LB-020 - DEVELOPMENT OF AN R SHINY APPLICATION TO STREAMLINE DRUG-DRUG INTERACTION SIMULATIONS UTILIZING THE SIMCYP-R PACKAGE.

S. Al Sahlawi¹, J. Hogan², T. Cabalu², K. Yee²; ¹Univeristy of Florida, Orlando, FL, USA, ²Merck, West Point, PA, USA.

Background: Physiologically Based Pharmacokinetic (PBPK) modeling is widely used to evaluate drug-drug interaction (DDI) risks. Simcyp® is a PBPK platform that simulates DDIs involving drug-metabolizing enzymes and transporters. The Simcyp-R package enables users to conduct simulations within R, reducing simulation time, and enhancing data visualization through R's robust statistical and graphical capabilities. This project aims to develop a user-friendly R Shiny interface that leverages the Simcyp-R package to streamline DDI assessment workflow.

Methods: We developed an R Shiny application to facilitate single- and multiple-dosing simulations, as well as DDI simulations, utilizing the Simcyp-R package (v23). The R Shiny interface was developed in R (v4.2.1) and was designed to enable users to upload files, adjust simulation inputs, run simulations, and view the output. To validate the app, we conducted multiple simulations using Merck’s internal compounds and compounds from the Simcyp library. The results generated by the R Shiny app were compared with those from the Simcyp simulator, assessing both accuracy and simulation runtime.

Results: The R Shiny interface was designed with four main tabs to streamline DDI simulation workflow. The File Upload tab enables users to upload Simcyp compound files and add observed concentration-time profiles for overlay and non-compartmental analysis (NCA). The Single- and Multiple-Dose Simulation tabs enable simulations with adjustable parameters (e.g., dosing regimen, trial design) and output summary statistics of observed vs. predicted PK metrics, concentration-time profiles, and a detailed database file. The DDI Simulation tab allows users to perform simulations by selecting validated clinical inhibitors or inducers from the Simcyp library, outputting AUC and Cmax ratios. Overall, the application generated results consistent with the Simcyp simulator and significantly improved workflow efficiency by reducing simulation time, especially for drugs with longer half-lives and complex models.

Conclusion: The R Shiny application provides an efficient and user-friendly workflow for conducting DDI simulations. This tool facilitates faster simulations with enhanced data visualization, supporting decision-making in drug development.