Blog Stop the Copy–Paste–Verify–Repeat Loop in GxP Bioanalytical Reporting Every regulated report begins the same way: you gather the data, enter it into a spreadsheet, transfer it to a document, verify it, and have someone else verify it again. Whenever there’s a change, this cycle repeats. In the second episode of our Expert Coffee Break…
Blog Long-term Study Archiving After Watson LIMS™: Key Insights for Regulated Bioanalytical Labs In a regulated bioanalytical lab, the work doesn’t end when a study is finalized — the data has to stay complete, retrievable, and compliant for many years to come. A recent up to data Expert Coffee Break brought together CEO Norbert Bittner…
Blog The Post-Merger Watson LIMS™ Problem: A Cost-Effective Path to Decommissioning A CFO/CIO guide to decommissioning legacy bioanalytical LIMS without compliance risk. Post-merger application rationalization moves quickly until it hits a GxP-regulated system. Both sides of a pharmaceutical M&A often run Watson™ LIMS, and neither environment appears safe to decommission without creating a compliance gap….
Blog Long-Term Retention of Bioanalytical Watson LIMS™ Studies: A Compliance-First Perspective Most bioanalytical labs running Watson LIMS™ have never made a conscious decision about archiving. They have simply deferred. What 21 CFR Part 11 and EU GMP Annex 11 actually require, and why format independence is a regulatory posture, not an IT preference. Executive Summary The majority…
Blog Four Dimensions of Time Savings in GxP Bioanalytical Study Reporting With rising expectations under ICH M10, FDA Part 11, and EMA guidelines, bioanalytical labs face growing pressure: more data, more documentation, and less room for error. Manual reporting still risks transcription mistakes, slows QC cycles, and complicates inspection readiness.This article highlights four dimensions where automation drives measurable…
Blog Leveraging AI in GxP Environments: A Context-First Approach to Bioanalytical Data Management In regulated bioanalytical laboratories, the promise of artificial intelligence has often seemed at odds with the stringent requirements of GxP compliance. Traditional approaches to AI implementation face significant hurdles: data privacy concerns, validation challenges, and the complexity of maintaining compliance when using…
