Roundtable Discussion: Driving Confidence in Preclinical Models Through Robust Validation Standards
- What does “validated enough” mean in your organisation?
- How do validation expectations differ between discovery screening, candidate selection, and IND-enabling decisions?
- How are you selecting positive and negative control compounds, and where do gaps remain?
- What trade-offs exist between scientific relevance, historical data availability, and program timelines?
- How do you demonstrate human relevance when clinical anchoring data are limited or absent?
- What surrogate endpoints (e.g. biomarkers, exposure-response, phenotypic signatures) are most persuasive internally and externally?
- How do regulatory expectations influence your internal validation bar?
- Are FDA/EMA interactions raising standards, or creating flexibility around context-ofuse?
- Where do cross-industry frameworks (e.g. HESI, IQ MPS, consortia efforts) genuinely help, and where do they fall short?