Biotech Data Modernization in Practice: Building a Connected View of Biotech Operations

A growing biotech company wanted to answer a practical manufacturing question: Why are some batches taking longer than others? The information needed to investigate the question already existed. Manufacturing information was in the Manufacturing Execution System (MES). Process conditions were captured by a historian. Laboratory results were in the Laboratory Information Management System (LIMS). Quality

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Data Modernization in Life Sciences: A Practical Roadmap for Pharma and Biotech

A biotech company may already have the data it needs to answer an important question. The problem is that the answer may be spread across five different systems. Consider one batch. The MES knows what happened during execution. The historian captures process conditions. LIMS contains laboratory results. The eQMS holds deviations and investigations. ERP contains

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Data integrity concept in GxP computer systems

Data Integrity in GxP Systems: Why It Matters and How to Get It Right

Data integrity remains a critical focal point for regulatory agencies overseeing the pharmaceutical and biotechnology industries. Ensuring data integrity is not merely a compliance requirement; it’s fundamental to patient safety, product quality, and operational efficiency. This article explores the significance of data integrity in Good Practice (GxP) systems, common challenges organizations face, and best practices

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Integrating Data Integrity Requirements into Quality Management Systems

Data integrity translates into the consistency, completeness, and accuracy of data. It is required in all aspects of biopharmaceutical development and manufacturing, including emerging technologies like block chain, as you introduce them into your Quality Management Systems. Consistency, standardization, and traceability are some of the many issues we face when it comes to data integrity. Once

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