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Visiopharm introduces Phenoplex™, a unified solution for a better multiplex image analysis workflow

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Visiopharm, a world leader in AI-driven digital pathology image analysis software, today introduced Phenoplex , their latest innovation as part of their Oncotopix® Discovery platform.

Phenoplex offers a novel easy-to-use unified workflow for multiplex tissue image analysis. Designed to meet the needs of scientists, it simplifies the analysis pipeline from multiple software suites into one workflow and enables users to continuously review their data to get to meaningful results.

Phenoplex is a complete workflow with built-in tools to:

Analyse multiplex and highplex imagesImport files to rapidly visualize and QC biomarkers and biomarker groupsVerify and quantify cellular phenotypes in each tissue regionInteractively plot connecting multiplex images with graphs/plots and a cell galleryProduce and export the data, plots, and imagery needed for manuscript publication

As part of the Oncotopix Discovery AI-based research platform, Phenoplex supports the same flexibility to design the required analysis pipelines without requiring coding skills. Phenoplex analysis works with all major multiplex image file formats, whole-slide images and large datasets.

“Phenoplex embodies Visiopharm’s commitment to multiplex analysis and support for the immuno-oncology community,” said Louise Armstrong, Chief Commercial Officer at Visiopharm. “This new workflow allows us to continue to refine, improve, and create tools within each workflow stage. What researchers need is a unified workflow in one software package that can address all the steps required to deliver meaningful biological results that are needed. Phenoplex will be a trusted companion for anyone needing meaningful data from these complex images.”

Phenoplex was developed to support the critical field of cancer immunology. The growth of immunotherapy as the fifth pillar of cancer treatment has driven a need to better understand the role of the immune system in solid tumor therapies. Understanding the spatial biology of tumors has become crucial for researchers and the main method is the use of multi-marker staining and multiplexed imaging methods in FFPE sections to perform multiplex phenotyping of the cells in situ as orthogonal work done by flow cytometry of suspension samples.

In recent years there have been a number of advanced technologies introduced to perform highplex (10 to 40 or more markers in one section) staining and imaging of tissue sections, preserving the spatial features of cell populations. However, as the ‘plex level of imaging systems has grown, so too has the complexity of the image analysis required to make sense of all this data. Phenoplex was developed, in part, to address the needs of the immuno-oncology field and enable a simpler way to extract important biological information from these complex multiplex images.

About Visiopharm

Visiopharm® is a world leader in AI-driven precision pathology software. Their pioneering image analysis tools support thousands of scientists, pathologists, and image analysis experts in academic institutions, biopharmaceutical industry, and diagnostic centers. AI-based image analysis and tissue mining tools support research and drug development research worldwide, while CE-IVD APPs provide decision support. With the most advanced and sophisticated artificial intelligence and deep learning, Visiopharm delivers tissue data mining tools, precision results, and workflows.

Visiopharm was founded in 2002 and is privately owned. The company operates internationally with over 750 customer accounts and countless users in more than 40 countries. The company headquarters are in Denmark’s Medicon Valley, with offices in Sweden, England, Germany, The Netherlands and United States.

For enquiries: 

Johanne Louise Brændgaard
Chief Marketing Officer
jlb@visiopharm.com

The post Visiopharm introduces Phenoplex™, a unified solution for a better multiplex image analysis workflow appeared first on Visiopharm · Pathology image analysis software.

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