How DOE and MVDA Improved Scale-Up Performance at a CDMO

Viral based therapies continue to show clinical promise, but they bring with them added bioprocessing complexity. Scale-down models can provide a high-throughput, cost-effective environment where scientists can test the parameters necessary to navigate complexity and mitigate risk during scale up.

With the right toolset, process developers can survey more and develop deeper process-level understanding that can drive down the cost of manufacturing these life-changing therapies.

Read our white paper to learn more about:

  • How to build a stepwise approach to screening, optimization, and sensitivity testing using intuitive Design of Experiments (DOE) software to guide development
  • How DOE and multivariate data analysis (MVDA) combine to generate holistic and accurate models
  • How to overcome scaling challenges with an iterative Quality by Design (QbD) strategy that leverages scalable bioreactor systems and powerful data analysis tools

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