PhenoCycler-Fusion 2.0
PhenoCycler ® -Fusion 2.0 is the fastest solution for spatial biology researchers who need to achieve the quickest route to results. Trusted by top academic and industry leaders, this next-generation platform sets the pace for groundbreaking spatial discoveries.
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Great images, easy workflow.
Fluourescent IHC Microscopy / Highly Multiplexed Microscopy
It is a very easy to use implementation of codex and highly multiplexed microscopy. The software handles a lot of the previously manual setup, and the images speak for themselves. Additionally, the software platform handles image processing concurrently to acquisition in the background, which speeds up the analysis pipeline and reduces memory needed for raw tile images and intermediate files. All in all the platform is quick and fairly consumer friendly.
Review Date: 24 Mar 2023 | Akoya Biosciences
Powered by high-speed imaging and proprietary barcoding technology, PhenoCycler-Fusion 2.0 introduces multi-slide automation with rapid fluidics establishing itself as the fastest spatial biology solution. These advanced capabilities amplify your ability to uncover more discoveries, faster.
Key Benefits:
- The fastest: The fastest spatial biology solution capable of imaging 1 million cells in 10 minutes with faster than ever cycling
- Scalable Plexing: Detect 100+ biomarkers while preserving tissue integrity using barcoding technology
- High Throughput: Maximize throughput without imaging area or plex constraints; effortlessly phenotype 40 samples at 20 plex in just one week
- Unmatched Content: Design your desired panels from an extensive database or get started with ready-to-use PhenoCode™ Discovery Panels
Key Features:
- Whole-slide scanning: multi-slide automation and dual panel analysis
- Tissue formats: Whole-slides FFPE and Fresh Frozen; Tissue sections and microarrays
- Multiplexing capabilities: Supports 100+ biomarkers depending on barcode compatibility
- Speed (1.5 cm x 1.5 cm): 25 minutes per cycle
- File format: Algorithm ensure high-quality spatial images in gigabyte-sized files, streamlining research
