Aggregation of Raw Material Data for Predictive Analysis in Biomanufacturing

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Aggregation of Raw Material Data for Predictive Analysis in Biomanufacturing  

ABOUT

The Raw Material Data Analytics project seeks to apply data analytics to multi-company aggregated raw material data. We use a case study approach, narrowly focused on specific critical raw material components, to develop methods that can be applied to other raw materials.

The pilot case studies for this effort are:

  • Trace Elements – Metal ions present in salts used to prepare buffers and cell culture media can negatively impact the process or product.  This workstream seeks to collect trace element from a variety of key salts and sugars to be able to study trends over time.
  • Database of Raw-Material Driven Process Variability – The goal of this workstream case study is to ensure that manufacturers have complete and current information on variability in raw materials used in their processes by curating a comprehensive and searchable database of current literature with the goal of expanding into proprietary case examples.
  • Leachables Fate Map – Extractables and leachables from polymeric materials can negatively impact the process or product.  This case study seeks to build an aggregated database of extractable information with the ultimate goal of collecting leachable and process information to map the fate of the leachables in a process.

See all BioMAN research projects

 

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