AI-based Digital 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

December 2022 | 212 pages | ID: A5B291F42B07EN
Roots Analysis

Abstracts

Pathology, an essential field in medicine, focuses on comprehending the nature, causes, and origins of diseases. It is pivotal in diagnosing various conditions, especially cancer, contributing significantly to healthcare decisions—around 70-80%. The projected surge in cancer cases, expected to reach 27 million new cases annually by 2040, alongside an aging population, anticipates a substantial increase in pathologists' workload. However, there's a declining number of active pathologists, estimated to drop by 30% by 2030 compared to 2010, with about 63.2% expected to retire in the next decade. This could create a significant gap between the demand for pathology services and the available pathologists.

Technological advancements, notably AI-driven digital imaging, have revolutionized pathology. AI-based digital pathology involves digitizing patient samples to create high-resolution digital slides for analysis. This innovation significantly improves diagnostic accuracy and research capabilities. It addresses the growing workload by enabling faster and more consistent diagnoses, facilitating remote collaboration, reducing errors, increasing productivity, and saving costs. Investments in digital pathology have soared, exceeding $1.6 billion since 2016, with substantial funding in 2021 alone. The recent collaboration between 3DHISTECH and Epredia to speed up cancer diagnostics through a pathology innovation incubator demonstrates the industry's growth and dedication to enhancing healthcare and research. Experts foresee a steady market growth in the upcoming years due to the rising demand for AI-based digital pathology solutions and continuous advancements in this field.

Report Coverage

• The report conducts an examination of the digital pathology market, focusing on type of neural network, type of assay, type of end-user, area of application, type of target disease indication and key geographies
• It analyzes the market's growth factors such as drivers, restraints, opportunities, and challenges that impact its progression.
• Assessment of potential advantages and obstacles within the market is provided, along with insights into the competitive landscape for leading market players.
• Revenue forecasts for market segments are presented concerning six major regions.
• A comprehensive overview summarizes research insights on the present state and anticipated evolution of the AI-based digital pathology market in the medium to long term.
• The introduction to AI-based digital pathology delves into artificial intelligence applications within digital pathology, outlining workflows, healthcare applications, and regulatory requirements. It concludes with discussions on challenges, growth drivers, and future prospects of AI in digital pathology.
• Detailed evaluation of AI-based digital pathology companies considers parameters such as geographical reach, establishment year, company size, headquarters location, product and service types, features, applications, target diseases, end-users, and available software count.
• In-depth analysis covers contemporary market trends including service and application distribution, feature and application distribution, product types and headquarters location, and a hybrid representation of company size and headquarters location.
• Elaborate profiles of notable companies in this domain encompass company overview, establishment year, employee count, headquarters location, management team, recent developments, and future outlook.
• Evaluation of industry players' capabilities across various services in AI-based digital pathology facilitates comparison within peer groups and identifies opportunities for competitive advantage. This includes benchmarking based on portfolio strength and funding activity.
• Analysis of funding and investments in digital pathology from 2016 to 2022 details instances, invested amounts, funding types, application areas, geographies, and active players in the AI-based digital pathology domain.
• Thorough analysis aims to estimate present and future demand based on geographical regions (North America, Europe, Asia, Latin America, MENA, Rest of the World) and end-users (hospitals, research, and other sectors).

Key Market Companies

• PathAI
• Paige
• Akoya Biosciences
• PROSCIA
• Visiopharm
• Roche Tissue Diagnostics
• Aiforia Technologies
• Indica Labs
• Ibex Medical Analytics

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