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Making PBPK models more reproducible in practice

Authors: Elena Domínguez Romero; Stanislav Mazurenko; Martin Scheringer; Vítor A. P. Martins dos Santos; Chris T. A. Evelo; Mihail Anton; John M. Hancock; +2 Authors

Making PBPK models more reproducible in practice

Abstract

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.

Countries
Netherlands, Czech Republic, Slovenia, Slovenia
Keywords

MATLAB, farmakokinetika, farmakodinamika, sistemska biologija, TOXICOLOGY, info:eu-repo/classification/udc/57, Review, systems biology; pharmacokinetics; model code; reproducibility; SBML; MATLAB, Models, Biological, SBML, Humans, Animals, Pharmacokinetics, Computer Simulation, farmakodinamika, reproducibility, Systems Biology, pharmacokinetics, pharmacodynamics, model code, reproducibility, SBML, MATLAB, systems biology, Reproducibility of Results, farmakokinetika, systems biology, info:eu-repo/classification/udc/57; 659.2:004, SYSTEMS BIOLOGY, sistemska biologija, model code, RISK-ASSESSMENT, pharmacokinetics, Software, STANDARDS

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    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
9
Top 10%
Top 10%
Top 10%
Green
gold