Why traditional validation may fall short for artificial intelligence in bioanalysis: a perspective from the European Bioanalysis Forum

Abstract

As artificial intelligence enters bioanalysis, traditional validation frameworks, designed for static, deterministic systems are proving unfit for purpose. This paper, developed from the 2025 European Bioanalysis Forum Spring Focus Workshop, challenges the assumption that applications using artificial intelligence should be validated like conventional tools. We propose a shift toward adaptive qualification: an approach rooted in scientific oversight, contextual relevance and earned trust. Reframing artificial intelligence as a learning system, more trainee than tool, we explore how oversight must evolve beyond compliance to ensure transparency, robustness and fitness for purpose. Above all, we argue that scientists must remain at the helm. Not to preserve legacy processes, but to guide this evolving landscape with clarity, collaboration and responsibility, keeping innovation sharp and the patient in focus.

Ähnliche Arbeiten