(Rentschler Biopharma SE) - Predicting the process – A CDMO's journey to computational
Speaker: Walter Denk, Dipl. Math. - Group Lead Bioprocess Data Science Unit
For a CDMO, the efficient utilization of its manufacturing capacities can have the most crucial business impact. In the
past, many labor-intensive manual process steps were executed, to produce the client’s product with payment for every hour invested. Nowadays, CDMO’s who can offer the same or even better product
quality while reducing manual steps and wet lab activities will outperform those CDMOs lacking behind in digitalization and automation.
Additionally, more clients, especially bigger pharma companies, expect CDMOs to provide transparent access to the data captured during the development and
production process, in order to compare these with their in-house processes. Last but not least, regulators put new regulations in place, the pharmaceutical community is expected to respect, as
well as, to incorporate into their bioprocesses. That can also open up new development pathways for faster biopharmaceutical approval; provided you have the data to back up any claims to omit
certain process steps, for faster drug approvals.
Driven by these factors, Rentschler Biopharma SE is initiating a holistic approach for capturing, managing, and analyzing data that we produce every day during
biopharmaceutical production. We will reveal the vision of the Bioprocess Data Science Unit at our company, that aims to address these three key challenges. We will also discuss on how we are
planning to leverage this data infrastructure, not just to comply with external drivers, but also to improve and automate many internal processes for the benefit of our clients and their