ZEISS Research Microscopy Solutions and Alpenglow Biosciences have announced a multi-phase partnership to build an inverted light-sheet microscope and accompanying bioinformatics pipeline aimed at clinical pathology.
The companies say the joint system will digitize entire tissue samples without a microtome, generate 3D images and feed them into a GPU-accelerated analytics engine. In press materials, ZEISS and Alpenglow predict the workflow could deliver “clinically impactful insights at the same time or faster than traditional pathology” and eventually provide AI-enabled decision support that predicts treatment response and prognosis.
While the expectations are ambitious, the press release did not provide a detailed time table for the firms’ expectations for regulatory clearance, clinical trials or commercial launch.
Aim to unlock the full data potential of biopsies
Alpenglow chief executive Dr. Nicholas Reder called the deal marks “a significant step” in its goal to analyze the “information contained in every single cell of a biopsy, rather than relying on just a small fraction of the tissue.” Dr. Michael Albiez, head of ZEISS Research Microscopy Solutions, said pairing ZEISS’s light-sheet hardware with Alpenglow’s software “enables the creation of powerful, fully integrated workflows for 3D pathology, from sample to analytics.”
Planned application areas include enhanced 3D pathology workflows for entire tissues, translational research to track immune-cell infiltration and novel biomarkers, drug-development studies on mechanism of action and patient selection, and AI tools for clinical decision support
The partners also claim the system will be “fastest whole tissue imaging” technology, citing the contributions of ZEISS engineering and its Arivis visualization platform combined with Alpenglow’s data-processing and AI prowess.
From thin to volumetric
If the technology reaches routine use, it could shift pathology from thin-section slides toward volumetric analysis. For now, the collaboration adds to a crowded field of companies betting on 3D imaging and machine learning to improve diagnostics. Major players such as Philips Healthcare, Leica Biosystems, and Roche are heavily invested in digital and AI-driven pathology. Additionally, a growing number of startups and specialized companies like Paige and Ibex Medical Analytics are influential in the domain.
