Conference Dates

September 17-21, 2017


Continuous and intensified bioprocessing is attracting much attention from biopharmaceutical companies seeking to maximize the efficiency of their manufacturing assets. Continuous and intensified bioprocessing promises smaller facilities, reduced scale-up risk, more consistent product quality and higher throughputs. However, there are still many (technical) challenges for practical implementation of intensified and continuous bioprocesses. In the upstream processing, tools for high throughput intensified and continuous cell culture development are limited, furthermore at 2000 L scale many single use bioreactors may not be suitable to support the high cell densities required for intensified processing. Furthermore, current cell retention systems are expensive, suffer from product sieving and long term blocking effects. In addition, clarification of extremely high cell density cell cultures is challenging. In the downstream processing, to deal with the higher yields, continuous unit operations, such as MCC product capture, are finding its way into manufacturing. Although flow-through polishing steps with e.g. membrane adsorbers are receiving substantial attention, scalability has been challenging. Furthermore, robust solutions for continuous low pH viral inactivation, continuous virus filtration and continuous diafiltration need further development. When interconnecting unit operations into a continuous process, advanced process control tools need to be developed to balance flows between the unit operations and allow feedback/feedforward control based on data rich inputs from PAT tools. Here we will discuss the some of the latest solutions to address these issues, including SUBs designed for extreme cell densities up to 2000 L scale, retention systems that address product sieving issues, clarification of extreme cell density harvests, scalable Membrane Adsorbers in cassette format, PAT tools and process automation, and show real life examples and added value of these solutions with cost modeling data

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