Translating time: Challenges, progress, and future directions
Year: 2025
Type: review
Abstract: Mice are the dominant model system to study human health and disease. Yet, there is a pressing need to use diverse model systems to address long-standing issues in biomedical sciences. Mice do not spontaneously recapitulate many of the diseases we seek to study. Accordingly, the relevance of studying mice to understand human disease is limited. We discuss examples associated with limitations of the mouse model, and how the inclusion of a richer array of model systems can help address long standing issues in biomedical sciences. We also discuss a tool called Translating Time, an online resource ( www.translatingtime.org ) that equates corresponding ages across model systems and humans. The translating time resource can be used to bridge the gap across species and make predictions when data are sparse or unavailable as is the case for human fetal development. Moreover, the Translating Time tool can map findings across species, make inferences about the evolution of shared neuropathologies, and inform the optimal model system for studying human biology in health and in disease. Resources such as these can be utilized to integrate information across diverse model systems to improve the study of human biology in health and disease. • Mice are the dominant model system to study human health and disease but they do not spontaneously recapitulate many of the diseases we seek to study. • The inclusion of a richer array of model systems can address long standing issues in biomedical sciences. • Translating Time is a resource to equate ages across species, that has the power to predict the timetable of developmental processes in any species. • Resources such as Translating Timecan be used to harness information from diverse species to overcome challenges in human medicine.
Source: Brain Research Bulletin
Institution: Auburn University
Language: English
Subfield: Small Animals
Field: Veterinary
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $3,280
OpenAlex ID: W4406405230