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Case Study

Unlocking CMC process data for predictive analytics

Predictive models can dramatically improve drug production, but they require large-scale, contextualized datasets. At a top 25 biopharma, data scientists working in chemistry, manufacturing, and controls (CMC) were stuck. They couldn't use process data (collected by PharmaMV software) to build these models because it wasn't optimized for predictive analytics.

The biopharma partnered with TetraScience to liberate this trove of valuable data. The solution uses the Tetra Scientific Data and AI Cloud™ to automatically replatform and engineer data from PharmaMV into AI-native Tetra Data.

Now, the data scientists can:

  • Search and assemble contextualized data rapidly
  • Access AI-native data for advanced analytics and modeling of drug production

Read the customer story to learn more.

Case Study
Unlocking CMC process data for predictive analytics

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