Evaluating the translational value of preclinical models: available tools and frameworks, challenges and strategies : workshop reports - Pistollato, Francesca; Furtmann, Fabia; Straccia, Marco; Avey, Marc; Azilagbetor, David Mawufemor; Camp, Celean; Delaney, Conor; Ferreira, Guilherme S.; Garcia-Bermejo, Maria Laura; Gastaldello, Annalisa; Gurusamy, Kurinchi; Holden, Laura; et al. (Alternatives to laboratory animals, 2026)
Recent global initiatives are accelerating the shift toward human-centric approaches, reducing reliance on animal models in preclinical research and other domains. In this changing landscape, objectively evaluating the scientific relevance and merit of research involving animal models, and assessing their translational relevance is increasingly critical. Over the past decade, several tools have been developed to assess translational relevance, accuracy/appropriateness and efficacy of preclinical animal models, evaluate risk-of-bias in preclinical research, support harm-benefit analyses, and facilitate the adoption of non-animal replacement strategies. However, the uptake of such tools remains limited. To address this, a Biomedical Research for the 21st Century (BioMed21) Collaboration workshop on ‘Evaluating translational value of animal models in preclinical research — Tools, challenges, and strategies’, was convened by Humane World for Animals (30 June-1 July 2025). The event brought together tool developers and diverse global interest-holders to review current assessment tools, discuss their strengths, complementarity, limitations and feasibility, and explore opportunities for cross-sector collaboration. This paper summarises key outcomes of these presentations and discussions, highlighting knowledge gaps and barriers to the adoption of these tools and frameworks by researchers, funders and regulators. Strategies to raise awareness and promote the use of the tools and frameworks, to better inform funding decisions, regulatory approval and the appraisal of preclinical research, are also proposed.