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Metabolic Engineering enables new design chemicals

Without modern biotechnology, clothes that come out clean when washed at only 40 degrees Celsius would be inconceivable. Today, chemical substances are also being replaced by biotechnology in many other industrial areas, such as agriculture or cosmetics, but they still play a subordinate role compared with petrochemicals.


The product portfolio is too small; production is too expensive or difficult to scale up. A new field might help industrial biotechnology to achieve a breakthrough: synthetic biology, i.e. the reprograming of biological systems. Until now, the fact that new chemicals only reached commercialisation via expensive fundamental research was regarded as the bottleneck of this modern biotechnology. A challenge, which has now been taken up by the biotech start-ups, Zymergen and Arzeda. Instead of looking for suitable chemical solutions in biology, the companies manipulate the DNA of naturally occurring enzymes to manufacture the appropriate chemicals directly using fermentation.

This “metabolic engineering”, as it is known, is not carried out by people but by an automated process, which is based on Big Data, at a fraction of the current costs. Consequently metabolic engineering will open up new paths to industrial development and commercialisation of design chemicals.

Whereas only yesterday, development departments spent months researching a new chemical, in future, artificial intelligence will search for the most effective recipe in a fully automated process, which will only take a few weeks. The ultimate vision is the disruption of traditional production processes in the chemicals industry and the start of a post-petro era. 

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AI and sustainability: a new strategic area of activity

In the global debate about the risks to society posed by and the economic potential of artificial intelligence, two complementary lines of argument stand out in striving for specific approaches to a “sustainable” use of AI. Both topics are of relevance to all companies wishing to develop a long-term AI strategy. However, they are usually not differentiated sufficiently in practice. An attempt at clarification by Andreas Neef, Managing Partner of Z_punkt.


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