Lipotype and Nestlé Institute of Health Sciences collaborate on lipidomics research

Joint research project reveals robustness of Lipotype technology

Lipotype, a Max-Planck spin-off company, and the Nestlé Institute of Health Sciences (NIHS), will collaborate to employ the innovative Lipotype Shotgun Lipidomics Technology to analyse lipids in blood for nutritional research.

Recently, Lipotype and NIHS jointly published results of the robustness of the Lipotype technology. Lipotype envisions a future use of its technology in clinical diagnostics screens to establish reliable lipid diagnostic biomarkers.

The purpose of this collaboration is to enable NIHS to use the Lipotype Shotgun Lipidomics Technology for lipid analysis. The mass spectrometry based Lipotype technology covers a broad spectrum of lipid molecules and delivers quantitative results in high-throughput. The Nestlé Institute of Health Sciences uses this technology platform for nutritional research. NIHS is a specialised biomedical research institute and is part of Nestlé’s global research and development network.

During the collaboration, Lipotype and NIHS conducted a joint research project and demonstrated that the Lipotype technology was robust enough to deliver data with high precision and negligible technical variation between different sites.

In addition, important features are the high coverage and throughput, which were confirmed when applying the Lipotype technology. Lipotype envisions these as important features, required for future use in clinical diagnostics screens to establish and validate reliable lipid diagnostic biomarkers.

The results were recently published in the European Journal of Lipid Science and Technology.

Lipotype is a spin-off company of the Max-Planck-Institute of Molecular Cell Biology and Genetics in Dresden, Germany. Prof. Kai Simons, CEO of Lipotype, explains: 'We developed a novel Shotgun Lipidomics technology to analyse lipids in blood and other biological samples. Our analysis is quick and covers hundreds of lipid molecules at the same time. Our technology can be used to identify disease-related lipid signatures.'

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