What is the next GLP-1? Uncovering healthcare’s next gamechangers

Some innovations don’t just improve an industry, they redefine it. The assembly line made cars widely accessible. Television transformed entertainment and communication. The smartphone put computing power into our hands.

In healthcare, GLP-1 therapies mark a similar turning point. What began as a diabetes treatment now helps with obesity, sleep apnea and more. For patients, GLP-1s can be life-changing. For providers, they offer meaningful clinical and financial impact, as broader use could reduce inpatient growth for type 2 diabetes to just 8% by 2035.

Scalable innovation is more urgent than ever as health systems grapple with financial pressures, declining patient satisfaction and rising affordability concerns. In a decade shaped by GLP-1s, what breakthrough will redefine healthcare next?

And believe it or not, AI is not the only game in town.

Here are three emerging ideas we’re watching.

Three areas that could be the “next GLP-1”

1. Synthetic biology and programmable therapeutics

   While GLP-1s changed the game for metabolic disease, synthetic biology could redefine how we treat a wide range of chronic conditions. Scientists are now exploring ways to program living cells and microbes to deliver therapies from within the body. Think insulin production on demand or highly targeted cancer-fighting agents.

   Specialty drugs, including biologics, gene therapies and cellular treatments, now make up 54% of total U.S. drug spending. These treatments will continue to dominate health system pharmacy budgets, as costs are projected to rise nearly 4% in 2026. As advanced pharmaceuticals gain broader adoption, they will demand sweeping changes. Health systems that don’t evolve their pharmacy infrastructure now risk being caught off guard by therapies that challenge every part of their operating model, from storage and distribution to staffing and scheduling.

2. Care traffic control to improve access and experience

   Think of care navigation platforms as healthcare’s version of air traffic control. Just as air traffic control ensures every plane travels safely and efficiently, these platforms help guide patients to the most appropriate care setting based on clinical urgency, location and insurance status.

   This kind of orchestration directly addresses two pressing challenges: improving access and enhancing the patient experience. Instead of navigating a confusing web of referrals or facing delays, patients receive timely, tailored guidance.

   Consumers are frustrated and acting on it. Half report major dissatisfaction and one in four plan to switch their primary care physician, according to Vizient data. Many are turning to wellness apps, second opinions and DIY care, underscoring the urgent need for navigation platforms that simplify and personalize access.

   Outpatient volumes are projected to increase 18% by 2035. Meeting this demand will require platforms like care traffic control that blend digital tools and team-based care. Intermountain Health and Northeast Georgia Health System are already using smart routing systems and incentivizing navigation outcomes to reduce avoidable ED visits.

   The future lies in automated, intelligent orchestration where consumer-first experiences and operational efficiency are no longer separate goals, but two sides of the same system.

3. Digital twin models for system planning

   In an environment where decisions about capital and labor carry long-term consequences, digital twin technology is becoming a valuable tool for strategic planning. A concept that started in the aerospace and manufacturing industries, a digital twin is essentially a virtual replica of a real-world health system, built from the organization’s clinical and operational data, so it reacts like the actual system would. For example, a hospital might use a digital twin of its emergency department to see how adjusting staffing ratios or patient intake processes would affect wait times and throughput.

   We all know AI is already shaping the future, and when integrated with digital twins, these models become even more accurate by forecasting demand and improving resource allocation. The value here isn’t just theoretical. Inpatient demand is expected to rise 5% overall, driven largely by an aging population with complex comorbidities. With real estate and labor costs escalating, systems can’t afford missteps. Digital twins help ensure every investment, whether in a new outpatient surgery center or expanded post-acute footprint, is guided by data, not guesswork.

What’s at stake and what to do next

GLP-1s didn’t just improve clinical outcomes. They changed the rules of engagement for chronic care. They are giving us a glimpse of what happens when innovation is paired with infrastructure: fewer admissions, better experiences and measurable economic impact.

But health systems can’t afford to wait for lightning to strike twice. Demand is rising across every care setting, especially as the 65+ population grows and chronic conditions multiply. Systems that experiment now will be better positioned to adapt, scale and lead.

The next GLP-1 is coming. It might not be a medication. It might be a model, a platform or a partnership. The question isn’t if it’s coming. It’s whether we’re ready.