A Gentle Introduction to Optimal Design for Pharmacometric Models

Speaker: Tim Waterhouse, Metrum Research Group
Sponsored by the Statistics and Pharmacometrics Special Interest Group for ASA and ISoP: sxpsig.github.io/
Abstract:
PK/PD studies should be designed in such a way that the model parameters will be estimated with adequate precision and bias. This can be assessed by simulation, but depending on the study and model(s) involved, it can be impractical to evaluate many combinations of design variables. Optimal design tools allow us to quickly evaluate designs and even search over a design space for the best possible design.
In this webinar, we will introduce basic concepts of optimal design, and then present examples of how to inform PK sampling time selection using the freely-available R packages PopED and PFIM for optimal design and mrgsolve for simulation.
Chapters
• 0:00: SxP Introduction
• 4:02: What is Optimal Design?
• 6:57: Optimal Design Background
• 14:50: Tools for optimal design.
• 16:40: PopED for optimal design
• 35:26: PFIM for optimal design
• 40:02: ODE PK model example using mrgsolve with PopED and PFIM
• 48:45: Wrap-up