AI-based Digital Pathology / AI Pathology Market Distribution by Type of Neural Network (Artificial Neural Network, Convolutional Neural Network, Fully Convolutional Network, Recurrent Neural Network and Other Neural Networks), Type of Assay (ER Assay, HER2 Assay, Ki67 Assay, PD-L1 Assay, PR Assay and Other Type of Assays), Type of End-user (Academic Institutions, Hospitals / Healthcare Institutions, Laboratories / Diagnostic Institutions, Research Institutes and Other End-users), Area of Application (Diagnostics, Research and Other Areas of Application), Type of Target Disease Indication (Breast Cancer, Colorectal Cancer, Cervical Cancer, Gastrointestinal Cancer, Lung Cancer, Prostate Cancer and Other Indications) and Key Geographies (North America, Europe, Asia, Latin America, Middle East and North Africa and Rest of the World), 2022-2035

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Overview

Pathology is a subfield of medical science that primarily focuses on the nature, genesis and cause of a disease. Further, pathology forms an essential component of diagnostic pathways established for multiple disease indications, especially cancer detection. In fact, 70-80% of the total healthcare decisions involved in either diagnosis or treatment of ailments require a pathological assessment. Further, according to the International Agency for Research on Cancer (IARC), by 2040, 27 million new cancer cases are expected to be reported annually. This rise in cancer cases, coupled to the rapidly ageing global population, is expected to lead to a substantial increase in the pathology workload. However, as the demand for professional pathologists continues to increase, the number of active pathologists in the field is diminishing over time. As per a recent study, a 30% decline in the number of active pathologists is expected to be observed by 2030, as compared to the number of such professionals in 2010. Moreover, 63.2% of the currently active pathologists are anticipated to retire in the next 10 years. Furthermore, it is projected that a substantial disparity (close to 30%) between the expected demand for pathology services and supply of pathologists is likely to be witnessed by the year 2030.

Amidst the ever-growing demand for pathology services, the simultaneous use of technological advances to automate and digitize healthcare procedures is growing. These developments have accelerated research and clinical diagnosis, as well as enhanced patient outcomes, in the recent years. Specifically, AI-powered digital imaging is one such technology, which has revolutionized the pathology industry by enabling high-throughput scanning of patient samples. To provide more context, AI-based digital pathology / AI pathology involves collection, management, analyzing and sharing of data (via digital slides) in a digital setting. Through this process, digital slides are created by scanning conventional glass slides with a scanning device, which may be seen on a computer screen or a mobile device and offer a high-resolution digital image.  Further, AI pathology technique presents a viable solution to managing the growing pathology workload, while also ensuring more rapid and consistent diagnostic services and research activities. Moreover, AI-powered digital pathology solutions (digital pathology scanners and digital pathology software) allow pathologists to examine more cases and offer a precise diagnosis. It is worth highlighting that digitized workflows can speed up processing times, lower administrative errors, enable remote collaboration and boost productivity, thereby, allowing significant cost savings.  Experts believe that there has been a significant rise in the revenue generation potential within this domain. This is further supported by the significant investments being made in this industry. Since 2016, funding received by digital pathology firms have surpassed USD 1.6 billion, with majority of amount being raised in the year 2021. Considering the rising popularity and demand for such solutions in the healthcare and research industry, and the ongoing efforts of AI-powered digital pathology solution providers / AI pathology solution providers to further improve / expand their respective portfolios, we believe that the AI-based digital pathology market is likely to evolve at a steady pace, till 2035.

Scope of the Report

The “AI-based Digital Pathology / AI Pathology Market by Type of Neural Network (Artificial Neural Network, Convolutional Neural Network, Fully Convolutional Network, Recurrent Neural Network and Other Neural Networks), Type of Assay (ER Assay, HER2 Assay, Ki67 Assay, PD-L1 Assay, PR Assay and Other Type of Assays), Type of End-user (Academic Institutions, Hospitals / Healthcare Institutions, Laboratories / Diagnostic Institutions, Research Institutes and Other End-users), Area of Application (Diagnostics, Research and Other Areas of Application), Target Disease Indication (Breast Cancer, Colorectal Cancer, Cervical Cancer, Gastrointestinal Cancer, Lung Cancer, Prostate Cancer and Other Indications) and Key Geographies (North America, Europe, Asia, Latin America, Middle East and North Africa and Rest of the World): Industry Trends and Global Forecasts, 2022-2035” report features an extensive study of the current market landscape and future potential of the AI-based digital pathology market. The study features an in-depth analysis, highlighting the capabilities of various stakeholders engaged in providing AI-based digital pathology. Amongst other elements, the report features:

  • An executive summary of the insights captured during our research. It offers a high-level view on the current state of AI-based digital pathology market and its likely evolution in the mid-long term.
  • A general introduction to AI-based digital pathology, featuring information on artificial intelligence in digital pathology, workflow of AI-based digital pathology, applications of AI-based digital pathology solutions in the healthcare domain. Additionally, the chapter includes details on the various regulatory requirements related to AI-based digital pathology. The chapter concludes with a discussion on the challenges, key growth drivers and future perspectives associated with the use of AI in digital pathology.
  • A detailed assessment of the overall market landscape of AI-based digital pathology providers, based on several relevant parameters, such as geographical reach, year of establishment, company size (in terms of number of employees), location of headquarters (country-wise and continent-wise), type of product (hardware and software), type of service (automated image analysis, image management, vendor agnostic, cloud-based solution, whole slide imaging, laboratory information system, hospital information system and picture archiving and communication system), type of feature (prognostic algorithms, predictive algorithms and multi-modal fusion algorithms), additional features (customizability, scalability and deployment options), area of application (diagnosis and research use), target disease indication, type of assay, type of end-user (research institutes, academic institutions, hospitals / healthcare institutions, laboratories / diagnostic institutions, others) and information on number of available software. 
  • An in-depth analysis, highlighting the contemporary market trends, including [A] distribution based on type of service and area of application, [B] distribution based on type of feature and area of application, [C] distribution based on type of product and area of application, [D] type of product and location of headquarters, as well as [E] an insightful hybrid representation of AI-based digital pathology providers based on company size and location of headquarters.
  • Elaborate profiles of various prominent players that are engaged in offering services related to AI-based digital pathology. Each profile features a brief overview of the company (including information on year of establishment, number of employees, location of headquarters and management team) and details related to recent developments and an informed future outlook.
  • A company competitive analysis of various players engaged in this domain. It highlights the capabilities of industry players (in terms of their expertise across various services related to AI-based digital pathology). The analysis allows companies to compare their existing capabilities within and beyond their peer groups and identify opportunities to gain a competitive edge in the industry.  The chapter also includes benchmarking of industry players engaged in this domain based on their portfolio strength (type of product, type of service, type of feature, additional features, area of application and type of end-user) and funding activity (number of funding instances and funding amount).
  • An analysis of the funding and investments made within this domain, during the period 2016-2022, based on several relevant parameters, such as number of instances, amount invested, type of funding, area of application, geography and information on most active players engaged in the AI-based digital pathology domain. 
  • An elaborate analysis in order to estimate the current and future demand for AI-based digital pathology, based on several relevant parameters, such as geography (North America, Europe, Asia, Latin America, MENA and Rest of the World) and end-users (hospitals, research and other end-users). 
  • A detailed market forecast analysis, highlighting the likely evolution of the AI-based digital pathology market in the short to mid-term and long term, over the period 2022-2035. Further, the year-wise projections of the current and future opportunity have been segmented based on several relevant parameters, such as type of neural network (artificial neural network, convolutional neural network, fully convolutional network, recurrent neural network and other neural networks), type of assay (ER assay, HER2 assay, Ki67 assay, PD-L1 assay, PR assay and other type of assays), type of end-user (academic institutions, hospitals / healthcare institutions, laboratories / diagnostic institutions, research institutes and other end-users), area of application (diagnostics, research and other areas of application), target disease indication (breast cancer, colorectal cancer, cervical cancer, gastrointestinal cancer, lung cancer, prostate cancer and other indications) and key geographies (North America, Europe, Asia, Latin America, Middle East and North Africa and Rest of the World). In order to account for future uncertainties and to add robustness to our model, we have provided three market forecast scenarios, namely conservative, base and optimistic scenarios, which represent different tracks of the industry’s growth. 

All actual figures have been sourced and analyzed from publicly available information forums. Financial figures mentioned in this report are in USD, unless otherwise specified.

Frequently Asked Questions

  • What is digital pathology? How does digital pathology work? 
  • Who are the leading players offering AI-based digital pathology / AI pathology solutions?
  • Which geographies are key hubs for AI-based digital pathology providers?
  • What is the projected growth of the AI-based digital pathology market? 
  • Which type of end-users are primarily employing AI in digital pathology in their regular workflow?
  • What type of funding models are common in AI-based digital pathology market?
  • What are the key strategies that can be implemented by emerging players to enter the AI-based digital pathology market?
  • What are the key market trends and driving factors that are likely to impact the growth of the AI-based digital pathology / AI pathology market?
  • How is the current and future opportunity likely to be distributed across key market segment?

Contents

Table Of Contents

1. PREFACE
1.1. Chapter Overview
1.2. Market Segmentations
1.3. Research Methodology
1.4. Key Questions Answered
1.5. Chapter Outlines

2. EXECUTIVE SUMMARY

3. INTRODUCTION
3.1. Chapter Overview
3.2. Artificial Intelligence in Digital Pathology
3.3. Workflow of AI-based Digital Pathology
3.4. Applications of AI-based Digital Pathology Solutions
3.5. Regulatory Requirements Focused on AI-based Digital Pathology:
3.6. Challenges Associated with the Use of AI in Digital Pathology
3.7. Future Perspectives

4. AI-BASED DIGITAL PATHOLOGY: MARKET LANDSCAPE
4.1. Chapter Overview
4.2. AI-based Digital Pathology Providers: Overall Market Landscape
4.2.1. Analysis by Type of Product
4.2.2. Analysis by Type of Service Offered
4.2.3. Analysis by Type of Feature
4.2.4. Analysis by Additional Features
4.2.5. Analysis by Target Disease Indication
4.2.6. Analysis by Type of Assay
4.2.7. Analysis by Area of Application
4.2.8. Analysis by Type of End-user
4.2.9. Analysis by Number of Available Software

4.3. AI-based Digital Pathology Providers: Developer Landscape
4.3.1. Analysis by Geographical Reach
4.3.2. Analysis by Year of Establishment
4.3.3. Analysis by Company Size
4.3.4. Analysis by Location of Headquarters (Country-wise)
4.3.5. Analysis by Location of Headquarters (Continent-wise)

5. AI-BASED DIGITAL PATHOLOGY MARKET: KEY INSIGHTS
5.1. Chapter Overview
5.1.1. Analysis by Type of Service and Area of Application
5.1.2. Analysis by Type of Feature and Area of Application
5.1.3. Analysis by Type of Product and Area of Application
5.1.4. Analysis by Type of Product and Location of Headquarters
5.1.5. Analysis by Company Size and Location of Headquarters

6. COMPANY PROFILES
6.1. Chapter Overview
6.2. PathAI
6.2.1. Company Overview
6.2.2. Recent Developments and Future Outlook

6.3. Paige
6.3.1. Company Overview
6.3.2. Recent Developments and Future Outlook

6.4. Akoya Biosciences
6.4.1. Company Overview
6.4.2. Recent Developments and Future Outlook

6.5. PROSCIA
6.5.1. Company Overview
6.5.2. Recent Developments and Future Outlook

6.6. Visiopharm
6.6.1. Company Overview
6.6.2. Recent Developments and Future Outlook

6.7. Roche Tissue Diagnostics
6.7.1. Company Overview
6.7.2. Recent Developments and Future Outlook

6.8. Aiforia Technologies
6.8.1. Company Overview
6.8.2. Recent Developments and Future Outlook

6.9. Indica Labs
6.9.1. Company Overview
6.9.2. Recent Developments and Future Outlook

6.10. Ibex Medical Analytics
6.10.1. Company Overview
6.10.2. Recent Developments and Future Outlook

7. COMPANY COMPETITIVENESS ANALYSIS
7.1. Chapter Overview
7.2. Assumptions and Key Parameters
7.3. Methodology
7.4. Benchmarking of Portfolio Strength
7.5. Benchmarking of Funding Strength
7.6. Company Competitiveness Analysis: Small Players
7.7. Company Competitiveness Analysis: Mid-sized Players
7.8. Company Competitiveness Analysis: Large Players

8. FUNDING AND INVESTMENTS
8.1. Chapter Overview
8.2. Types of Funding
8.3. AI-based Digital Pathology: List of Funding and Investments
8.3.1. Cumulative Year-wise Trend by Number of Instances
8.3.2. Cumulative Year-wise Trend by Amount Invested
8.3.3. Analysis by Type of Funding
8.3.4. Analysis by Type of Funding and Amount Invested
8.3.5. Analysis by Area of Application
8.3.6. Analysis by Geography
8.3.7. Most Active Players: Analysis by Number of Funding Instances
8.3.8. Most Active Players: Analysis by Amount Raised
8.4. Concluding Remarks

9. DEMAND ANALYSIS
9.1. Chapter Overview
9.2. Scope and Methodology
9.3. Global Demand for AI-based Digital Pathology, 2022-2035
9.4. Demand for AI-based Digital Pathology: Analysis by Geography
9.4.1. Demand for AI-based Digital Pathology in North America
9.4.1.1 Demand for AI-based Digital Pathology in the US
9.4.1.2 Demand for AI-based Digital Pathology in Canada

9.4.2. Demand for AI-based Digital Pathology in Europe
9.4.2.1. Demand for AI-based Digital Pathology in UK
9.4.2.2. Demand for AI-based Digital Pathology in Germany
9.4.2.3. Demand for AI-based Digital Pathology in Spain
9.4.2.4. Demand for AI-based Digital Pathology in Italy
9.4.2.5. Demand for AI-based Digital Pathology in France

9.4.3. Demand for AI-based Digital Pathology in Asia
9.4.3.1. Demand for AI-based Digital Pathology in China
9.4.3.2. Demand for AI-based Digital Pathology in Japan
9.4.3.3. Demand for AI-based Digital Pathology in South Korea

9.4.4. Demand for AI-based Digital Pathology in Latin America
9.4.4.1. Demand for AI-based Digital Pathology in Brazil

9.4.5. Demand for AI-based Digital Pathology in MENA
9.4.5.1. Demand for AI-based Digital Pathology in Saudi Arabia

9.4.6. Demand for AI-based Digital Pathology in Rest of the World
9.4.6.1. Demand for AI-based Digital Pathology in Australia

9.5. Demand for AI-based Digital Pathology: Analysis by Type of End-user
9.5.1 Demand for AI-based Digital Pathology in Hospitals
9.5.2. Demand for AI-based Digital Pathology in Research Institutes
9.5.3. Demand for AI-based Digital Pathology in Other End-users

9.6. Concluding Remarks

10. MARKET SIZING AND OPPORTUNITY ANALYSIS
10.1. Chapter Overview
10.2. Forecast Methodology and Key Assumptions
10.3. Global AI-based Digital Pathology Market, 2022-2035

10.4. AI-based Digital Pathology Market: Analysis by Type of Neural Network, 2022 and 2035
10.4.1. AI-based Digital Pathology Market for Artificial Neural Network, 2022-2035
10.4.2. AI-based Digital Pathology Market for Convolutional Neural Network, 2022-2035
10.4.3. AI-based Digital Pathology Market for Fully Convolutional Network, 2022-2035
10.4.4. AI-based Digital Pathology Market for Recurrent Neural Network, 2022 – 2035
10.4.5. AI-based Digital Pathology Market for Other Neural Networks, 2022 – 2035

10.5. AI-based Digital Pathology Market: Analysis by Type of Assay, 2022 and 2035
10.5.1. AI-based Digital Pathology Market for ER Assay, 2022-2035
10.5.2. AI-based Digital Pathology Market for HER2 Assay, 2022-2035
10.5.3. AI-based Digital Pathology Market for Ki67 Assay, 2022-2035
10.5.4. AI-based Digital Pathology Market for PD-L1 Assay, 2022-2035
10.5.5. AI-based Digital Pathology Market for PR Assay, 2022-2035
10.5.6. AI-based Digital Pathology Market for Other Type of Assays, 2022-2035

10.6. AI-based Digital Pathology Market: Analysis by Type of End-user, 2022 and 2035
10.6.1. AI-based Digital Pathology Market for Academic Institutions, 2022-2035
10.6.2. AI-based Digital Pathology Market for Hospitals / Healthcare Institutions, 2022-2035
10.6.3. AI-based Digital Pathology Market for Laboratories / Diagnostic Institutions, 2022-2035
10.6.4. AI-based Digital Pathology Market for Research Institutes, 2022-2035
10.6.5. AI-based Digital Pathology Market for Other End-users, 2022-2035

10.7. AI-based Digital Pathology Market: Analysis by Area of Application, 2022 and 2035
10.7.1. AI-based Digital Pathology Market for Diagnostics, 2022-2035
10.7.2. AI-based Digital Pathology Market for Research, 2022-2035
10.7.3. AI-based Digital Pathology Market for Other Areas of Application, 2022-2035

10.8. AI-based Digital Pathology Market: Analysis by Target Disease Indication, 2022 and 2035
10.8.1. AI-based Digital Pathology Market for Breast Cancer, 2022-2035
10.8.2. AI-based Digital Pathology Market for Colorectal Cancer, 2022-2035
10.8.3. AI-based Digital Pathology Market for Cervical Cancer, 2022-2035
10.8.4. AI-based Digital Pathology Market for Gastrointestinal Cancer, 2022-2035
10.8.5. AI-based Digital Pathology Market for Lung Cancer, 2022-2035
10.8.6. AI-based Digital Pathology Market for Prostate Cancer, 2022-2035
10.8.7. AI-based Digital Pathology Market for Other Indications, 2022-2035

10.9. AI-based Digital Pathology Market: Analysis by Key Geographies, 2022 and 2035
10.9.1. AI-based Digital Pathology Market in North America, 2022-2035
10.9.1.1. AI-based Digital Pathology Market in the US, 2022-2035
10.9.1.2. AI-based Digital Pathology Market in Canada, 2022-2035

10.9.2. AI-based Digital Pathology Market in Europe, 2022-2035
10.9.2.1. AI-based Digital Pathology Market in UK, 2022-2035
10.9.2.2. AI-based Digital Pathology Market in Germany, 2022-2035
10.9.2.3. AI-based Digital Pathology Market in Spain, 2022-2035
10.9.2.4. AI-based Digital Pathology Market in Italy, 2022-2035
10.9.2.5. AI-based Digital Pathology Market in France, 2022-2035

10.9.3. AI-based Digital Pathology Market in Asia, 2022-2035
10.9.3.1. AI-based Digital Pathology Market in China, 2022-2035
10.9.3.2. AI-based Digital Pathology Market in Japan, 2022-2035
10.9.3.3. AI-based Digital Pathology Market in South Korea, 2022-2035

10.9.4. AI-based Digital Pathology Market in Latin America, 2022-2035
10.9.4.1. AI-based Digital Pathology Market in Brazil, 2022 – 2035

10.9.5. AI-based Digital Pathology Market in MENA, 2022-2035
10.9.5.1. AI-based Digital Pathology Market in Saudi Arabia, 2022-2035

10.9.6. AI-based Digital Pathology Market in Rest of the World, 2022-2035
10.9.6.1. AI-based Digital Pathology Market in Australia, 2022-2035

11. CONCLUDING REMARKS

12. EXECUTIVE INSIGHTS
12.1. Chapter Overview

12.2. aetherAI
12.2.1. Company Snapshot
12.2.2. Interview Transcript: Joe Yeh (Chief Executive Officer and Chairman)

12.3. CTL Clinitech Lab
12.3.1. Company Snapshot
12.3.2. Interview Transcript: Suraj Bramhane (Laboratory Director and Chief Pathologist)

12.4. Huron Digital Pathology
12.4.1. Company Snapshot
12.4.2. Interview Transcript: Savvas Damaskinos (Vice President, Research and Technology)

12.5. Mindpeak
12.5.1. Company Snapshot
12.5.2. Interview Transcript: Anil Berger (Vice President, Sales and Marketing)

13. APPENDIX 1: TABULATED DATA

14. APPENDIX II: LIST OF COMPANIES AND ORGANIZATION

List Of Figures

Figure 2.1 Executive Summary: Market Landscape
Figure 2.2 Executive Summary: Key Insights
Figure 2.3 Executive Summary: Funding and Investments
Figure 2.4 Executive Summary: Demand Analysis
Figure 2.5 Executive Summary: Market Sizing and Opportunity Analysis
Figure 3.1 Workflow of AI-based Digital Pathology
Figure 3.2 Applications of AI-based Digital Pathology Solutions
Figure 4.1 AI-based Digital Pathology Providers: Distribution by Type of Product
Figure 4.2 AI-based Digital Pathology Providers: Distribution by Type of Service Offered
Figure 4.3 AI-based Digital Pathology Providers: Distribution by Type of Feature
Figure 4.4 AI-based Digital Pathology Providers: Distribution by Additional Features
Figure 4.5 AI-based Digital Pathology Providers: Distribution by Target Disease Indication
Figure 4.6 AI-based Digital Pathology Providers: Distribution by Type of Assay
Figure 4.7 AI-based Digital Pathology Providers: Distribution by Area of Application
Figure 4.8 AI-based Digital Pathology Providers: Distribution by Type of End-user
Figure 4.9 AI-based Digital Pathology Providers: Distribution by Number of Available Software
Figure 4.10 AI-based Digital Pathology Providers: Distribution by Geographical Reach
Figure 4.11 AI-based Digital Pathology Providers: Distribution by Year of Establishment
Figure 4.12 AI-based Digital Pathology Providers: Distribution by Company Size
Figure 4.13 AI-based Digital Pathology Providers: Distribution by Location of Headquarters (Country-wise)
Figure 4.14 AI-based Digital Pathology Providers: Distribution by Location of Headquarters (Continent-wise)
Figure 5.1 Key Insights: Distribution by Type of Service and Area of Application
Figure 5.2 Key Insights: Distribution by Type of Feature and Area of Application
Figure 5.3 Key Insights: Distribution by Type of Product and Area of Application
Figure 5.4 Key Insights: Distribution by Type of Product and Location of Headquarters
Figure 5.5 Key Insights: Distribution by Company Size and Location of Headquarters
Figure 7.1 Company Competitiveness Analysis: Benchmarking of Portfolio Strength
Figure 7.2 Company Competitiveness Analysis: Benchmarking of Funding Strength
Figure 7.3 Company Competitiveness Analysis: Small Players
Figure 7.4 Company Competitiveness Analysis: Mid-sized Players
Figure 7.5 Company Competitiveness Analysis: Large Players
Figure 8.1 Funding and Investments: Cumulative Year-wise Trend by Number of Instances
Figure 8.2 Funding and Investments: Cumulative Year-wise Trend by Amount Invested
Figure 8.3 Funding and Investments: Distribution of Instances by Type of Funding
Figure 8.4 Funding and Investments: Distribution of Instances by Type of Funding and Amount Invested
Figure 8.5 Funding and Investments: Distribution of Instances by Area of Application
Figure 8.6 Funding and Investments: Distribution of Instances by Geography
Figure 8.7 Most Active Players: Distribution by Number of Funding Instances
Figure 8.8 Most Active Players: Distribution by Amount Raised
Figure 8.9 Funding and Investments: Concluding Remarks
Figure 9.1 Global Demand for AI-based Digital Pathology, 2022-2035 (Million Slides)
Figure 9.2 Demand for AI-based Digital Pathology: Distribution by Geography, 2022 and 2035
Figure 9.3 Demand for AI-based Digital Pathology in North America, 2022-2035 (Million Slides)
Figure 9.4 Demand for AI-based Digital Pathology in the US, 2022-2035 (Million Slides)
Figure 9.5 Demand for AI-based Digital Pathology in Canada, 2022-2035 (Million Slides)
Figure 9.6 Demand for AI-based Digital Pathology in Europe, 2022-2035 (Million Slides)
Figure 9.7 Demand for AI-based Digital Pathology in UK, 2022-2035 (Million Slides)
Figure 9.8 Demand for AI-based Digital Pathology in Germany, 2022-2035 (Million Slides)
Figure 9.9 Demand for AI-based Digital Pathology in Spain, 2022-2035 (Million Slides)
Figure 9.10 Demand for AI-based Digital Pathology in Italy, 2022-2035 (Million Slides)
Figure 9.11 Demand for AI-based Digital Pathology in France, 2022-2035 (Million Slides)
Figure 9.12 Demand for AI-based Digital Pathology in Asia, 2022-2035 (Million Slides)
Figure 9.13 Demand for AI-based Digital Pathology in China, 2022-2035 (Million Slides)
Figure 9.14 Demand for AI-based Digital Pathology in Japan, 2022-2035 (Million Slides)
Figure 9.15 Demand for AI-based Digital Pathology in South Korea, 2022-2035 (Million Slides)
Figure 9.16 Demand for AI-based Digital Pathology in Latin America, 2022-2035 (Million Slides)
Figure 9.17 Demand for AI-based Digital Pathology in Brazil, 2022-2035 (Million Slides)
Figure 9.18 Demand for AI-based Digital Pathology in MENA, 2022-2035 (Million Slides)
Figure 9.19 Demand for AI-based Digital Pathology in Saudi Arabia, 2022-2035 (Million Slides)
Figure 9.20 Demand for AI-based Digital Pathology in Rest of the World, 2022-2035 (Million Slides)
Figure 9.21 Demand for AI-based Digital Pathology in Australia, 2022-2035 (Million Slides)
Figure 9.22 Global Demand for AI-based Digital Pathology: Distribution by Type of End-user, 2022 and 2035
Figure 9.23 Global Demand for AI-based Digital Pathology in Hospitals, 2022-2035 (Million Slides)
Figure 9.24 Global Demand for AI-based Digital Pathology in Research Institutes, 2022-2035 (Million Slides)
Figure 9.25 Global Demand for AI-based Digital Pathology in Other End-users, 2022-2035 (Million Slides)
Figure 10.1 Global AI-based Digital Pathology Market, 2022-2035 (USD Million)
Figure 10.2 AI-based Digital Pathology Market: Distribution by Type of Neural Network, 2022 and 2035
Figure 10.3 AI-based Digital Pathology Market for Artificial Neural Network, 2022-2035 (USD Million)
Figure 10.4 AI-based Digital Pathology Market for Convolutional Neural Network, 2022-2035 (USD Million)
Figure 10.5 AI-based Digital Pathology Market for Fully Convolutional Network, 2022-2035 (USD Million)
Figure 10.6 AI-based Digital Pathology Market for Recurrent Neural Network, 2022-2035 (USD Million)
Figure 10.7 AI-based Digital Pathology Market for Other Neural Networks, 2022-2035 (USD Million)
Figure 10.8 AI-based Digital Pathology Market: Distribution by Type of Assay, 2022 and 2035
Figure 10.9 AI-based Digital Pathology Market for ER Assay, 2022-2035 (USD Million)
Figure 10.10 AI-based Digital Pathology Market for HER2 Assay, 2022-2035 (USD Million)
Figure 10.11 AI-based Digital Pathology Market for Ki67 Assay, 2022-2035 (USD Million)
Figure 10.12 AI-based Digital Pathology Market for PD-L1 Assay, 2022-2035 (USD Million)
Figure 10.13 AI-based Digital Pathology Market for PR Assay, 2022-2035 (USD Million)
Figure 10.14 AI-based Digital Pathology Market for Other Type of Assays, 2022-2035 (USD Million)
Figure 10.15 AI-based Digital Pathology Market: Distribution by Type of End-user, 2022 and 2035
Figure 10.16 AI-based Digital Pathology Market for Academic Institutions, 2022-2035 (USD Million)
Figure 10.17 AI-based Digital Pathology Market for Hospitals / Healthcare Institutions, 2022-2035 (USD Million)
Figure 10.18 AI-based Digital Pathology Market for Laboratories / Diagnostic Institutions, 2022-2035 (USD Million)
Figure 10.19 AI-based Digital Pathology Market for Research Institutes, 2022-2035 (USD Million)
Figure 10.20 AI-based Digital Pathology Market for Other End-users, 2022-2035 (USD Million)
Figure 10.21 AI-based Digital Pathology Market: Distribution by Area of Application, 2022 and 2035
Figure 10.22 AI-based Digital Pathology Market for Diagnostics, 2022-2035 (USD Million)
Figure 10.23 AI-based Digital Pathology Market for Research, 2022-2035 (USD Million)
Figure 10.24 AI-based Digital Pathology Market for Other Areas of Application, 2022-2035 (USD Million)
Figure 10.25 AI-based Digital Pathology Market: Distribution by Target Disease Indication, 2022 and 2035
Figure 10.26 AI-based Digital Pathology Market for Breast Cancer, 2022-2035 (USD Million)
Figure 10.27 AI-based Digital Pathology Market for Colorectal Cancer, 2022-2035 (USD Million)
Figure 10.28 AI-based Digital Pathology Market for Cervical Cancer, 2022-2035 (USD Million)
Figure 10.29 AI-based Digital Pathology Market for Gastrointestinal Cancer, 2022-2035 (USD Million)
Figure 10.30 AI-based Digital Pathology Market for Lung Cancer, 2022-2035 (USD Million)
Figure 10.31 AI-based Digital Pathology Market for Prostate Cancer, 2022-2035 (USD Million)
Figure 10.32 AI-based Digital Pathology Market for Other Indications, 2022-2035 (USD Million)
Figure 10.33 AI-based Digital Pathology Market: Distribution by Geography, 2022 and 2035
Figure 10.34 AI-based Digital Pathology Market in North America, 2022-2035 (USD Million)
Figure 10.35 AI-based Digital Pathology Market in the US, 2022-2035 (USD Million)
Figure 10.36 AI-based Digital Pathology Market in Canada, 2022-2035 (USD Million)
Figure 10.37 AI-based Digital Pathology Market in the Europe, 2022-2035 (USD Million)
Figure 10.38 AI-based Digital Pathology Market in UK, 2022-2035 (USD Million)
Figure 10.39 AI-based Digital Pathology Market in the Germany, 2022-2035 (USD Million)
Figure 10.40 AI-based Digital Pathology Market in Spain, 2022-2035 (USD Million)
Figure 10.41 AI-based Digital Pathology Market in Italy, 2022-2035 (USD Million)
Figure 10.42 AI-based Digital Pathology Market in France, 2022-2035 (USD Million)
Figure 10.43 AI-based Digital Pathology Market in Asia, 2022-2035 (USD Million)
Figure 10.44 AI-based Digital Pathology Market in China, 2022-2035 (USD Million)
Figure 10.45 AI-based Digital Pathology Market in Japan, 2022-2035 (USD Million)
Figure 10.46 AI-based Digital Pathology Market in South Korea, 2022-2035 (USD Million)
Figure 10.47 AI-based Digital Pathology Market in Latin America, 2022-2035 (USD Million)
Figure 10.48 AI-based Digital Pathology Market in Brazil, 2022-2035 (USD Million)
Figure 10.49 AI-based Digital Pathology Market in MENA, 2022-2035 (USD Million)
Figure 10.50 AI-based Digital Pathology Market in Saudi Arabia, 2022-2035 (USD Million)
Figure 10.51 AI-based Digital Pathology Market in Rest of the World, 2022-2035 (USD Million)
Figure 10.52 AI-based Digital Pathology Market in Australia, 2022-2035 (USD Million)
Figure 11.1 Concluding Remarks: Market Landscape
Figure 11.2 Concluding Remarks: Key Insights
Figure 11.3 Concluding Remarks: Funding and Investments
Figure 11.4 Concluding Remarks: Demand Analysis
Figure 11.5 Concluding Remarks: Market Sizing and Opportunity Analysis

List Of Tables

Table 4.1 List of AI-based Digital Pathology Providers
Table 4.2 AI-based Digital Pathology Providers: Information on Type of Product
Table 4.3 AI-based Digital Pathology Providers: Information on Type of Service Offered
Table 4.4 AI-based Digital Pathology Providers: Information on Type of Feature
Table 4.5 AI-based Digital Pathology Providers: Information on Additional Features
Table 4.6 AI-based Digital Pathology Providers: Information on Area of Application
Table 4.7 AI-based Digital Pathology Providers: Information on Type of End-user
Table 6.1 AI-based Digital Pathology Providers: List of Profiled Companies
Table 6.2 PathAI: Company Snapshot
Table 6.3 PathAI: Recent Developments and Future Outlook
Table 6.4 Paige: Company Snapshot
Table 6.5 Paige: Recent Developments and Future Outlook
Table 6.6 Akoya Biosciences: Company Snapshot
Table 6.7 Akoya Biosciences: Recent Developments and Future Outlook
Table 6.8 PROSCIA: Company Snapshot
Table 6.9 PROSCIA: Recent Developments and Future Outlook
Table 6.10 Visiopharm: Company Snapshot
Table 6.11 Visiopharm: Recent Developments and Future Outlook
Table 6.12 Roche Tissue Diagnostics: Company Snapshot
Table 6.13 Roche Tissue Diagnostics: Recent Developments and Future Outlook
Table 6.14 Aiforia Technologies: Company Snapshot
Table 6.15 Aiforia Technologies: Recent Developments and Future Outlook
Table 6.16 Indica Labs: Company Snapshot
Table 6.17 Indica Labs: Recent Developments and Future Outlook
Table 6.18 Ibex Medical Analytics: Company Snapshot
Table 6.19 Ibex Medical Analytics: Recent Developments and Future Outlook
Table 8.1 AI-based Digital Pathology Providers: List of Funding and Investments
Table 12.1 aetherAI: Company Snapshot
Table 12.2 CTL Clinitech Lab: Company Snapshot
Table 12.3 Huron Digital Pathology: Company Snapshot
Table 12.4 Mindpeak: Company Snapshot
Table 12.5 Pramana: Company Snapshot
Table 13.1 AI-based Digital Pathology Providers: Distribution by Type of Product
Table 13.2 AI-based Digital Pathology Providers: Distribution by Type of Service Offered
Table 13.3 AI-based Digital Pathology Providers: Distribution by Type of Feature
Table 13.4 AI-based Digital Pathology Providers: Distribution by Additional Features
Table 13.5 AI-based Digital Pathology Providers: Distribution by Target Disease Indication
Table 13.6 AI-based Digital Pathology Providers: Distribution by Type of Assay
Table 13.7 AI-based Digital Pathology Providers: Distribution by Area of Application
Table 13.8 AI-based Digital Pathology Providers: Distribution by Type of End-User
Table 13.9 AI-based Digital Pathology Providers: Distribution by Number of Available Software
Table 13.10 AI-based Digital Pathology Providers: Distribution by Geographical Reach
Table 13.11 AI-based Digital Pathology Providers: Distribution by Year of Establishment
Table 13.12 AI-based Digital Pathology Providers: Distribution by Company Size
Table 13.13 AI-based Digital Pathology Providers: Distribution by Location of Headquarters (Country-wise)
Table 13.14 AI-based Digital Pathology Providers: Distribution by Location of Headquarters (Continent-wise)
Table 13.15 Key Insights: Distribution by Type of Service and Area of Application
Table 13.16 Key Insights: Distribution by Type of Feature and Area of Application
Table 13.17 Key Insights: Distribution by Type of Product and Area of Application
Table 13.18 Key Insights: Distribution by Type of Product and Location of Headquarters
Table 13.19 Key Insights: Distribution by Company Size and Location of Headquarters
Table 13.20 Funding and Investments: Cumulative Year-wise Trend by Number of Instances
Table 13.21 Funding and Investments: Cumulative Year-wise Trend by Amount Invested
Table 13.22 Funding and Investments: Distribution of Instances by Type of Funding
Table 13.23 Funding and Investments: Distribution of Instances by Type of Funding and Amount Invested
Table 13.24 Funding and Investments: Distribution of Instances by Area of Application
Table 13.25 Funding and Investments: Distribution of Instances by Geography
Table 13.26 Most Active Players: Distribution by Number of Funding Instances
Table 13.27 Most Active Players: Distribution by Amount Raised
Table 13.28 Funding and Investments: Concluding Remarks
Table 13.29 Global Demand for AI-based Digital Pathology, 2022-2035 (Million Slides)
Table 13.30 Demand for AI-based Digital Pathology: Distribution by Geography, 2022 and 2035
Table 13.31 Demand for AI-based Digital Pathology in North America, 2022-2035 (Million Slides)
Table 13.32 Demand for AI-based Digital Pathology in the US, 2022-2035 (Million Slides)
Table 13.33 Demand for AI-based Digital Pathology in Canada, 2022-2035 (Million Slides)
Table 13.34 Demand for AI-based Digital Pathology in Europe, 2022-2035 (Million Slides)
Table 13.35 Demand for AI-based Digital Pathology in UK, 2022-2035 (Million Slides)
Table 13.36 Demand for AI-based Digital Pathology in Germany, 2022-2035 (Million Slides)
Table 13.37 Demand for AI-based Digital Pathology in Spain, 2022-2035 (Million Slides)
Table 13.38 Demand for AI-based Digital Pathology in Italy, 2022-2035 (Million Slides)
Table 13.39 Demand for AI-based Digital Pathology in France, 2022-2035 (Million Slides)
Table 13.40 Demand for AI-based Digital Pathology in Asia, 2022-2035 (Million Slides)
Table 13.41 Demand for AI-based Digital Pathology in China, 2022-2035 (Million Slides)
Table 13.42 Demand for AI-based Digital Pathology in Japan, 2022-2035 (Million Slides)
Table 13.43 Demand for AI-based Digital Pathology in South Korea, 2022-2035 (Million Slides)
Table 13.44 Demand for AI-based Digital Pathology in Latin America, 2022-2035 (Million Slides)
Table 13.45 Demand for AI-based Digital Pathology in Brazil, 2022-2035 (Million Slides)
Table 13.46 Demand for AI-based Digital Pathology in MENA, 2022-2035 (Million Slides)
Table 13.47 Demand for AI-based Digital Pathology in Saudi Arabia, 2022-2035 (Million Slides)
Table 13.48 Demand for AI-based Digital Pathology in Rest of the World, 2022-2035 (Million Slides)
Table 13.49 Demand for AI-based Digital Pathology in Australia, 2022-2035 (Million Slides)
Table 13.50 Global Demand for AI-based Digital Pathology: Distribution by End-users, 2022 and 2035
Table 13.51 Global Demand for AI-based Digital Pathology in Hospitals, 2022-2035 (Million Slides)
Table 13.52 Global Demand for AI-based Digital Pathology in Research Institutes, 2022-2035 (Million Slides)
Table 13.53 Global Demand for AI-based Digital Pathology in Other End-users, 2022-2035 (Million Slides)
Table 13.54 Global AI-based Digital Pathology Market, Conservative, Base and Optimistic Scenario, 2022-2035 (USD Million)
Table 13.55 AI-based Digital Pathology Market: Distribution by Type of Neural Network, 2022 and 2035
Table 13.56 AI-based Digital Pathology Market for Artificial Neural Network, Conservative, Base and Optimistic Scenario, 2022-2035 (USD Million)
Table 13.57 AI-based Digital Pathology Market for Convolutional Neural Network, Conservative, Base and Optimistic Scenario, 2022-2035 (USD Million)
Table 13.58 AI-based Digital Pathology Market for Fully Convolutional Network, Conservative, Base and Optimistic Scenario, 2022-2035 (USD Million)
Table 13.59 AI-based Digital Pathology Market for Recurrent Neural Network, Conservative, Base and Optimistic Scenario, 2022-2035 (USD Million)
Table 13.60 AI-based Digital Pathology Market for Other Neural Networks, 2022-2035, Conservative, Base and Optimistic Scenario, 2022-2035 (USD Million)
Table 13.61 AI-based Digital Pathology Market: Distribution by Type of Assay, 2022 and 2035
Table 13.62 AI-based Digital Pathology Market for ER Assay, Conservative, Base and Optimistic Scenario, 2022-2035 (USD Million)
Table 13.63 AI-based Digital Pathology Market for HER2 Assay, Conservative, Base and Optimistic Scenario, 2022-2035 (USD Million)
Table 13.64 AI-based Digital Pathology Market for Ki67 Assay, Conservative, Base and Optimistic Scenario, 2022-2035 (USD Million)
Table 13.65 AI-based Digital Pathology Market for PD-L1 Assay, Conservative, Base and Optimistic Scenario, 2022-2035 (USD Million)
Table 13.66 AI-based Digital Pathology Market for PR Assay, Conservative, Base and Optimistic Scenario, 2022-2035 (USD Million)
Table 13.67 AI-based Digital Pathology Market for Other Type of Assays, Conservative, Base and Optimistic Scenario, 2022-2035 (USD Million)
Table 13.68 AI-based Digital Pathology Market: Distribution by Type of End-user, 2022 and 2035
Table 13.69 AI-based Digital Pathology Market for Academic Institutions, Conservative, Base and Optimistic Scenario, 2022-2035 (USD Million)
Table 13.70 AI-based Digital Pathology Market for Hospitals / Healthcare Institutions, Conservative, Base and Optimistic Scenario, 2022-2035 (USD Million)
Table 13.71 AI-based Digital Pathology Market for Laboratories / Diagnostic Institutions, Conservative, Base and Optimistic Scenario, 2022-2035 (USD Million)
Table 13.72 AI-based Digital Pathology Market for Research Institutes, Conservative, Base and Optimistic Scenario, 2022-2035 (USD Million)
Table 13.73 AI-based Digital Pathology Market for Other End-users, Conservative, Base and Optimistic Scenario, 2022-2035 (USD Million)
Table 13.74 AI-based Digital Pathology Market: Distribution by Area of Application, 2022 and 2035
Table 13.75 AI-based Digital Pathology Market for Diagnostics, Conservative, Base and Optimistic Scenario, 2022-2035 (USD Million)
Table 13.76 AI-based Digital Pathology Market for Research, Conservative, Base and Optimistic Scenario, 2022-2035 (USD Million)
Table 13.77 AI-based Digital Pathology Market for Other Areas of Application, Conservative, Base and Optimistic Scenario, 2022-2035 (USD Million)
Table 13.78 AI-based Digital Pathology Market: Distribution by Target Disease Indication, 2022 and 2035
Table 13.79 AI-based Digital Pathology Market for Breast Cancer, Conservative, Base and Optimistic Scenario, 2022-2035 (USD Million)
Table 13.80 AI-based Digital Pathology Market for Colorectal Cancer, Conservative, Base and Optimistic Scenario, 2022-2035 (USD Million)
Table 13.81 AI-based Digital Pathology Market for Cervical Cancer, Conservative, Base and Optimistic Scenario, 2022-2035 (USD Million)
Table 13.82 AI-based Digital Pathology Market for Gastrointestinal Cancer, Conservative, Base and Optimistic Scenario, 2022-2035 (USD Million)
Table 13.83 AI-based Digital Pathology Market for Lung Cancer, Conservative, Base and Optimistic Scenario, 2022-2035 (USD Million)
Table 13.84 AI-based Digital Pathology Market for Prostate Cancer, Conservative, Base and Optimistic Scenario, 2022-2035 (USD Million)
Table 13.85 AI-based Digital Pathology Market for Other Indications, Conservative, Base and Optimistic Scenario, 2022-2035 (USD Million)
Table 13.86 AI-based Digital Pathology Market: Distribution by Key Geographies, 2022 and 2035
Table 13.87 AI-based Digital Pathology Market in North America, Conservative, Base and Optimistic Scenario, 2022-2035 (USD Million)
Table 13.88 AI-based Digital Pathology Market in the US, Conservative, Base and Optimistic Scenario, 2022-2035 (USD Million)
Table 13.89 AI-based Digital Pathology Market in Canada, Conservative, Base and Optimistic Scenario, 2022-2035 (USD Million)
Table 13.90 AI-based Digital Pathology Market in the Europe, Conservative, Base and Optimistic Scenario, 2022-2035 (USD Million)
Table 13.91 AI-based Digital Pathology Market in UK, Conservative, Base and Optimistic Scenario, 2022-2035 (USD Million)
Table 13.92 AI-based Digital Pathology Market in the Germany, Conservative, Base and Optimistic Scenario, 2022-2035 (USD Million)
Table 13.93 AI-based Digital Pathology Market in Spain, Conservative, Base and Optimistic Scenario, 2022-2035 (USD Million)
Table 13.94 AI-based Digital Pathology Market in Italy, Conservative, Base and Optimistic Scenario, 2022-2035 (USD Million)
Table 13.95 AI-based Digital Pathology Market in France, Conservative, Base and Optimistic Scenario, 2022-2035 (USD Million)
Table 13.96 AI-based Digital Pathology Market in Asia, Conservative, Base and Optimistic Scenario, 2022-2035 (USD Million)
Table 13.97 AI-based Digital Pathology Market in China, Conservative, Base and Optimistic Scenario, 2022-2035 (USD Million)
Table 13.98 AI-based Digital Pathology Market in Japan, Conservative, Base and Optimistic Scenario, 2022-2035 (USD Million)
Table 13.99 AI-based Digital Pathology Market in South Korea, Conservative, Base and Optimistic Scenario, 2022-2035 (USD Million)
Table 13.100 AI-based Digital Pathology Market in Latin America, Conservative, Base and Optimistic Scenario, 2022-2035 (USD Million)
Table 13.101 AI-based Digital Pathology Market in Brazil, Conservative, Base and Optimistic Scenario, 2022-2035 (USD Million)
Table 13.102 AI-based Digital Pathology Market in MENA, Conservative, Base and Optimistic Scenario, 2022-2035 (USD Million)
Table 13.103 AI-based Digital Pathology Market in Saudi Arabia, Conservative, Base and Optimistic Scenario, 2022-2035 (USD Million)
Table 13.104 AI-based Digital Pathology Market in Rest of the World, Conservative, Base and Optimistic Scenario, 2022-2035 (USD Million)
Table 13.105 AI-based Digital Pathology Market in Australia, Conservative, Base and Optimistic Scenario, 2022-2035 (USD Million)

List Of Companies

The following companies and organizations have been mentioned in the report:

  1. 3D HISTECH
  2. 50 Partners
  3. 83North
  4. 8VC
  5. ACME Investments
  6. Act Venture Capital
  7. Adage
  8. aetherAI
  9. Agilent
  10. Agilent Technologies
  11. Aiforia 
  12. Akoya Biosciences
  13. Aktia Nordic Micro Cap
  14. Alpha Intelligence Capital
  15. Alverno Laboratories
  16. aMoon
  17. AnaPath
  18. Angels Santé 
  19. APEX Ventures
  20. Ascend Capital Partners
  21. ATP
  22. Augmentiqs
  23. Augsburg University Hospital
  24. Aventior
  25. Axon Diagnostics
  26. BankInvest
  27. Bayern Kapital
  28. BGV
  29. Biospring Partners
  30. BioView
  31. Blue Venture Fund
  32. Breyer Capital
  33. Bristol Myers Squibb
  34. C.L. Davids Fond
  35. CADESS
  36. Casdin Capital
  37. Catalio Capital Management 
  38. CellCarta
  39. Charles River Laboratories
  40. Cleveland Clinic
  41. Corista
  42. Crosscope
  43. Clinitech Laboratory
  44. D1 Capital Partners
  45. Danhua Capital
  46. Databricks
  47. Datavant
  48. Deciphex
  49. Dedalus
  50. Deep Bio
  51. DeePathology.ai
  52. Dell
  53. DHVC
  54. Diagnexia
  55. Digital Pathology Lab
  56. Dr. Lal PathLabs
  57. Emerald Development Managers
  58. Enterprise Ireland
  59. Entrepreneurs Investis
  60. EOSIN Microscopic Intelligence
  61. Epredia
  62. Fairhaven Capital
  63. FFEI
  64. Flagship Biosciences
  65. Fluidigm
  66. Flybridge Capital Partners
  67. Fonds Ambition Amorçage Angels
  68. Fusion Fund
  69. General Atlantic
  70. General Catalyst
  71. Genuv
  72. Gestalt Diagnostics
  73. GI Partners
  74. GlaxoSmithKline
  75. Glencoe Software
  76. GNI Group
  77. Godman Sachs Merchant Banking division
  78. Grey Slide Imaging
  79. Halo Business Angel Network 
  80. Hamamatsu Photonics
  81. HBAN MedTech Syndicate HealthCare VenturesHealthQuest Capital
  82. Highline Capital Management
  83. High-Tech Gründerfonds
  84. HistoIndex
  85. Hitachi Ventures
  86. Hologic
  87. Hospitex International
  88. Huron Digital Pathology
  89. Ibex Medical Analytics
  90. ImaBiotech
  91. Imsight
  92. Indica Labs
  93. iCAIRD
  94. INFINITT
  95. Inform Diagnostics
  96. Innovationsstarter Fonds HamburgInnovatus Capital Partners
  97. Inovata Personalised Health Accelerator
  98. Inspirata
  99. Intel
  100. Invicro
  101. Irrus Investments
  102. Janssen
  103. JiNan Danjier Electronics
  104. JLK
  105. Johnson & Johnson Innovation
  106. Kaiser Permanente
  107. Kamet Ventures
  108. KdT Ventures
  109. Kenan Turnacioglu
  110. KFBIO
  111. KKR
  112. LabCorp
  113. Leica Biosystems
  114. Lumea
  115. Lunaphore
  116. Mayo Clinic
  117. Mechanomind
  118. Merck
  119. microDimensions
  120. Mindpeak
  121. Motic Digital PathologyMotu Ventures
  122. NantOmics
  123. National Cancer Institute
  124. National Science Foundation
  125. NextStep Ventures NGD-Lab
  126. Nina Capital
  127. NorthCap UniversityNovartis
  128. Octopus Ventures
  129. OneCell
  130. Ontario Centres of Excellence
  131. Opta-Tech
  132. OptraScan
  133. OracleBio
  134. Orange Digital Ventures
  135. Oxford University Innovation 
  136. Paige
  137. Parapixel
  138. Parkwalk Advisors
  139. Partech
  140. PathAI
  141. Pathan
  142. Pathcore
  143. PereDoc
  144. Perspectum
  145. PHC 
  146. Philips
  147. Pictor Labs
  148. Pillar VC
  149. Piper Jaffray Merchant Banking
  150. Planven Entrepreneur Ventures
  151. Plug and PlayPolaris Partners
  152. Poplar Healthcare
  153. PP Capital
  154. Pramana
  155. Primaa
  156. PROSCIA
  157. Puhua Capital
  158. Quest Diagnostics
  159. Razor’s Edge Ventures
  160. Refactor Capital
  161. Reveal Biosciences
  162. Robin Hood Ventures ROBO Global
  163. Roche Tissue Diagnostics
  164. RT Capital Management
  165. Sana Kliniken Berlin-Brandenburg
  166. Scale Venture Partners
  167. Sectra
  168. Sentient Med
  169. Siemens Healthineers
  170. SigTuple
  171. Smart In MediaSonora Quest Laboratories
  172. STO-Rahoitus
  173. S V Market
  174. Targos
  175. TechcyteTelegraph Hill Partners
  176. Tiger Global Management
  177. Triangle Peak Partners
  178. Tribun Health
  179. U.S. Department of Energy
  180. Ultivue
  181. Unilabs
  182. UNIM
  183. University of Edinburgh
  184. UofL HealthUniversity of Oxford
  185. US Department of Energy
  186. Vækstfonden
  187. ViQi
  188. Visiopharm
  189. Western Digital Capital
  190. WSK Medical
  191. XIFIN
  192. ZayaAI
  193. Zegami

Source 1: https://www.cancer.org/research/cancer-facts-statistics/global.html
Source 2: https://www.philips.co.uk/healthcare/sites/pathology/about/why-go-digital

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