Making PBPK models more reproducible in practice

Systems biology aims to understand living organisms through mathematically modeling their behaviors at different organizational levels, ranging from molecules to populations. Modeling involves several steps, from determining the model purpose to developing the mathematical model, implementing it computationally, simulating the model's behavior, evaluating, and refining the model. Importantly, model simulation results must be reproducible, ensuring that other researchers can obtain the same results after writing the code de novo and/or using different software tools. Guidelines to increase model reproducibility have been published. However, reproducibility remains a major challenge in this field. In this paper, we tackle this challenge for physiologically-based pharmacokinetic (PBPK) models, which represent the pharmacokinetics of chemicals following exposure in humans or animals. We summarize recommendations for PBPK model reporting that should apply during model development and implementation, in order to ensure model reproducibility and comprehensibility. We make a proposal aiming to harmonize abbreviations used in PBPK models. To illustrate these recommendations, we present an original and reproducible PBPK model code in MATLAB, alongside an example of MATLAB code converted to Systems Biology Markup Language format using MOCCASIN. As directions for future improvement, more tools to convert computational PBPK models from different software platforms into standard formats would increase the interoperability of these models. The application of other systems biology standards to PBPK models is encouraged. This work is the result of an interdisciplinary collaboration involving the ELIXIR systems biology community. More interdisciplinary collaborations like this would facilitate further harmonization and application of good modeling practices in different systems biology fields.

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Publication Details

Journal
Briefings in Bioinformatics
Published
2024-09-23
DOI
https://doi.org/10.1093/bib/bbae569
Citations
9
Primary Topic
Gene Regulatory Network Analysis
Type
article
Field-Weighted Citation Impact
2.10

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article

Making PBPK models more reproducible in practice

John M. Hancock, Mihail Anton, Vítor A. P. Martins dos Santos, María Suárez‐Diez et al.
9 citations
Briefings in Bioinformatics
Gene Regulatory Network Analysis
2.10
article

Making PBPK models more reproducible in practice

John M. Hancock, Mihail Anton, Vítor A. P. Martins dos Santos, María Suárez‐Diez, Stanislav Mazurenko, Anže Županič, Elena Domínguez-Romero, Chris T. Evelo, Martin Scheringer
article en
9 citations

Abstract

Systems biology aims to understand living organisms through mathematically modeling their behaviors at different organizational levels, ranging from molecules to populations. Modeling involves several steps, from determining the model purpose to developing the mathematical model, implementing it computationally, simulating the model's behavior, evaluating, and refining the model. Importantly, model simulation results must be reproducible, ensuring that other researchers can obtain the same results after writing the code de novo and/or using different software tools. Guidelines to increase model reproducibility have been published. However, reproducibility remains a major challenge in this field. In this paper, we tackle this challenge for physiologically-based pharmacokinetic (PBPK) models, which represent the pharmacokinetics of chemicals following exposure in humans or animals. We summarize recommendations for PBPK model reporting that should apply during model development and implementation, in order to ensure model reproducibility and comprehensibility. We make a proposal aiming to harmonize abbreviations used in PBPK models. To illustrate these recommendations, we present an original and reproducible PBPK model code in MATLAB, alongside an example of MATLAB code converted to Systems Biology Markup Language format using MOCCASIN. As directions for future improvement, more tools to convert computational PBPK models from different software platforms into standard formats would increase the interoperability of these models. The application of other systems biology standards to PBPK models is encouraged. This work is the result of an interdisciplinary collaboration involving the ELIXIR systems biology community. More interdisciplinary collaborations like this would facilitate further harmonization and application of good modeling practices in different systems biology fields.

Briefings in BioinformaticsVol. 25(6)
University of Ljubljana (SI), Masaryk University (CZ), Science for Life Laboratory (SE), University Hospital Brno (CZ), St. Anne's University Hospital Brno (CZ), National Institute of Biology (SI), Elixir Medical (United States) (US), National Bioinformatics Infrastructure Sweden, Chalmers University of Technology (SE), Wageningen University & Research (NL)
European Commission, Ministerstvo Školství, Mládeže a Tělovýchovy, Universiteit Maastricht, Nederlandse Organisatie voor Wetenschappelijk Onderzoek, RECETOX Přírodovědecké Fakulty Masarykovy Univerzity
Openalex Percentile: Top 12%
Gene Regulatory Network Analysis
2.10
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