Kevin Trimm, Kyle Wathen

Traditional trial design approaches often rely on average pharmacokinetic and pharmacodynamic (PK/PD) assumptions to predict treatment response. While useful, these averages may not capture important patient-level differences in exposure, disease characteristics, pathogen susceptibility, or treatment response. As a result, a trial may be designed with too many or too few patients to achieve its intended objectives.

How can incorporating patient-level PK/PD variability lead to more informed and efficient trial design decisions?

Join this webinar for a practical demonstration of how individualized PK/PD modeling can be incorporated into a clinical trial design workflow, using Cytel’s East Horizon™ platform. Through a virtual patient population and a generic treatment example, we will compare trial simulations based on average PK/PD assumptions with those accounting for patient-level variability, highlighting differences in expected treatment response, uncertainty, and sample-size requirements.

Key Topics

• Why average PK/PD assumptions may not fully capture patient-level differences that influence treatment response.
• How individualized PK/PD modeling can be incorporated into clinical trial simulations.
• How average and individualized PK/PD approaches can produce different expectations for treatment response, uncertainty, and sample-size requirements.
• How to apply individualized PK/PD modeling in practice, with code examples illustrating its implementation in East Horizon and its potential to support more informative and efficient trial designs.

Moderator

Kevin Trimm – Chief Product Officer, Cytel

Speakers

Kyle Wathen – Vice President, Scientific Strategy & Innovation, Cytel

Nathan Teuscher, PhD – President and Founder, Aplos Analytics