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Data-Driven Quality Control

Quality Control Workflows for Chromatography Data Analysis

Case Studies

As a process for separating components of a sample, chromatography is critical to modern pharmaceutical and biotech workflows. One challenge is the difficulty in aggregating data across multiple runs or across diverse in-house instrumentation. Manual data reporting and transformation between data formats are time-consuming and prone to errors.

Biopharma organizations are partnering with TetraScience to unlock the full value of chromatography data – and faster, more reliable quality control. 

Our case study – Data-Driven Quality Control – describes how TetraScience helped a top 15 global biopharma to improve chromatography data analysis. You'll learn about our automated quality control workflows for:

  • System suitability tests (SST)
  • Column degradation checks
  • Shelf-life for active pharmaceutical ingredients (APIs)

TetraScience ingested and processed high-performance liquid chromatography (HPLC) data into a FAIR format. 

Researchers saved an estimated 8 hours/week in manual data gathering, visual comparison and reporting. Our client was also able to use existing runs to predict failures before they occurred while resolving inefficiencies in communication.

Enhance Your Data-driven Quality Control  

Read our case study for an in-depth look at how Tetra Science has advanced chromatography data analysis in the cloud. We will review:

  1. Cost savings in manual labor and consumables
  2. Streamlined reporting between functions 
  3. Harmonized data adhering to FAIR principles
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