Mapping physiology: A systems biology approach for the development of alternative methods in toxicology
Series / Report no.
Open Access
Type
Journal Article
Article
Article
Language
en
Date
2025-01-20
Research Projects
Organizational Units
Journal Issue
Title
Mapping physiology: A systems biology approach for the development of alternative methods in toxicology
Translated Title
Published in
ALTEX 2025; 42(2):301-7
Abstract
Chemical safety assessment still heavily relies on animal testing, which is associated with ethical dilemmas and has limited human predictive value. New approach methodologies (NAMs), including in vitro and in silico techniques, offer alternative solutions. In silico toxicology has made progress in predicting chemical effects but frequently lacks biological mechanistic foundations. Recent developments focus on the mechanistic understanding of adverse effects caused by chemicals, as embedded in (quantitative) adverse outcome pathways (AOPs). However, there is a demand for more detailed mechanistic insights at the gene and cell levels, encompassing both pathology and physiology. Drawing inspiration from the Disease Maps Project, this paper introduces physiological maps (PMs) as comprehensive graphical representations of biochemical processes related to specific organ functions. PMs are standardized using Systems Biology Graphical Notation (SBGN) and controlled vocabularies and annotations. Curation guidelines have been developed to ensure reproducibility and usability. We present the methodology used to build PMs, emphasizing the essential collaboration between domain experts and curators. PMs offer user-friendly, standardized visualization for data analysis and educational purposes. Enabling a better understanding of (patho)physiology, they also complement and support the development of AOPs by providing detailed mechanistic information at the gene and cell level. Furthermore, PMs contribute to developing in vitro test batteries and to building (dynamic) in silico models aiming to predict the toxicity of chemicals. Collaborative efforts between the toxicology and systems biology communities are crucial for creating standardized and comprehensive PMs, supporting and accelerating the development of human-relevant NAMs for next-generation risk assessment.
Assessing the safety of chemicals still relies heavily on animal testing, which raises ethical concerns and has limited relevance to humans. New approach methodologies (NAMs), such as in silico (computer-based) models and in vitro (laboratory-based) experiments, offer promising alternatives. However, current NAMs often lack a detailed understanding of the underlying biological mechanisms. This paper introduces physiological maps (PMs), in silico tools that visually represent biological processes and interactions within specific organs and cells. PMs use standardized formats and annotations, making them easy to share and understand. By providing insights into human biology, PMs complement and enhance NAMs, including adverse outcome pathways (AOPs), in vitro experiments, and in silico models, aiming to improve predictions of chemical toxicity. This approach fosters collaboration between toxicology and systems biology scientists in order to advance human-relevant risk assessment methods.
Assessing the safety of chemicals still relies heavily on animal testing, which raises ethical concerns and has limited relevance to humans. New approach methodologies (NAMs), such as in silico (computer-based) models and in vitro (laboratory-based) experiments, offer promising alternatives. However, current NAMs often lack a detailed understanding of the underlying biological mechanisms. This paper introduces physiological maps (PMs), in silico tools that visually represent biological processes and interactions within specific organs and cells. PMs use standardized formats and annotations, making them easy to share and understand. By providing insights into human biology, PMs complement and enhance NAMs, including adverse outcome pathways (AOPs), in vitro experiments, and in silico models, aiming to improve predictions of chemical toxicity. This approach fosters collaboration between toxicology and systems biology scientists in order to advance human-relevant risk assessment methods.