Chair of Bioprocess Engineering at BioTalk – Biological Manufacturing Excellence

BioTalk is a leading annual meeting which brings together some of the most influential senior executives across the world’s Pharma & Bio-pharmaceutical Manufacturing community. The Talk will look at how companies and leaders are driving change within the industry to achieve manufacturing excellence through a series of key notes, workshops, discussions and debates.

Highlights

• Downstream/Upstream Process Technology PlatformsDigitalizationSpecialised cell culture media
• Single-use & Disposable TechnologiesSeparation and Purification TechnologyVirus Filtration Process
• Smart Manufacturing Technologies – Tech. TransferFacility Management & IntegrationLean/Operational

Agenda (PDF)
Speakers
Participants

On September 20th at 14:50-15:20, Prof. Dr. Peter Neubauer, Chair of Bioprocess Engineering, Technische Universität Berlin (a Bio-PAT member) will give a talk on “ Realization of automated learning for bioprocess development by integrating robot-driven well-controlled parallel cultures, analytical technologies, and modelling“.
Content:
– Automated laboratories become state of the art. However, to gain a maximum of knowedge from the experiments, implementation of a closed loop learning framework is a key with (i) integrated real-time high-throughput analytics, (ii) proper automated real-time handling of the generated data to control the running experiments. The data should follow the FAIR (Findable Accessible Interoperable Reusable) principles, (iii) Integration of a model-based tool tailored for the small data problem, real-time use of mathematical models that can deal with the low data/complexity ratio that characterizes bioprocess development.
– The KIWI-biolab aims to solve these issues with an integrative and collaborative approach. Analytical technologies are connected with high throughput cultivation systems and with tools for automated documentation and standardization of experimental/computational workflows. AI approaches are adapted to High Throughput Bioprocess Development by the use of mechanistic models in combination with Machine Learning algorithms (hybrid models). The strength and relevance for scalability of this approach is documented by examples from bacterial protein expression projects.

Further, there will be a small lab tour showing the KIWI-biolab, the highthroughput and fermentation facilities as well as process analytical technologies.

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