Experimental models of osteoarthritis: Advances, limitations and rational selection for translational research

Jianxiong Shu1, Taiyuan Huang1, Zhaoran Wu1

  • 1Department of Joint and Orthopedics, Orthopedic Center, Clinical Research Center, Zhujiang Hospital, Southern Medical University, Guangzhou, Guangdong, China.

Insights

Developing effective osteoarthritis (OA) treatments requires better experimental models. This review evaluates animal and in vitro models to bridge the gap between preclinical research and clinical applications for osteoarthritis therapies.

Area of Science:

  • Biomedical research
  • Translational science
  • Osteoarthritis research

Background:

  • Osteoarthritis (OA) is a complex joint disease with no approved disease-modifying drugs (DMOADs) due to a translational gap.
  • Preclinical models are crucial for understanding OA and testing therapies, but their clinical relevance is often limited.

Purpose of the Study:

  • To comprehensively review and evaluate current experimental models for osteoarthritis.
  • To establish a rational framework for selecting appropriate OA models based on pathological features.
  • To facilitate the development of effective OA therapeutics by bridging the preclinical-clinical translational gap.

Main Methods:

  • Systematic evaluation of various animal models (surgical, mechanical, chemical, metabolic, aging, genetic).
  • Assessment of in vitro platforms, ex vivo tissue explants, and emerging technologies (organ-on-a-chip, organoids).
  • Analysis of model advantages, limitations, and applicability to specific OA subtypes.

Main Results:

  • Current OA models have limitations in recapitulating the complexity of human disease.
  • In vitro and bioengineered platforms offer complementary insights and can enhance predictive reliability.
  • A framework for rational model selection is proposed to improve translational potential.

Conclusions:

  • No single model perfectly replicates OA; a combination of approaches is often necessary.
  • Improved model selection and utilization of novel platforms can accelerate the development of DMOADs.
  • This review provides a reference for enhancing preclinical research reliability and advancing personalized OA therapies.

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