Element Biosciences, a U.S. genetic analysis equipment company and major shareholder of Samsung Electronics, is unveiling next-generation genomic analysis technology in Seoul. Samsung is also exploring new business opportunities in precision medicine by integrating Element's sequencing and multi-omics technologies with its AI and medical device sectors.
Samsung announced that Element will hold its global roadshow, "Shift Your Science," at the RYSE Hotel in Seoul on October 20. The event will continue in San Diego and Boston in the U.S., as well as in Munich, Germany, and Stockholm, Sweden.
During the event, Element will showcase its next-generation high-throughput sequencer, "Vitari," and its multi-omics solution, "Cytos." CEO Molly He and CTO Michael Prebble will be in attendance.
Vitari is a benchtop sequencer capable of processing up to 10 billion reads and 3TB of data at once. The company claims it can maintain an analysis accuracy of 99.99% while reducing the cost of genomic analysis to $100 per individual. Shipments are expected to begin in the second half of this year.
Cytos is a multi-omics solution that simultaneously analyzes various biological information, such as morphology, protein expression, and transcriptomics, from a single cell. It is designed to facilitate the comparison of cellular changes in drug development processes.
Element reported a 40% increase in revenue last year and has installed over 450 systems in more than 40 countries worldwide. The company is rapidly expanding its business scope beyond genomic analysis equipment to include multi-omics.
In June, Samsung invested an additional $175 million in Element's Series E funding, securing its position as the largest shareholder. This marks Samsung's second investment following its Series D funding in 2024. Samsung plans to target the precision medicine market by combining Element's genomic analysis technology with its capabilities in AI, medical devices, and digital health.
An Element representative stated, "We will support researchers in answering biological questions that have been difficult to address with existing technologies, based on high-quality experimental data."
* This article has been translated by AI.
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