(T-110) Simulation of Trial Predictions with Model Uncertainty using NMsim

Weiyan Zhang, Ph.D. – Associate Director, Modeling & Simulations, Vertex Pharmaceuticals; Philip Delff, Ph.D. – Director, Modeling & Simulations, Vertex Pharmaceuticals

Objectives: Clinical Trial Simulation (CTS) is the application of pharmacokinetics (PK) or pharmacokinetics/pharmacodynamics (PK/PD) modeling to assist in the design of clinical trials. Simulation with NMsim allows users to incorporate uncertainties from either a covariance step or bootstrap results. NMsim can moreover run simulations on multiple NONMEM models simultaneously. The user only needs to provide paths to control stream(s) and a simulation data set. We aim to show these features through some examples that are highly relevant in pharmacometrics.

Methods: Two different PopPK models estimated on two separate groups of patients will be simulated. Simple modifications using the NMsim R package will be shown to address questions like:
• How to create models capable of simulating data representing two groups of patients selected from a population?
• How to incorporate uncertainties from a covariance step?
• How to incorporate uncertainties from bootstrap results?
• How to summarize simulation results during post-processing?

The seamless workflow of NMsim allows the codes to be readily applicable to most NONMEM PopPK models, the user interface entirely within R.

Results: NMsim provides a well-designed interface to rapidly simulate a large number of clinical trials. Model-agnostic code allows simulation of multiple NONMEM models with parameter uncertainty. The results illustrate how easily a model-based approach to some questions commonly asked in drug discovery and drug development can be performed.

Conclusions: The examples provided in this work address selected questions related to parameter uncertainty of two PopPK models. NMsim's features provide a powerful tool to easily explore clinical trial simulations to support study design during the drug development process.

Citations: [1] 2024. NMsim: An R package that can simulate Nonmem models. https://philipdelff.github.io/NMsim
[2] 2024. NMsim: Seamless ‘Nonmem’ Simulation Platform. https://cran.r-project.org/web/packages/NMsim