Onsite In-Silico Clinical Trials with NLME Models| Leiden, Netherlands

Description

Learn to design and execute In Silico Clinical Trials (ISCTs) using Pumas and Julia. This intensive one-day workshop guides participants through a complete 7-step ISCT workflow—from building mechanistic QSP models to generating calibrated virtual populations and running virtual clinical trials. Using two disease models (tumor burden and HBV), participants will be introduced to copula sampling, MILP-based population calibration, global sensitivity analysis, and bootstrap inference for treatment effect estimation. Hands-on exercises ensure you leave with practical skills to apply ISCTs to your own drug development programs.

ISCTs represent a powerful paradigm shift in drug development, enabling researchers to simulate clinical outcomes across diverse virtual patient populations before committing resources to expensive real-world trials. This workshop provides a comprehensive, hands-on introduction to the complete ISCT workflow using Julia and the Pumas pharmacometrics platform.

Based on the methodology published in *CPT: Pharmacometrics & Systems Pharmacology* (Cortés-Ríos et al., 2025), this workshop translates a validated 7-step framework into practical skills. Participants will work through two progressively complex disease models: a tumor burden model that introduces core concepts, and an 11-ODE Hepatitis B virus (HBV) QSP model that demonstrates real-world complexity.

What You Will Learn

• Build QSP Models in Pumas: Define disease progression and drug PK/PD using the Pumas `model` macro with proper NLME parameterization
• Conduct Global Sensitivity Analysis: Identify influential parameters using Sobol and eFAST methods to focus model development efforts
• Generate Virtual Populations: Sample correlated parameters using copulas while preserving clinically-observed distributions
• Calibrate to Clinical Data: Use Mixed-Integer Linear Programming (MILP) to select virtual patients matching target clinical distributions
• Run Virtual Clinical Trials: Simulate multi-arm trials with treatment phases and calculate clinical endpoints
• Quantify Uncertainty: Apply bootstrap inference for confidence intervals on treatment effects

Who Should Attend

• Pharmacometricians transitioning to QSP modeling
• Quantitative systems pharmacologists building virtual patient workflows
• Clinical pharmacologists designing virtual trials
• Computational biologists working on drug development pipelines
• Anyone interested in leveraging in silico methods for clinical trial optimization

Prerequisites

• Working knowledge of Julia and basic Pumas modeling (or equivalent experience with NLME frameworks)
• Understanding of pharmacokinetic/pharmacodynamic and QSP concepts
• Familiarity with ordinary differential equations
• Laptop

Materials Provided

• Complete Pumas codebase with ISCTWorkflow module
• Quarto based tutorials covering theory and implementation
• Executable example scripts with annotated code
• Exercise solutions for self-study
• Reference documentation for all module functions
• Pumas 2.8 trial license

Reference

• Cortés-Ríos, J., Magee, M., Sher, A., Jusko, W. J., & Desikan, R. (2025). A Step-by-Step Workflow for Performing In Silico Clinical Trials With Nonlinear Mixed Effects Models. *CPT: Pharmacometrics & Systems Pharmacology*. DOI: [10.1002/psp4.70122](https://doi.org/10.1002/psp4.70122)
  Notes:
  Please note that these workshops are intended for attendees from academic or industry backgrounds. We kindly request that you register using your institutional or work email address, as this same address will be used to grant you access to Pumas products. If you have any questions or concerns, feel free to reach out to us.

Pricing: $500 for Industry, $100 for Academia

Bring Your Team, Save More! Groups of 3+ qualify for a group discount. Email [email protected] to inquire.

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Host or Publisher Pumas-AI, Inc.