SimRFlow: An R-based workflow for automated high-throughput PBPK simulation with the Simcyp^® simulator.

Area of Science:

• Pharmacokinetics and Drug Metabolism
• Computational Chemistry
• Systems Biology

Background:

• Physiologically based pharmacokinetic (PBPK) modeling is crucial for predicting drug behavior in vivo.
• High-throughput screening of drug candidates requires efficient and automated modeling tools.
• Manual data curation for PBPK simulations is a significant bottleneck in drug discovery.

Purpose of the Study:

• To develop an automated, high-throughput PBPK modeling workflow.
• To integrate data curation, simulation, and visualization into a single tool.
• To facilitate rapid PBPK analysis for large compound libraries.

Main Methods:

• Developed SimRFlow, an R Shiny application utilizing Certara's Simcyp® simulator.
• Automated data collection from ChEMBL, Norman Suspect List, and httk-R databases.
• Implemented three modules: Data Collection, Simulation (Monte Carlo), and Data Visualization.
• Supported oral, intravenous, and dermal administration routes with customizable simulation parameters.

Main Results:

• SimRFlow automates the curation of physicochemical and experimental data.
• The tool performs high-throughput Monte Carlo simulations for virtual subjects.
• Generates summary statistics, tissue concentration-time profiles, and detailed results databases.
• Provides an R Shiny interface with extensive visualization options for compound-specific profiles and parameter comparisons.

Conclusions:

• SimRFlow significantly reduces the time and effort required for PBPK simulations.
• Enables efficient screening of numerous compounds without manual data input.
• Facilitates understanding of compound-specific pharmacokinetic profiles and predictions.