Helmholtz Munich Receives Grant to Improve Stem Cell Islet Transplants for Type 1 Diabetes
Helmholtz Munich has been awarded a prestigious grant from Breakthrough T1D, a leading global type 1 diabetes (T1D) research and advocacy organization, to enhance the effectiveness of stem cell-derived islet transplantation for T1D. By integrating artificial intelligence (AI) and machine learning (ML) approaches, the project aims to tackle a critical hurdle in diabetes treatment – the early loss of transplanted beta cells due to ischemic stress.
Advancing Stem Cell Therapies for Diabetes
Stem cell-derived islet therapies hold tremendous promise for treating T1D, potentially offering long-term solutions that reduce dependence on insulin injections. These therapies have made great progress in the last several years, however challenges remain. One challenge is that a significant portion of beta cells are lost due to inflammatory and ischemic stress following transplantation, limiting the effectiveness of the treatment. By leveraging AI and ML, researchers at Helmholtz Munich and the Technical University of Munich (TUM) aim to identify the molecular mechanisms behind this cell loss and develop targeted interventions to improve transplant success.
Harnessing AI for Beta Cell Survival
“By analyzing vast biological datasets with AI, we can pinpoint key stress markers that threaten beta cell survival and develop targeted interventions to improve transplantation success,” explains Prof. Fabian Theis, Head of the Computational Health Center at Helmholtz Munich and Professor for Mathematical Modeling of Biological Systems at TUM. To achieve this, researchers are integrating computational modeling with laboratory experiments. “An AI-powered predictive model allows us to simulate the challenges beta cells encounter post-transplantation, enabling us to test potential treatments virtually before confirming their effectiveness in the lab,” Theis adds.
The research unfolds in several stages. First, AI tools will map cellular changes occurring during early transplantation, highlighting critical pathways for beta cell survival. Large-scale experimental screenings will then explore pharmaceutical and genetic interventions that could enhance cell resilience. The most promising approaches will be validated in preclinical models by transplanting both primary and stem cell-derived islets into mice. Throughout the process, AI models will be refined with experimental feedback, continuously improving predictions for optimal transplantation strategies.
From AI Models to Real-World Solutions
By minimizing early-stage beta cell loss, this AI-driven approach aims to make stem cell-derived islet transplantation a viable treatment for type 1 diabetes. Maximizing the use of limited donor material, addressing safety concerns, and accelerating clinical translation are key priorities. “This method allows us to precisely tailor interventions, increasing both the efficiency and safety of transplantation,” says Prof. Heiko Lickert, Director of the Institute of Diabetes and Regeneration Research at Helmholtz Munich and Professor for Beta Cell Biology at TUM. “Ultimately, we aim to establish a long-term solution for type 1 diabetes, bringing us closer to a functional cure.”
“Breakthrough T1D is focused on finding cures for type 1 diabetes with cell therapies as a key priority area. We look forward to the opportunity that AI models may provide to significantly accelerate the pace of research for islet replacement therapies. These new tools have the potential to enable discoveries more quickly, identifying patterns and signatures in the data that might otherwise be missed,” says Nicholas Mamrak, scientist at Breakthrough T1D.
