Live Preview | Using MonolixSuite to conduct exposure-effect relationship analysis to support clinical decision-making

Transforming Data into Decisions: Step-by-step Exposure-Response Analysis using MonolixSuite

Course Description

Drug exposure-effect relationship research aims to evaluate the quantitative relationship between drug dose, exposure and effect. It explores the dose-effect relationship through modeling and simulation to provide a scientific basis for drug development.

This course will introduce how to calculate key individual exposure indicators (such as AUC and Cmax), which are essential for understanding the variability of patient efficacy and building a robust ER model; and show how to efficiently calculate these indicators in MonolixSuite and R. Then focus on the analysis of exposure-effect relationships and its application in clinical trial design. Combined with the application case of PCSK9-targeted monoclonal antibodies, understand how to build and optimize ER models, and use models to support dose selection for future clinical trials. This course will also explain the analysis methods of continuous effect data and strategies for handling count, classification, and event-time data.

Course Outline 

• Calculation Methods for Key Individual Exposure Indicators
• Implementation steps and workflow of ER analysis in Monolix

Language: Mandarin

Presenter: 
Dr. Monika Twarogowska, Applications Manager, Clinical Pharmacology and Pharmacometrics Solutions, Simulations Plus

Chinese and English interactive guest:
Dr. Lin Lanxi, Quantitative Pharmacology Researcher, Simulations Plus

Webinar Platform: Xiaoeknow (to attend, you will need the WeChat app)

Live Q&A in English and Mandarin following the presentation.

Registration deadline: February 26th at 5:00 PM CST