Predicting Behaviour and Driving Outcomes: How Pharma Can Adapt Indicator-Driven Adherence Models

Join Lynda Brown-Ganzert, CEO of RxPx, Dr. Kathleen Martin-Ginnis and Kenneth S. Noguchi, PhD, Postdoctoral Fellow as they explore how leading and lagging indicators — combined with behavioral science and AI — can reshape patient support and drive better adherence outcomes.

Medication adherence remains one of the most pressing challenges in healthcare, yet traditional metrics often tell us what happened only after the fact.

Leaders from research and industry unpack how leading indicators, behavioral science models like COM-B, and AI-powered tools can transform patient support from reactive to proactive.

Through real patient case studies, they illustrate how personalized interventions can address motivation, capability, and social support to improve outcomes — while keeping patient privacy and collaboration at the center.

This conversation is ideal for pharma professionals across brand, medical affairs, market access, and patient engagement roles who want to understand the next wave of adherence innovation.

What you’ll take away:

  • The difference between lagging indicators (traditional adherence measures) and leading indicators (predictive signals of patient behavior).

  • How the COM-B model (Capability, Opportunity, Motivation – Behavior) helps explain why patients struggle with adherence.

  • Real-world patient case studies that show how AI and peer support can address challenges like motivation gaps or knowledge barriers.

  • The role of AI in creating personalized, privacy-compliant health interventions that scale.

  • How collaborative research and technology can accelerate innovation in patient support.

 

Watch as industry and research leaders explore how pharma can shift from lagging, retrospective adherence measures to leading indicators that predict behaviour before patients fall off track.

Watch the full video now.

Fill out the form below to receive the video in your inbox!