Osteoarthritis (OA) is increasingly recognised as a disease of diverse phenotypes with variable clinical presentation, progression, and response to therapeutic intervention. This same diversity is readily apparent in the many animal models of OA. However, model selection, study design, and interpretation of resultant findings, are not routinely done in the context of the target human (or veterinary) patient OA sub-population or phenotype.

This review discusses the selection and use of animal models of OA in discovery and therapeutic-development research. Beyond evaluation of the different animal models on offer, this review suggests focussing the approach to OA-animal model selection on study objective(s), alignment of available models with OA-patient sub-types, and the resources available to achieve valid and translatable results. How this approach impacts model selection is discussed and an experimental design checklist for selecting the optimal model(s) is proposed. This approach should act as a guide to new researchers and a reminder to those already in the field, as to issues that need to be considered before embarking on in vivo pre-clinical research.

The ultimate purpose of using an OA animal model is to provide the best possible evidence if, how, when and where a molecule, pathway, cell or process is important in clinical disease. By definition this requires both model and study outcomes to align with and be predictive of outcomes in patients. Keeping this at the forefront of research using pre-clinical OA models, will go a long way to improving the quality of evidence and its translational value.

骨关节炎 (OA) 越来越被认为是一种具有多种表型的疾病，具有不同的临床表现、进展和对治疗干预的反应。在 OA 的许多动物模型中，这种相同的多样性很明显。然而，模型选择、研究设计和对结果结果的解释通常不是在目标人类（或兽医）患者 OA 亚群或表型的背景下进行的。

本综述讨论了 OA 动物模型在发现和治疗开发研究中的选择和使用。除了评估所提供的不同动物模型外，本综述建议将 OA 动物模型选择的方法重点放在研究目标、可用模型与 OA 患者亚型的一致性以及可用于实现有效和可翻译的资源结果。讨论了这种方法如何影响模型选择，并提出了用于选择最佳模型的实验设计清单。这种方法应该作为新研究人员的指南，并提醒已经在该领域的研究人员，在开始体内临床前研究之前需要考虑的问题。

使用 OA 动物模型的最终目的是提供可能的最佳证据，即分子、通路、细胞或过程在临床疾病中是否、如何、何时以及何地重要。根据定义，这需要模型和研究结果与患者的结果保持一致并对其进行预测。使用临床前 OA 模型将其保持在研究的前沿，将大大有助于提高证据质量及其转化价值。