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Process Advancing Medicine
  • Dublin
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Multivariate Data Analysis

Complex interrelated datasets | actionable insights | CPP vs. CQA | manufacturing troubleshooting | process characterization | DoEs | find breakthroughs faster

Today’s process development and manufacturing operations produce massive amounts of information that require new tools, like multivariate data analysis, to extract relevant information from complex and interrelated datasets.  

We use MVDA to unearth actionable insights from the datasets we create during process development and we also use it to review historical production information when we tackle a challenging manufacturing issue. By more clearly understanding the interactions between process variables and critical quality attributes across our datasets, we find optimization breakthroughs faster and solve technical challenges without running experiments. 

We also use MVDAs during process characterization activities and on the DoEs that we run, ensuring that a full statistical analysis is deployed against the precious data we collect, helping us make better process development decisions that facilitate speed through your pipeline.