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Deepcell Announces Successful Installation of the First Commercial REM-I Platform

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Deepcell, a pioneer in artificial intelligence (AI)-powered single cell analysis to fuel deep biological discoveries, today announced the first commercial placement of the REM-I platform at Erasmus Medical Center in Rotterdam. This commercial milestone follows placements of pre-commercial instruments at laboratories in Europe and the U.S. for Beta testing. In addition, the company announced plans to share new data and customer experiences with the REM-I platform at upcoming scientific meetings. These include the Congress of the International Society for the Advancement of Cytometry, CYTO 2024, taking place May 4-8, 2024, in Edinburgh, Scotland and the American Association of Immunologists annual conference, Immunology 2024, taking place May 3-7, 2024, in Chicago, Ill.

“With the full commercial launch of the REM-I platform, we look forward to seeing the broad range of scientific questions our customers tackle with the ability to combine single cell imaging, sorting, and high-dimensional analysis,” said Maddison Masaeli, Ph.D., co-founder and chief executive officer and Deepcell. “We’ve already seen tremendous interest in the REM-I platform and look forward to sharing more data from our platform at AAI and CYTO."

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The REM-I platform is a high-dimensional single cell morphology solution which comprises the REM-I benchtop instrument, an AI Foundation Model, and the Axon data suite. By bringing together single cell imaging, sorting, and high-dimensional analysis, the REM-I platform will catalyze new methods of discovery in a wide range of fields including cancer biology, developmental biology, stem cell biology, gene therapy, and functional screening, among others.

“Deepcell’s technology will support our research in onco-cardio and transplantation rejection, enabling us to apply artificial intelligence to study immune and cancer cells and their functions in greater detail,” said Peter van der Spek, Ph.D., Professor, Department of Pathology & Clinical Bioinformatics, Erasmus Medical Center. “Being able to understand cell morphology in this way, rather than using predefined parameters, will enable new discoveries not possible with previous research techniques.”