Preface to the special issue of Food and Chemical Toxicology on “New approach methodologies and machine learning in food safety and chemical risk assessment: Development of reproducible, open-source, and user-friendly tools for exposure, toxicokinetic, and toxicity assessments in the 21st century”

Lin, Zhoumeng; Basili, Danilo; Chou, Wei-Chun

doi:10.1016/j.fct.2024.114809

Food and Chemical Toxicology

2024

DOI: 10.1016/j.fct.2024.114809

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Preface to the special issue of Food and Chemical Toxicology on “New approach methodologies and machine learning in food safety and chemical risk assessment: Development of reproducible, open-source, and user-friendly tools for exposure, toxicokinetic, and toxicity assessments in the 21st century”

Zhoumeng Lin,

Danilo Basili,

Wei-Chun Chou

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Making PBPK models more reproducible in practice

Domínguez-Romero,

Mazurenko,

Scheringer

et al. 2024

Briefings in Bioinformatics

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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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Making PBPK models more reproducible in practice

Domínguez-Romero,

Mazurenko,

Scheringer

et al. 2024

Briefings in Bioinformatics

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show abstract

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Cited by 1 publication

References 19 publications

Making PBPK models more reproducible in practice

Making PBPK models more reproducible in practice

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