Advanced data analytics tools are used by industry to find the golden nuggets in historical data, to aid in process development, to fine-tune production, and to achieve long-term improvements in product quality and throughput.
Advanced data analytics tools are used by industry to find the golden nuggets in historical data, to aid in process development, to fine-tune production, and to achieve long-term improvements in product quality and throughput. Four key stages of data analytics can be seen as being part of a data analytical continuum. Handling those key stages diligently by using advanced data analytics tools is expected to give manufacturers a competitive edge.
Read this article from in Pharmaceutical Technology’s Biologics and Sterile Drug Manufacturing 2018 eBook.
Pharmaceutical Technology
eBook: Biologics and Sterile Drug Manufacturing 2018
Vol. 42
May 2018
Pages: 14–18
When referring to this article, please cite it as L. Eriksson and C. McCready, "Characterizing a Bioprocess with Advanced Data Analytics," Pharmaceutical Technology Biologics and Sterile Drug Manufacturing eBook (May 2018).
Lennart Eriksson, PhD, is senior lecturer and data scientist, lennart.eriksson@sartorius-stedim.com, and Chris McCready is lead data scientist, both at Sartorius Stedim Data Analytics.
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