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Auditing Reproducibility in Non-Targeted Analysis: 103 LC/GC--HRMS Tools Reveal Temporal Divergence Between Openness and Operability

Published: December 23, 2025 | arXiv ID: 2512.20279v1

By: Sarah Alsubaie, Sakhaa Alsaedi, Xin Gao

Potential Business Impact:

Makes lab tests reliable for food safety.

Business Areas:
Test and Measurement Data and Analytics

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.

Country of Origin
πŸ‡ΈπŸ‡¦ Saudi Arabia

Repos / Data Links

Page Count
26 pages

Category
Computer Science:
Computational Engineering, Finance, and Science