In regulated laboratory environments, the integrity of data depends on more than a generic life cycle. Traditional models fail to capture the diverse procedures across analytical workflows.

This article explores the necessity of a flexible analytical data life cycle, one that adapts to various processes—whether it’s observational testing or spectroscopic analysis. Drawing insights from regulatory guidance and practical examples, it outlines:

  • The difference between active and inactive data phases
  • The importance of sample management and preparation
  • Second-person review and short-term retention
  • Why flexibility is key in adapting to specific analytical contexts

Without this adaptability, labs risk data errors, integrity issues, and inefficiencies.

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Inspired by “A Flexible Analytical Data Life Cycle?” by R.D. McDowall in Spectroscopy, September 2018.