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Xyall has attracted a Series B investment of 6 million euros to accelerate the commercialization of its automated tumor dissection systems. The funding comes from a consortium led by Health Investment Partners (HIP). Also participating are existing investors Sioux Technologies, the Brabant Development Agency (BOM) and several private investors.
Selecting tumor tissue and cell samples for molecular diagnostic testing is predominantly still a manual, labor-intensive step with a risk of error and cross-contamination. Current practice involves pathologists pen-marking regions of interest. Using visual assessment, lab technicians then translate these ROIs into dissection slides, manually scraping the tissue and placing it in small containers. The worldwide shortage of such specialists puts additional pressure on clinical labs.
Co-located in Sioux’s Eindhoven HQ, Xyall enables molecular pathology laboratories to fully automate their tumor tissue dissection workflow. Its first solution, the Tissector High Throughput System, was launched in 2021. The startup has already sold several of these systems to large, commercial labs in the US, with the first being fully operational since March. Later this year, Xyall will launch its compact Tissector Table Top System aimed at hospital-based molecular pathology. For its solutions, the company has developed its own technologies in the areas of precision movement, medical robotics and image registration.
“The increase in new therapies is driving up demand for molecular diagnostic tests to inform treatment decisions for cancer patients. These tests require a consistently high sample quality and efficiency that’s difficult to achieve with the current way of working,” explains Xyall CEO Guido du Pree. “Clinicians and lab scientists have been calling for faster and more accurate tissue dissection so that precision medicine could become a reality. We provide the missing link by delivering fully automated tissue dissection solutions that enable a more efficient, standardized and more accurate workflow.”
