Cloud-Clone pitches CBA kits as a way to turn standard flow cytometers into multiplex protein tools
Cloud-Clone Corp. says its Cytometric Bead Array kits let labs use existing flow cytometers for high-plex protein testing instead of buying dedicated multiplex systems. The company is targeting a global installed base it estimates at 150,000 to 200,000 instruments, with a new 36-plex panel and compatibility across major brands.
Why it matters: - Cloud-Clone is positioning CBA kits as a lower-cost alternative to dedicated multiplex detection platforms. - The approach is aimed at labs that already own flow cytometers but face bottlenecks from limited access to specialized multiplex instruments. - The company says the model reduces the need for outsourced testing, repeated sample splitting and new capital equipment purchases.
What happened: - Cloud-Clone Corp. introduced its Cytometric Bead Array technology as a way to run multiplex protein assays on standard laboratory flow cytometers. - The release was dated September 1, 2026, from Huston, Texas. - Cloud-Clone also announced a 36-plex neuro-endocrine-immune panel built on the same platform. - The company included a product page for more information: Cloud-Clone official website.
The details: - CBA technology uses fluor-encoded microspheres coated with capture antibodies for different analytes. - Mixed beads are incubated with samples to form bead-target-detection antibody complexes. - A flow cytometer identifies analytes through APC-based bead coding and reads protein levels through PE fluorescence intensity. - Cloud-Clone says the kits work on Beckman Coulter DxFLEX and CytoFLEX series, BD FACSMelody and FACSCanto series, Agilent NovoCyte series and Thermo Fisher Attune NxT. - The assays run on entry-level analytical through high-end sorting flow cytometers if APC and PE channels are available. - The APC-Cy7 channel is required for panels with more than 27 analytes. - The company says the assays need only 25 μL of sample volume. - Cloud-Clone says the assays reach pg/mL sensitivity and a dynamic range of 3 to 5 orders of magnitude. - The company says most samples do not need serial dilution retesting. - The 36-plex panel combines RAAS hormones ALD and AngII, cardiac markers ANP and BNP, sympathetic mediators EPI and NE, vascular endothelial factor EDN1 and Th1/Th2/Th17 cytokines in one reaction vessel. - Cloud-Clone says its assay components are produced in-house, including fluor-encoded microspheres and matched capture-detection antibody pairs. - The company says its antibody library exceeds 27,000 clones. - Each panel undergoes cross-reactivity testing, matrix-effect characterization and spike-recovery validation. - Typical spike recovery is 80% to 120%, with R² of at least 0.97, according to the release.
Between the lines: - The release is framed as an instrument-agnostic pitch for labs that already have flow cytometry hardware but not dedicated bead-array platforms. - Cloud-Clone is trying to turn a common cell-analysis instrument into a broader protein-quantification workflow, which could widen access to multiplex testing if performance holds up in practice. - The company also leans on supply-chain resilience, arguing that in-house component production reduces exposure to disruptions. - Cloud-Clone says major suppliers Beckman Coulter, BD, Agilent and Thermo Fisher Scientific held about 78.3% of the global flow-cytometry market in 2023, underscoring the size of the installed base it is targeting. - The company estimates global flow cytometer inventory at 150,000 to 200,000 units and says more than 23,000 new units shipped in 2025.
What's next: - Cloud-Clone says it will keep expanding its CBA panel portfolio and optimizing assay performance. - The company says it will continue supporting research into immune, cardiovascular, neuroendocrine and inflammatory disease mechanisms. - Researchers considering the platform will need compatible lasers and detection channels before running higher-plex panels.
Disclaimer: This article was produced by AGP Wire with the assistance of artificial intelligence based on original source content and has been refined to improve clarity, structure, and readability. This content is provided on an “as is” basis. While care has been taken in its preparation, it may contain inaccuracies or omissions, and readers should consult the original source and independently verify key information where appropriate. This content is for informational purposes only and does not constitute legal, financial, investment, or other professional advice.
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