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University of Graz News Electrons and AI: New approaches to the search for new medicines

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Tuesday, 24 March 2026

Electrons and AI: New approaches to the search for new medicines

Four people in white lab coats are standing side by side in a bright chemistry laboratory. Their faces have been obscured. They are looking towards the camera; three have their arms hanging by their sides, whilst one person has their arms crossed. To the left and right, laboratory equipment, shelves, cables and several labelled bottles can be seen; daylight streams into the laboratory through large windows in the background. ©Uni Graz/Angele

Eduardo Rial-Rodriguez, Gabriele Laudadio, Florian Wagner and Oliver Kappe are using AI in the search for new drugs. Photo: University of Graz/Angele

Researchers at the University of Graz are revolutionising the development of new medicines by combining electrochemistry and artificial intelligence. Thanks to smart optimisation, the search for new active ingredients will in future be faster, more sustainable and safer.

A chemistry laboratory full of delicate powders and liquids is often the starting point in the search for new medicines. This is because discovering new active ingredient molecules requires complex reaction chains involving substances that can be highly problematic. An alternative to this is electrochemistry. It uses electrons to trigger chemical reactions and thus specifically produce new molecules that could later be used in medicines.

That sounds simple, but it is very challenging, as Gabriele Laudadio explains: “It’s like a highly complex jigsaw puzzle. We have to optimise a multitude of parameters.” What are the right electrodes, and what current strength is required? The researcher at the Institute of Organic Chemistry at the University of Graz aims to solve this puzzle. “To do this, we have to carry out hundreds of trials using the trial-and-error method until we succeed.”

AI-Optimiziation

To improve this process, he is now taking a new approach together with scientists from the Research Centre for Pharmaceutical Engineering (RCPE) and Merck KGaA: combining chemistry with artificial intelligence. Using what is known as Bayesian optimisation, the series of experiments is optimised to such an extent that only 20 to 30 attempts are required. But it is not just the time spent in the laboratory that is reduced. “We also gain certainty that we have found the optimal conditions for our experiment,” explains Laudadio.

“We have been able to prove that this approach works and can actually produce molecules in this way.” Numerous further steps and test series are still required before drugs can be produced using this method. But: “This method represents a huge step forward for the development of new active ingredients,” the researcher is convinced.

This process is not only faster, but also much more environmentally friendly and safer than the previous approach. There is no hazardous waste and energy consumption is reduced. “Very soon we will have drugs in initial clinical trials that have been developed using AI systems. We are currently witnessing the beginning of a scientific revolution,” Laudadio is convinced.

Interested? You can gain an insight into the world of molecules through a Bachelor’s degree in Chemistry, Pharmaceutical Sciences or Molecular Biology.

The Paper 

Electrochemical self-optimization for the synthesis of densely functionalized molecules; Eduardo Rial-Rodríguez, Florian L. Wagner, Thomas Fuchß, Alena Sommer, Johannes Krieger, Hans-Michael Eggenweiler, C. Oliver Kappe, Gabriele Laudadio. https://doi.org/10.1016/j.chempr.2026.102952

created by Roman Vilgut

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