DZL Scientists Fabian Theis and Herbert Schiller (DZL site Munich, CPC-M) and Boehringer Ingelheim have started a research collaboration to identify new avenues for the treatment of idiopathic pulmonary fibrosis. They could improve outcomes in people living with this severe and progressive lung disease. Supported by around 1 million euro in funding from Boehringer Ingelheim, the project will apply and further develop single-cell genomics techniques and AI models to analyze drug effects on cultured human lung tissue outside the body.<\/p>\n
Combining Experimental and Computational Expertise<\/strong><\/p>\n Idiopathic pulmonary fibrosis, short IPF, leads to scarring of lung tissue, resulting in a loss in lung function. This affects patients\u2019 ability to perform daily activities and can even be life-threatening. While current antifibrotic treatments can slow disease progression, there is a high remaining patient need with no treatments capable of stopping or reversing the disease available to date. This collaboration aims to help close this gap by developing a more physiologically relevant platform for drug discovery, using human lung tissue combined with single-cell transcriptomic analysis and AI models.<\/p>\n At the CPC-M\/Helmholtz Munich, two research groups are leading the collaboration: the\u00a0Research Unit for Precision Regenerative Medicine\u00a0headed by lung expert Prof. Herbert Schiller, and the\u00a0Institute for Computational Biology, led by biomedical AI specialist Prof. Fabian Theis.<\/p>\n The Schiller Lab has developed advanced methods to analyze drug effects at single-cell resolution in precision-cut human lung slices (hPCLS). This approach will now support pre-clinical testing of new anti-fibrotic candidates. \u201cBy working directly with human lung tissue and integrating advanced computational models, we hope to gain a detailed understanding of the cellular circuits driving fibrosis and identify novel ways to target them,\u201d says Schiller.<\/p>\n Meanwhile, the Theis Lab contributes its expertise in machine learning and biomedical AI. The team develops models that analyze and predict the effects of drug candidates at single-cell resolution. \u201cThis collaboration allows us to combine experimental biology and data science to better predict how potential drugs, and their combinations might behave in complex human tissues,\u201d Theis explains.<\/p>\n <\/p>\n