Facilitating pharmacometric workflow with the metrumrg package for R

Area of Science:

• Pharmacometrics
• Computational Biology
• Data Science

Background:

• Pharmacometric analyses often involve complex, multi-step workflows.
• Integrating various software tools can be challenging and time-consuming.
• Traceability and reproducibility are critical in scientific research.

Purpose of the Study:

• To introduce metrumrg, an R package designed to streamline pharmacometric workflows.
• To provide a unified environment for data preparation, modeling, simulation, diagnostics, and reporting.
• To enhance the integration of R with established pharmacometric software like NONMEM.

Main Methods:

• Development of the metrumrg R package.
• Implementation of an R interface for NONMEM modeling software.
• Support for running NONMEM in a distributed computing environment.
• Emphasis on text-based formats for analysis and reporting.

Main Results:

• metrumrg facilitates a start-to-finish analysis workflow within a single scripting language (R).
• The package integrates existing pharmacometric tools and provides novel solutions.
• Enhanced traceability of results is achieved through text-based formats.
• Efficient execution of NONMEM, including in distributed environments, is supported.

Conclusions:

• metrumrg offers a comprehensive solution for improving pharmacometric workflow efficiency and reproducibility.
• The package empowers researchers to conduct analyses from data preparation to reporting within R.
• Integration with NONMEM and emphasis on traceability make metrumrg a valuable tool for the pharmacometrics community.