PhenoCycler-Fusion 2.0, formerly known as CODEX®, is a breakthrough platform for spatial proteomics—offering ultrafast, multiplexed imaging of intact tissues with sample preservation. By combining the scalable automation of PhenoCycler with the high-resolution imaging of PhenoImager (formerly Phenoptics™), researchers can now access comprehensive single-cell data at scale—ideal for both discovery and translational studies.
Scalable Spatial Phenotyping Solutions
From Discovery to Clinical Research
Akoya’s integrated spatial biology ecosystem is designed to support research at every stage—from early discovery to regulated clinical applications. PhenoCycler-Fusion 2.0 sits at the core of this platform, enabling scalable workflows across a range of sample types and study sizes.
PhenoCycler-Fusion Technology Highlights
DNA-barcoded, cyclical imaging without sample damage
This technology uses DNA-tagged antibodies in a one-step staining protocol, followed by iterative binding and imaging cycles. Each round reveals new biomarkers while preserving tissue for further use.
Instrument Features
Combining speed, flexibility, and precision in one platform
PhenoCycler-Fusion 2.0 is designed for full-slide, high-speed imaging. With support for multiple slides and ultra-fine resolution, it offers flexibility and scale for diverse experimental designs.
Assays & Applications
Multiplexed imaging for a wide range of biological questions
PhenoCycler-Fusion enables researchers to answer complex spatial questions across immune oncology, neurology, fibrosis, infectious disease, and beyond.
Software & Data Analysis
Turn images into insights with intelligent spatial analytics
The system integrates with advanced software for seamless acquisition, processing, and analysis—providing actionable insights from single cells to tissue-level patterns.
Key Performance Advantages
High-content data with unmatched speed and reproducibility Engineered for performance, the system offers high-throughput results without compromising quality—making it ideal for large-scale studies.