NCA Assistant: An Open-source R/Shiny Interface for Non-compartmental Pharmacokinetic Analysis, Bioequivalence Testing and Study Planning
Abstract Accessible tools for pharmacokinetic education and routine clinical pharmacokinetic analysis remain limited. Commercial software carries licensing costs and on the other hand existing open-source alternatives lack integrated workflows spanning study planning through bioequivalence assessment and are not user-friendly. We developed NCA Assistant, a browser-based application for non-compartmental pharmacokinetic analysis, bioequivalence testing, and power and sample size calculations within a single platform designed for pharmacokinetic research and teaching. NCA Assistant was designed with Anthropic Claude AI as coding assistant, with multi-expert prompting. The app was developed in R/Shiny with a hub-based architecture connecting six workflow modules. Core computations rely on established R packages for non-compartmental analysis, power and sample size calculations and analysis of variance. For the interface, there was an emphasis for transparency through interactive visualization, configurable analysis settings and exportable audit trails. The application supports extravascular and intravenous dosing scenarios, handles both single-subject and batch analyses and accommodates standard crossover, replicate, and parallel bioequivalence designs.A dedicated visualization module generates publication-ready concentration–time plots. Features include interactive terminal half-life review with point selection override and configurable thresholds for elimination half-life calculation. A validation package, consisting of draft validation documents and a validation script, accompanies the application and is supplied in the supplemental materials. NCA Assistant provides an accessible entry point for pharmacokinetic data analysis suitable for graduate training and routine clinical pharmacology applications, with extensibility for use in more regulated environments.
Authors
- Rob ter Heine (ORCID: https://orcid.org/0000-0003-2185-8201)
Publication Details
- Journal
- The AAPS Journal
- Published
- 2026-09-28
- DOI
- https://doi.org/10.1208/s12248-026-01316-w
- Primary Topic
- Statistical Methods in Clinical Trials
- Type
- article
- Field-Weighted Citation Impact
- 0.00