In 2008, melamine in infant formula forced laboratories across three continents to verify a compound they had never monitored. Non-targeted analysis using LC/GC-HRMS handles these cases. But when findings trigger regulatory action, reproducibility becomes operational: can an independent laboratory repeat the analysis and reach the same conclusion? We assessed 103 tools (2004-2025) against six pillars drawn from FAIR and BP4NTA principles: laboratory validation (C1), data availability (C2), code availability (C3), standardised formats (C4), knowledge integration (C5), and portable implementation (C6). Health contributed 51 tools, Pharma 31, and Chemistry 21. Nine in ten tools shared data (C2, 90/103, 87%). Fewer than four in ten supported portable implementations (C6, 40/103, 39%). Validation and portability rarely appeared together (C1+C6, 18/103, 17%). Over twenty-one years, openness climbed from 56% to 86% while operability dropped from 55% to 43%. No tool addressed food safety. Journal data-sharing policies increased what authors share but not what reviewers can run. Tools became easier to find but harder to execute. Strengthening C1, C4, and C6 would turn documented artifacts into workflows that external laboratories can replay.
翻译:2008年,婴幼儿配方奶粉中的三聚氰胺事件迫使三大洲的实验室去验证一种从未监测过的化合物。基于LC/GC-HRMS的非靶向分析方法正是为此类情况而生。然而,当研究发现触发监管行动时,可重复性便具有了操作意义:独立实验室能否重复该分析并得出相同结论?我们依据FAIR与BP4NTA原则提炼的六大支柱,对103种工具(2004-2025年)进行了评估:实验室验证(C1)、数据可用性(C2)、代码可用性(C3)、标准化格式(C4)、知识整合(C5)以及可移植实现(C6)。其中,健康领域贡献了51种工具,制药领域31种,化学领域21种。十分之九的工具共享了数据(C2,90/103,87%)。支持可移植实现(C6)的工具不足十分之四(40/103,39%)。验证性与可移植性同时具备的情况更为罕见(C1+C6,18/103,17%)。在二十一年间,开放性从56%上升至86%,而可操作性却从55%下降至43%。没有一种工具专门针对食品安全问题。期刊的数据共享政策增加了作者共享的内容,但并未提升评审者可运行的程度。工具变得更容易查找,却更难以执行。加强C1、C4和C6,方可将已记录的成果转化为外部实验室能够复现的工作流程。