ArticleBiology & philosophy2026
Model organism futures in precision toxicology: tracking the emergence of a research repertoire.
Article in Biology & philosophy, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
This paper considers the continued use of simpler model organisms in newer forms of toxicological research in order to inform philosophical understandings of the epistemic roles played by such organisms in the contemporary life sciences. We focus on the emerging domain of 'precision toxicology' and consider three uses of model organisms within it, namely as (1) models of toxic effects and other forms of environmental exposures; (2) indicator species; and (3) bioremediators. We analyze the epistemic implications of these uses, arguing that they represent hybrid forms of modelling in comparison to traditional uses of model organisms, and identify similarities and differences between these emerging research practices and the model organism repertoire being adapted for use in this domain. Model organisms are simultaneously viewed as tools for intervention and representation within precision toxicology, in ways that differ from the model organism repertoire both in terms of the extent to which the models fit applied research goals and how they foster evolutionary and developmental understanding. Hence we argue that model organisms remain highly influential models in the life sciences but are being used in research more closely associated with the concept of 'precision,' and characterized by an ethos of intervention particularly in response to the environmental challenges associated to climate change and attention to the evolutionary and developmental grounding of health and disease. In closing, we reflect on the ways in which using the analytic framing associated with the repertoires approach facilitates the tracking of these developments in the contemporary life sciences. We also assess how they may affect the construction and significance of model systems over coming decades particularly in relation to precision-related research.
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