European Research Council Awards Helmholtz Munich with Highly Endowed Funding
Two newly acquired ERC Advanced Grants support the cutting-edge research of Munich Helmholtz scientists Heiko Lickert and Fabian Theis. The researchers are international stars in the fields of diabetes and artificial intelligence. The funding will enable them to realize novel solutions for a healthier society in a rapidly changing world even faster and with greater efficiency.
“Advances in medicine are only possible thanks to world-class research and long-term funding. It is the only way we can turn groundbreaking discoveries into sustainable solutions for patients. The new ERC Advanced Grants will not only massively accelerate crucial projects of two of our outstanding scientists at Helmholtz Munich, but also recognize the societal relevance of our research," says Helmholtz Munich CEO Matthias Tschöp.
ERC Advanced Grants are endowed with up to 2.5 million euros for a period of 5 years. The European Research Council awards these grants to outstanding top researchers who distinguish themselves by the originality and significance of their research contributions and who can demonstrate a considerable number of research results in the last 10 years.
Helmholtz Munich has received 46 ERC grants to date, making it one of the most competitive institutions in the international landscape.
The newly awarded projects at a glance:
Heiko Lickert, Diabetes:
Currently no drug treatment can stop the progression of diabetes, a disease characterized by the loss or dysfunction of insulin-producing beta cells in the pancreas. With his ERC grant “BetaRegeneration”, Heiko Lickert will decipher cellular and molecular mechanisms of beta cell protection and regeneration. Based on the previous identification and validation of known and novel therapeutic targets and combinatorial pharmacology, he will explore new avenues of targeted and combinatorial beta cell protection and regeneration. If successful, BetaRegeneration will initiate a paradigm shift from symptomatic to causal diabetes therapy.
Fabian Theis, Computational Health:
In molecular cell biology, we aim to understand cells. To do so, we arguably want to know a cell’s behavior under all perturbations. This classical path in cell biology can be taken anew when reading out the internal state in unprecedented detail using single-cell genomics. With his ERC grant “DeepCell”, Fabian Theis will combine single-cell genomics with machine learning to systematically model a cell’s behavior under perturbation, focusing on the largely untouched area of drug-induced perturbations with single-cell readouts. If successful, it will allow optimal treatment predictions in new cell types. DeepCell thus opens up the possibility of in silico drug screens, with the potential to expedite drug discovery and impact clinical settings.