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

IF 1.8 4区医学 Q3 BIOCHEMICAL RESEARCH METHODS

Bioanalysis Pub Date : 2025-07-01 Epub Date: 2025-07-29 DOI:10.1080/17576180.2025.2535219

Philip Timmerman, Katja Zeiser, Connor Walker, Robert Nelson, Michaela Golob, Matthew Barfield

引用次数: 0

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.

查看原文本刊更多论文

为什么传统的验证可能会在生物分析中的人工智能不足：来自欧洲生物分析论坛的观点。

随着人工智能进入生物分析领域，为静态、确定性系统设计的传统验证框架被证明不适合使用。这篇论文来自2025年欧洲生物分析论坛春季焦点研讨会，挑战了使用人工智能的应用程序应该像传统工具一样进行验证的假设。我们建议向适应性资格的转变：一种根植于科学监督、上下文相关性和赢得信任的方法。我们将人工智能重新定义为一个学习系统，更多的是学员而不是工具，探讨监管必须如何超越合规，以确保透明度、稳健性和适用性。最重要的是，我们认为科学家必须继续掌舵。不是为了保留传统流程，而是为了以清晰、协作和责任来指导这一不断变化的景观，保持创新的锐气和耐心的焦点。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

Bioanalysis BIOCHEMICAL RESEARCH METHODS-CHEMISTRY, ANALYTICAL

CiteScore

3.30

自引率

16.70%

发文量

审稿时长

2 months

期刊介绍： Reliable data obtained from selective, sensitive and reproducible analysis of xenobiotics and biotics in biological samples is a fundamental and crucial part of every successful drug development program. The same principles can also apply to many other areas of research such as forensic science, toxicology and sports doping testing. The bioanalytical field incorporates sophisticated techniques linking sample preparation and advanced separations with MS and NMR detection systems, automation and robotics. Standards set by regulatory bodies regarding method development and validation increasingly define the boundaries between speed and quality. Bioanalysis is a progressive discipline for which the future holds many exciting opportunities to further reduce sample volumes, analysis cost and environmental impact, as well as to improve sensitivity, specificity, accuracy, efficiency, assay throughput, data quality, data handling and processing. The journal Bioanalysis focuses on the techniques and methods used for the detection or quantitative study of analytes in human or animal biological samples. Bioanalysis encourages the submission of articles describing forward-looking applications, including biosensors, microfluidics, miniaturized analytical devices, and new hyphenated and multi-dimensional techniques. Bioanalysis delivers essential information in concise, at-a-glance article formats. Key advances in the field are reported and analyzed by international experts, providing an authoritative but accessible forum for the modern bioanalyst.