About us:
Germany's bioregions are regional initiatives to strengthen innovation in the field of biotechnology and related scientific fields such as medical technology, digital health and process engineering. The Working Group of Bioregions (AK Bioregio for short) has been in existence since 2004 and is the central network of these regional clusters in Germany. Around 25 members have joined forces to optimize and coordinate their regional activities in the interests of German biotechnology. The management of the working group is provided by the regions, the office of the working group has been located at BioDeutschland since 2009.
Our vision:
Biotechnology is one of the key technologies of the 21st century and is used on a large scale in a variety of products and services for the benefit of mankind and nature and is constantly being developed further. The technical use of biological processes will make a significant contribution to solving the global challenges of our century, in particular through better healthcare, sufficient food security, efficient energy supply and more environmentally friendly industrial production. Through the close networking of science, industry and administration in the bioregions, the Bioregio working group will develop biotechnology as one of the most important key technologies and contribute to making Germany one of the world's leading nations in biotechnology.
Our areas of activity/tasks:
- Meta-Networking: Promotion of innovation by connecting regional networks and clusters
- Biotech partnering: arranging partner inquiries between regional and international networks in the bioregions (broker function)
- Trend Radar: Analysis of trends in biotechnology, for example to identify potentially disruptive technologies or new business models at an early stage.
- Innovation promotion: Identification/enquiry of needs and development of possible solutions to reduce barriers to innovation (funnel function)
- Knowledge: Provision of know-how for political decision-makers
- Best practice: exchange and development of exemplary cluster models