JPMorgan Conference big shift to oral obesity drugs, AI discovery

At the JPMorgan Healthcare Conference, drugmakers highlighted a major shift in obesity treatment from injectable drugs to easy-to-take oral pills. At the same time, artificial intelligence emerged as a key force in speeding up drug discovery and lowering development costs.

At the 44th JP Morgan Healthcare Conference in San Francisco, drugmakers laid out a clear roadmap for the healthcare sector, with two themes dominating discussions: the mainstreaming of obesity medicines and the rapid rise of artificial intelligence in drug discovery.

Obesity treatments, once considered niche therapies, are now firmly entering the medical mainstream. A key shift highlighted at the conference is the move away from weekly injectable drugs toward daily oral pills, a transition aimed at expanding access beyond specialist clinics and early adopters.

Novo Nordisk pointed to intensifying global competition and said that by the end of the decade, more than one in three obesity patients could be using oral weight-loss medicines instead of injections.

Eli Lilly, while reaffirming confidence in its injectable portfolio led by blockbuster drug Mounjaro, showcased its oral GLP-1 candidate, orforglipron. The company positioned the pill as both a potential maintenance therapy after injectable-led weight loss and a convenient alternative for patients preferring oral treatment. Lilly is expected to seek US Food and Drug Administration approval for the drug in 2026. Unlike earlier oral GLP-1 therapies, orforglipron does not require strict timing around meals, which the company says could improve patient adherence.

Drugmakers are also increasingly framing GLP-1 therapies as long-term cardiometabolic treatments, emphasising benefits beyond weight loss, including improved heart health and reduced risks linked to diabetes and metabolic diseases.

Artificial intelligence emerged as the second major focus of the conference. AI is now being embedded as core infrastructure across drug development pipelines, moving beyond pilot projects to real-world deployment. A key example is the $1-billion joint AI drug-discovery initiative between Nvidia and Eli Lilly, aimed at compressing research timelines and reshaping how new medicines are identified and developed.

The industry’s emphasis is shifting toward advanced computing, automation and data-driven models to accelerate molecular design, testing and clinical development at scale.