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We aim to empower researchers with cutting-edge computational tools for comprehensive analysis of digital pathology images, facilitating the transition from raw data to biological significance in the pursuit of advancing biomedical research and development.
The Right Analysis Can Demystify The Unknown
Pathomics.ai – We Analyze Images
Our team has built tools that convert biological images into the results needed by scientists. We lead the industry in analyzing imagining data and as scientists ourselves, know how to navigate the challenges faced and deliver results.
Streamline
Streamline experimental workflows by providing simple and straightforward results that answer complex biological questions.
Integrate
Further understand biological mechanisms of disease by integration of multi-omic data sets.
Predict
Predict the type of disease from subtle features present in the image itself.
Digital Pathology Quantified
Do you face challenges extracting quantitative results and processing them to explainable outcomes from your spatial biology experiments such as digital pathology images, multiplex immunohistochemistry, spatial transcriptomics or multi-omics datasets?
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Our team has utmost experience in delivering impactful spatial biology results from datasets, as evidenced by our list of 50+ peer-reviewed and high impact publications in collaboration with academics and industry worldwide.
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Utilizing the latest analytical tools, including customized post-processing for visualization and interrogation of data, we are confident that we can deliver the analytical results you need for your research study or clinical trial.
You have obtained beautiful stained images, what's next?
Let us help you extract your qualitative data.
With our expertise, we can provide quantitative analytical results with greater accuracy, clear and precise methodologies, and valuable biological insights in a timely manner.
We offer validated results to help pathologists
We are here to work alongside pathologists by incorporating their feedback into our analytical process, ensuring confidence in the reliability and interpretation of your results.
We offer the ability to directly test multiple cell segmentation methodologies, ensuring you get the right answers to address your scientific questions.
Spatial Biology Potential - True Multi-Omics Realized
Biomarker intensities and percent positivity are only the start of what can be extracted from spatial omics datasets. At Pathomics.ai, we analyze cellular neighborhoods, tissue classifiers, and spatial relationships within those tissues.
Furthermore, we extract spatial information through integration of transcriptomic, proteomic, and metabolic datasets in order to uncover and demystify the underlying biology of disease states.
Identifying spatial features in your datasets can massively improve the accuracy of disease classifiers and provide a wealth of additional insights previously hidden in overly simplistic analysis methods.
