(S-044) Development of nmbench: A Lightweight NONMEM Workbench extension for Efficient Population Modeling and Simulation

Woojin Jung – Senior Health Convergence Research Center, Chungnam National University, Republic of Korea; Soyoung Lee – College of Pharmacy, Chungnam National University, Daejeon, Republic of Korea; Jung-woo Chae – College of Pharmacy, Chungnam National University, Daejeon, Republic of Korea; Hwi-yeol Yun – College of Pharmacy, Chungnam National University, Daejeon, Republic of Korea

Objectives: NONMEM remains the gold standard in population pharmacokinetic/pharmacodynamic (PK/PD) modeling. However, the complexity of its command-line interface and file management can limit user accessibility and operational efficiency. To address these challenges, we developed nmbench, a lightweight and extensible Visual Studio Code (VS Code) extension that serves as a user-friendly workbench for NONMEM. This extension aims to streamline model development, execution, and diagnostics by integrating with PsN (Perl-speaks-NONMEM) and organizing modeling workflows within a modern development environment.

Methods: nmbench was implemented in TypeScript using the VS Code extension API. It provides a tree-based visualization of NONMEM project structures, enabling real-time tracking of model files, output logs, and run statuses. Key PsN utilities such as execute, vpc, and bootstrap are accessible through an intuitive graphical interface. The extension dynamically displays run-specific metadata such as objective function value (OFV) changes and estimation results. It supports parsing of .mod, .ctl, and .lst files to facilitate efficient model navigation and inspection. The extension is primarily designed to support workflows involving NONMEM, PsN, and R scripting.

Results: nmbench offers a rich suite of diagnostic and visualization tools for model interpretation. The built-in .lst viewer enables structured inspection of NONMEM outputs. A Shiny-powered matrix viewer allows interactive exploration of parameter estimates across multiple runs, and a table viewer facilitates the visualization of output tables using histograms and time-series plots. In addition, user-defined R scripts are supported, with built-in templates for generating goodness-of-fit (GOF), visual predictive check (VPC), and individual plots using the xpose and xpose4 R packages. These integrated features enable seamless access to model results without switching between external applications, thereby enhancing the user experience in diagnostics and model refinement. The extension is optimized for NONMEM version 7.5.1 and PsN version 5.5.0, and is compatible with both Windows and macOS environments supported by VS Code.

Conclusions: nmbench provides a streamlined, reproducible, and user-friendly modeling environment by combining the robust analytical capabilities of PsN with the modern interface of Visual Studio Code. As a lightweight VS Code extension, nmbench offers high flexibility and ease of deployment across platforms, including remote computing environments, making it especially suitable for distributed research workflows and cloud-based modeling tasks. Future developments will include integrated diagnostics, and enhanced visualization modules to support model-informed drug development (MIDD).

Citations: [1] Lindbom L, Pihlgren P, Jonsson EN. PsN-Toolkit--a collection of computer intensive statistical methods for non-linear mixed effect modeling using NONMEM. Comput Methods Programs Biomed. 2005 Sep;79(3):241-57.
[2] Lindbom L, Ribbing J, Jonsson EN. Perl-speaks-NONMEM (PsN)--a Perl module for NONMEM related programming. Comput Methods Programs Biomed. 2004 Aug;75(2):85-94.

Keywords: Visual Studio Code extension, Software, Pharmacometrics