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Updated: Jan 20, 2026

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Tutorial on Causal Mediation Analysis for Pharmacometricians.

Sebastiaan Camiel Goulooze1, Eleonora Marostica1, Nelleke Snelder1

  • 1LAP&P Consultants BV, Leiden, the Netherlands.

CPT: Pharmacometrics & Systems Pharmacology
|January 19, 2026
PubMed
Summary
This summary is machine-generated.

Causal mediation analysis quantifies how biomarkers contribute to treatment effects, offering pharmacometricians a powerful tool. This tutorial introduces causal mediation analysis for biomarker development using simulation workflows.

Keywords:
biomarker developmentcausal inferencecausal mediation analysismediation analysispharmacokinetic–pharmacodynamic modeling

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Area of Science:

  • Pharmacometrics
  • Biomarker Development
  • Causal Inference

Background:

  • Mediation analysis quantifies the indirect effect of a treatment on clinical outcomes via a biomarker.
  • Pharmacometricians frequently analyze biomarker data using pharmacokinetic-pharmacodynamic (PK-PD) models.
  • Integrating mediation analysis enhances the pharmacometrics toolkit for biomarker-driven drug development.

Purpose of the Study:

  • To introduce causal mediation analysis concepts within a pharmacometric context.
  • To demonstrate the application of causal mediation analysis for biomarker development.
  • To provide a simulation-based workflow with example code and datasets for practical implementation.

Main Methods:

  • Exploration of generalized causal mediation analysis principles.
  • Application of causal mediation analysis to pharmacometric models.
  • Utilizing a simulation-based workflow for analysis and illustration.

Main Results:

  • Demonstration of how mediation analysis quantifies biomarker-mediated treatment effects.
  • Illustrates the suitability of causal mediation analysis for complex pharmacometric models (non-linearities, interactions).
  • Provides a reproducible workflow for applying these methods.

Conclusions:

  • Causal mediation analysis is a valuable addition to the pharmacometrics toolbox.
  • This approach supports biomarker development by elucidating indirect treatment effects.
  • The tutorial facilitates the adoption of causal mediation analysis in pharmacometric research.