Alois Rainer, Federal Minister for Agriculture, Food and Home Affairs, visited the German Federal Institute for Risk Assessment (BfR) in Berlin-Marienfelde today, 7 July 2026. The Minister’s programme included attending the Institute’s General Assembly, a meeting with the BfR management and a tour of the BfR experimental farm. The main topics of discussion were consumer health protection and the role of scientific policy advice. The BfR is a scientifically independent research institute operating under the Ministry’s remit.

On the occasion of his visit, Federal Minister Alois Rainer stated: “Close cooperation between research and policy is essential for identifying risks at an early stage and taking targeted countermeasures. Through its work, the BfR makes a significant contribution to ensuring that food, substances and products in Germany and Europe are safer. At present, hybrid threats to critical infrastructure are at the top of the list of potential – and, unfortunately, very real – risks. Of course, our food and feed can also become targets of attack. We want to protect people from this hazard as effectively as possible. We are in the process of establishing key structures and significantly strengthening cooperation between the federal government and the German federal states in the domain of food and feed defence. We are also driving forward activities in this domain at federal level.”

 “The timely identification of new health risks to the population is one of the BfR’s key tasks,” said BfR President Prof. Andreas Hensel. “Scientific assessment, policy advice and public information are the BfR’s key tools in this regard. Current issues such as microplastics and PFAS compounds – also known as ‘forever chemicals’ – are causing concern among many people. They are examples of just how important it is for the BfR to advise policymakers and educate the public on a scientific basis.”

Researchers from the Technion and Tel Aviv University have developed BetaDescribe, an AI system that translates protein sequences into natural-language descriptions of their functions and properties. Reported in PNAS, the system uses a generative AI approach with built-in verification mechanisms to infer protein function even when proteins are not closely related to previously characterized ones. By helping interpret the vast number of uncharacterized proteins in nature, BetaDescribe could accelerate biological research, drug discovery, and advances in biotechnology and agriculture.