Translational assessment instruments for preclinical to first-in-human decision-making: a scoping review

Area of Science:

• Translational science
• Drug development
• Clinical research

Background:

• Preclinical evidence for first-in-human (FIH) decisions often uses isolated tools, failing to preserve assumptions and decision intent across handoffs.
• Existing structured translational assessment instruments were reviewed to evaluate their components for decision-grade evidence integration.

Purpose of the Study:

• To review structured translational assessment instruments for preclinical-to-human decision-making.
• To examine if the current landscape supports decision-grade evidence integration.

Main Methods:

• Scoping review using PRISMA-ScR principles.
• Searches in PubMed and citation snowballing.
• Identification and mapping of 19 distinct instruments across the preclinical-to-FIH pathway.

Main Results:

• Strengths identified in model selection, reporting quality, risk-of-bias control, and mechanistic claims.
• Limitations include poor benchmarking against human outcomes and lack of uncertainty propagation.
• Outputs are rarely designed as reusable governance artifacts, leading to stronger evidence production than integration.

Conclusions:

• Weak interoperability between assessment instruments, not their absence, limits translational practice.
• A staged, uncertainty-aware workflow preserving assumptions and decision logic can improve preclinical evidence auditability and reuse for FIH governance.
• Prospective testing is needed to confirm if these workflows improve predictive performance or clinical decision quality.