27 Sep 2022  

5.30-6.30pm SGT | Online 

Synopsis:

Biopharma industry is facing three challenges of reducing development time, cost savings as well as quality assurance. Data Analytics as a proven technology is used across the entire biopharma value chain – from screening in early process development all the way to monitoring and control in commercial manufacturing. What we present here is the breakdown of each of the PD and CM steps and which type of Data Analytics best serve those areas. For example, both Design of Experiments (DOE) and Multivariate Data Analysis (MVDA) help to facilitate scale-up and scale-down studies as QBD approach whereas MVDA and real-time MVDA as PAT tools are best suited to perform root-cause analysis during pilot and commercial manufacturing. Examples from upstream, downstream, as well as final fill and finish bioprocessing steps are presented to show the value proposition of Data Analytics in face of the three challenges. 

Led by: 

David Wang, Senior Data Scientist, Sartorius

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