Industrial biotechnology utilises microorganisms or individual biomolecules such as enzymes in bioprocesses as the basis for the industrial production of chemicals, biopharmaceuticals or food additives. The key players are cells as living factories that can produce a desired product in large quantities in closed bioreactors. Developing bioprocesses in such a way that the biotechnological production of a product is optimised is very time-consuming and complex.

Specialist conference for the scale-up of bioprocesses

"Efficient bioprocess development forms the basis for a sustainable bioeconomy and the cost-effective production of therapeutics," says Peter Neubauer, Head of the Department of Bioprocess Engineering at Technische Universität (TU) Berlin. "Highly accelerated development cycles are only possible if we focus on completely new approaches and develop new technologies," says Neubauer. He is one of the world's pioneers in automated bioprocess development and has set up the Future Laboratory for AI-supported Bioprocess Development (KIWI-biolab), which is funded by the German Federal Ministry of Education and Research.

A major challenge in biotechnology is the scaling up of processes from a small laboratory bioreactor to "brewing" in huge steel containers. In 2009, Neubauer therefore initiated the BioProScale Symposium to create a platform where the latest trends in scale-up can be discussed. The event has since become a forum with international appeal for bioprocess engineering experts. Around 200 stakeholders from industry and science came to the Langenbeck-Virchow-Haus on the Charité campus in Berlin-Mitte from 9 to 11 April for the eighth edition, which was organised by TU Berlin together with Bio-PAT e.V. and BioProScale e.V..

Technology transfer

It became clear at the conference that digitalisation, automation and modelling now play a crucial role in all phases of bioprocess development. "Data science is the big trend in scale-up, and the coronavirus pandemic has given it another boost," says Emmanuel Anane in an interview with bioökonomie.de. In Denmark, he works for Fujifilm Diosynth Biotechnologies, a contract manufacturer for the pharmaceutical industry. Anane is involved in the production of biopharmaceuticals – such as antibodies – using hamster cells (CHO). These animal cells are usually cultivated in disposable bioreactors with a volume of 2,000 litres. "But when demand increases, processes in 20,000-litre steel tanks will become interesting". In order to simulate such increases in scale, Anane engages in technology transfer: "We transfer information from one context to another in order to simulate processes on an industrial scale using mathematical models."

One major challenge is the often incomplete data sets that customers supply to contract manufacturers. Artificial intelligence could provide a remedy, among other things. "AI-based algorithms could predict at which point in the bioprocess samples should be taken – that would be smart and extremely helpful for efficient data collection," says Anane. A team led by Frédéric de Lapierre from Munich University of Applied Sciences is also working with AI-based solutions. He presented a machine learning algorithm that automatically prepares the composition of the nutrient solution in a microbioreactor, checks growth and makes suggestions for improved media mixtures.