to agree with the symptoms and make a determination of what happens next,” said Dr Russo. “They may or may not be referred to cardiology; they may or may not be monitored. That “may or may not” is way too much.

“The way people get determined on if you’re going to get monitored to determine if you have an arrhythmia is broken,” he continued. “We truly believe that using big data tokenisation – so matching data sets – we can now predict arrhythmias in patients that are asymptomatic at a high enough rate that it’s cost-effective.”

Using iRhythm’s FDA-approved 14-day patch and EVERSANA’s machine-learning capabilities, researchers could analyse complex patient data from diabetes and COPD patients. These algorithms enabled clinicians to pinpoint individuals at the highest risk before the first warning bell sounds.

“The more we work with this, the better we get, the more predictive the model will get, and the better it’ll learn,” explained Russo. “We’ll be able to now go into large data sets, work with large payers, health systems and say, ‘Hey, these are your high-risk patients’.”

#3 The code with your capsule: Medicine’s digital metamorphosis

One of the most exciting developments discussed at this year’s Frontiers Health event was the intersection of medication and software, leading to the creation of combination products. It is an innovative approach, which, according to Click Therapeutics’ CEO and founder, David Benshoof Klein, aims to enhance the efficacy and safety of traditional pharmacotherapies by integrating them with digital therapeutics.

In his presentation, Klein highlighted the significant potential of combining drugs with software to create new dosage forms, termed “software-enhanced drugs.” This concept involves using robustly validated digital therapeutics alongside traditional medications to provide additional clinical benefits.

“We believe that soon many drugs will have these new dosage forms that combine robustly validated digital therapeutics with traditional pharmacotherapy,” he explained.

Take migraines – he noted – a condition that has long challenged simple treatments. With software-enhanced drugs, researchers have developed innovative approaches that don’t just suppress symptoms, but adapt to individual patient patterns. Furthermore, clinical data reveals promising results with patients experiencing significant reductions in monthly migraine days.

“The average patient in the intervention group went from 7.5 monthly migraine days to about 4.5,” said Klein, highlighting the life-changing potential of this combination of a migraine drug and a digital therapeutic.

Regulatory bodies are supporting this innovative wave. New FDA guidance on prescription drug use-related software clarifies the pathway for these innovative treatments, allowing the added benefits of software to be included directly on the drug label.

“This guidance demonstrates that regulatory bodies see the potential of these new treatments,” noted Klein.

#4 Introducing a “Google Maps” for diabetes management

Managing diabetes is a complex, full-time job. Tracking glucose, meals, exercise, and overall wellness requires constant attention – and daily life rarely cooperates perfectly. It’s a huge task for one person. But, as Welldoc’s Anand Iyer explained, AI-powered solutions can help to alleviate the burden on patients.

Welldoc’s system, he said, acts like a personal health navigator, which supports patients by analysing their health data and providing actionable insights. As Iyer explained, “If we could support the patient at the point of care through AI coaching, they enter a blood pressure value, a glucose value, how much insulin they took, if you could actually coach them in real-time at that point of care and tell them what to do… let them stand on AI shoulders and maybe reach further, can they better manage the disease?”

This AI-driven approach allows for continuous monitoring and personalised guidance, akin to having what Iyer calls a “Google Maps for a patient”. Moreover, he highlighted the importance of integrating AI with existing healthcare systems to enhance the overall care landscape for not just diabetes patients, but all patients.

“We actually have an opportunity to transform the entire care continuum, right? Whether it’s prevention, whether it’s treatment management or even acute care,” he said.