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Founded Year



Series C | Alive

Total Raised


Last Raised

$165M | 8 mos ago

About PathAI

PathAI provides AI-powered research tools and services for pathology. PathAI's platform promises substantial improvements to the accuracy of diagnosis and the efficacy of treatment of diseases like cancer, leveraging modern approaches in machine and deep learning.

PathAI Headquarter Location

1325 Boylston St. Suite 10000

Boston, Massachusetts, 02215,

United States

Latest PathAI News

Akoya Biosciences Announces a Groundbreaking Collaboration with PathAI to Combine Spatial Biology with AI-Powered Tools to Facilitate Discovery of Novel Predictive Biomarkers

Dec 13, 2021

Marlborough, Massachusetts, UNITED STATES MARLBOROUGH, Mass., Dec. 13, 2021 (GLOBE NEWSWIRE) -- Akoya Biosciences, Inc., (Nasdaq: AKYA), The Spatial Biology Company®, and PathAI, a global leader in artificial intelligence (AI)-powered technology for pathology, today announced a collaboration to advance the discovery and validation of novel predictive biomarkers for immunotherapies. The partners will leverage their industry leading capabilities in spatial biology and deep data mining using Phenoptics™, Akoya’s high throughput spatial phenotyping platform, and PathAI’s artificial intelligence tools and algorithms to enhance their shared biopharmaceutical partners’ ability to identify patients most likely to respond to drugs in clinical trials. Akoya will work with PathAI to create a seamless interface between the Advanced Biopharma Solutions (ABS) service offerings and PathAI’s analytical capabilities to provide a powerful and complete solution for biopharma partners. This partnership and ABS’ recent CLIA certification represent significant milestones in advancing Akoya’s ability to serve the growing demand for spatial biomarkers in clinical trials. “The combined power of spatial phenotyping and high throughput data sets from Akoya and PathAI’s algorithms can accelerate the discovery of spatial phenotypic signatures in the tumor microenvironment,” said Dr. Andy Beck, CEO of PathAI. “This could streamline drug development to identify patients with a high likelihood of responding to immunotherapies.” Discovery and validation of novel biomarkers could have particularly important near-term implications for improving the efficacy rates of immuno-oncology treatments, an area of medicine that is revolutionizing cancer treatment. Spatial biology is a rapidly emerging scientific discipline that enables deeper understanding of cancer immunology by analyzing the spatial architecture of tumor tissue sections and mapping the complex organization and interactions of tumor and immune cells within the tumor microenvironment. These insights streamline drug development, clinical trials, and biomarker discovery, and are currently being applied to immunotherapy research. “This collaboration takes Akoya’s ABS offering to the next level by providing biopharma partners with a comprehensive offering that integrates the most advanced technologies and know how in the field of spatial biomarkers and digital pathology,” said Brian McKelligon, Chief Executive Officer of Akoya Biosciences. “The combination of our Phenoptics platform and PathAI’s AI-powered technology has the potential to transform biomarker use in clinical trials and ultimately impact cancer care.” Dr. Michael Montalto, Chief Scientific Officer of PathAI, will discuss the role of AI in spatial biomarker development at Akoya’s Spatial Day Event on December 15, 2021. Register at this link . About Akoya Biosciences As The Spatial Biology Company®, Akoya Biosciences’ mission is to bring context to the world of biology and human health through the power of spatial phenotyping. The company offers comprehensive single-cell imaging solutions that allow researchers to phenotype cells with spatial context and visualize how they organize and interact to influence disease progression and treatment response. Akoya offers two distinct solutions, the CODEX® and Phenoptics™ platforms, to serve the diverse needs of researchers across discovery, translational and clinical research. To learn more about Akoya, visit . About PathAI PathAI is a leading provider of AI-powered research tools and services for pathology. PathAI’s platform promises substantial improvements to the accuracy of diagnosis and the efficacy of treatment of diseases like cancer, leveraging modern approaches in machine and deep learning. Based in Boston, PathAI works with leading life sciences companies and researchers to advance precision medicine. To learn more, visit . Akoya Investor Contact:

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Expert Collections containing PathAI

Expert Collections are analyst-curated lists that highlight the companies you need to know in the most important technology spaces.

PathAI is included in 9 Expert Collections, including Artificial Intelligence.


Artificial Intelligence

8,330 items

This collection includes startups selling AI SaaS, using AI algorithms to develop their core products, and those developing hardware to support AI workloads.


Digital Health 150

450 items

2019's cohort of the most promising digital health startups transforming the healthcare industry


Medical Devices

8,130 items

Companies developing medical devices (per the IMDRF's definition of "medical device"). Includes software, lab-developed tests (LDTs), and combination products. *Columns updated as regularly as possible.


Biopharma Tech

5,238 items

Companies involved in the research, development, and commercialization of chemically- or biologically-derived therapeutic & theranostic drugs. Excludes vitamins/supplements, CROs/clinical trial services.



3,605 items

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Health Monitoring & Diagnostics

2,707 items

Companies developing or offering products that aid in the assessment, screening, diagnosis, or monitoring of a person's state of health/wellness. Excludes companies focused solely on fitness/sports performance

PathAI Patents

PathAI has filed 5 patents.

The 3 most popular patent topics include:

  • Artificial neural networks
  • Classification algorithms
  • Clusters of differentiation
patents chart

Application Date

Grant Date


Related Topics




Machine learning, Classification algorithms, Artificial neural networks, Transcription factors, Clusters of differentiation


Application Date


Grant Date



Related Topics

Machine learning, Classification algorithms, Artificial neural networks, Transcription factors, Clusters of differentiation



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