Health & Life Sciences Research Tech

Agentic AI is spreading quickly across the research workflow. Even without this new level of autonomy, research automation can make the work seem less intimate for researchers, perhaps diminishing their sense of connection to participants or research tasks. What can this kind of disengagement mean in a domain where the research participants are patients, caregivers, and clinicians making life-affecting decisions?

The platforms built for health and life sciences research are streamlining workflows, and solutions can be as varied as the research contexts. For example, patient community platforms now generate regulatory-grade evidence; decentralized trial infrastructure has become a primary research channel; and AI-powered advisory systems have compressed workflows that once took months. 

AI is now part of almost every vendor pitch, and vendors are more likely to be better at explaining their tech than they are at explaining your practice. Adaptive interviews, agentic research deployment, synthetic control arms, and conversational RWE analytics land differently depending on your therapeutic area, your compliance environment, and what you already have in place. It helps to have the ability to translate your needs into their capabilities and vice versa.

Explore how to adapt it to your workflow as we cover what distinguishes different types of solutions, discuss typical users and use cases, and what kinds of features you can expect now and in the near future.

Who should attend?

• Pharma and biotech insights and market research teams 
• Patient experience and patient advocacy teams 
• Medical affairs and KOL engagement professionals 
• Clinical research and trial operations teams 
• Market access and health economics researchers 
• Research and insights buyers at any stage of evaluation