Phenoplex

Phenoplex, developed by Visiopharm, is a complete image analysis workflow solution designed for multiplex tissue imaging in spatial biology. Built on Visiopharm's AI platform, it supports researchers and image analysis scientists working to interrogate the tumor microenvironment using technologies such as imaging mass cytometry (Standard BioTools Hyperion XTi™) and high-plex fluorescent panels (Akoya PhenoCycler®, Lunaphore Comet®, and others). Phenoplex is purpose-built to help users make new discoveries, compare between cohorts, and reproduce results regardless of plex level.

The platform addresses the growing challenge of finding meaningful differences in spatial biology data as staining technologies expand the number of markers that can be simultaneously interrogated. With interactive verification steps throughout the workflow and deep-learning-powered analysis, Phenoplex enables users to trust their results at every stage of the analysis pipeline.

Core Capabilities

• Deep learning-powered cell detection: Pre-trained nuclear detection and cell segmentation algorithms support both fluorescence (DAPI) and imaging mass cytometry (DNA-Iridium channels), providing highly accurate and robust results across datasets.
• AI-based tissue classification: Paint-to-Train AI tissue segmentation allows detection of morphologic regions such as tumor, stroma, necrosis, and artifacts using any combination of markers.
• Flexible phenotyping for all plex levels: Fully automated unsupervised clustering for assays with up to 8 markers, and a user-guided gating workflow for assays with 8 to 40 or more markers.
• Interactive data exploration: Bidirectional evaluation plots, t-SNE visualizations, and image re-coloring views allow continuous verification and deeper exploration of results.
• True spatial biology analysis: Distance calculations between phenotypes and tissue class boundaries, neighborhood analyses, zone analyses for tumor margin assessments, and cell density correlations.
• Comprehensive export options: Results, images, and plots can be exported as layer data (.mld), standard .tif, and/or .tsv tab-delimited raw data files for use in external analysis pipelines.

Step-by-Step Workflow

1. Visualize: Import images from all major multiplex formats including Akoya Biosciences, Standard BioTools, Lunaphore, Rarecyte, Ionpath, Canopy Biosciences, Olympus, Zeiss, and more. Set user-defined color channel groups, assign colors to individual channels or channel groups, and perform initial image quality control. Exclude individual channels from downstream analyses during the QC step.
2. Classify Tissue: Apply Paint-to-Train AI segmentation to detect morphologic regions. Subdivide the tumor into subregions, automatically exclude non-relevant areas such as blank slide or artifacts, and create margins around specific regions of interest such as the invasive tumor front.
3. Detect Cells: Leverage pre-trained deep-learning nuclear detection and cell segmentation. Augment algorithms for special requirements by adding additional markers, annotating unusually shaped cells, or incorporating postprocessing steps.
4. Phenotype: Use automated unsupervised clustering for up to 8 markers, or apply the user-guided gating workflow for high-plex assays exceeding 8 markers, with thresholds adjustable in real time.
5. Verify: Confirm phenotyping results by combining graphs with image re-coloring views. Color t-SNE plots by cell type, link data points between graphs, and review biomarker co-occurrence using a matrix table representing all biomarkers used in the workflow.
6. Explore: Dive deeper into results using comprehensive bidirectional evaluation plots. Quantify cell counts per region, discover expression patterns, and perform spatial analyses across specific tissue areas.
7. Publish: Generate and export data, imagery, and plots in standard formats. Save all outputs to the Phenoplex database or export as .mld, .tif, or .tsv files for subsequent analysis in external pipelines.

Supported Imaging Platforms

• Akoya Biosciences (PhenoCycler®)
• Standard BioTools (Hyperion XTi™ imaging mass cytometry)
• Lunaphore (Comet®)
• Rarecyte, Ionpath, Canopy Biosciences, Olympus, Zeiss, and additional major multiplex imaging systems

Phenoplex is designed to integrate seamlessly into existing spatial biology research environments, supporting downstream analysis through standard file exports compatible with external data analysis pipelines. The platform's interactive verification approach and built-in data exploration tools — including t-SNE functions for rapid quality control and phenotype outlier identification — make it a robust solution for both discovery research and reproducible translational studies in the tumor microenvironment.