Activity Number:
|
246
- New Mothods for Biomedical and Genetics Data
|
Type:
|
Contributed
|
Date/Time:
|
Monday, July 30, 2018 : 2:00 PM to 3:50 PM
|
Sponsor:
|
Section on Statistics in Genomics and Genetics
|
Abstract #329887
|
Presentation
|
Title:
|
Mechanistic Model Based Simulation for Dosing Regimen Optimization
|
Author(s):
|
Siyan Xu* and Yu-Yun Ho and Wenping Wang
|
Companies:
|
Novartis Institutes for Biomedical Research, Inc and Novartis Pharmaceuticals Corporation and Novartis Pharmaceuticals Corporation
|
Keywords:
|
Dosing regimen optimization;
Simulation;
RxODE;
Mechanistic model
|
Abstract:
|
Mechanistic model based simulations are increasingly employed to optimize dosing regimen in all phases of drug development. A drug was developed for disease X at first, also shows benefit for disease Y. A following question is how to identify a dosing regimen for a Phase III trial to confirm drug effect in disease Y. To address it, we utilized the rich data collected from the clinical trials for disease X and the knowledge about an important efficacy biomarker Z in both diseases. An existing population PKPD model built for disease X was used to simulate expected biomarker Z response in disease Y. R package RxODE was used to simulate PK concentrations based on a set of ordinary differential equations describing the PK model. Bootstrapping was applied to construct disease Y patient population with intended criteria. Simulations were evaluated if the proposed approach could match the observed biomarker Z levels in disease X. Judging from simulated biomarker Z performances, one dosing regimen was selected with confidence to accelerate development of this drug in disease Y. This application will be of interest to statisticians who need to make informative decision in drug development.
|
Authors who are presenting talks have a * after their name.