Product Code: GVR-4-68040-548-5
Computational Pathology Market Growth & Trends:
The global computational pathology market size is expected to reach USD 1.04 billion by 2030, registering a CAGR of 8.24% from 2025 to 2030, according to a new report by Grand View Research, Inc. This growth can be attributed to the rising prevalence of chronic diseases, the increasing demand for advanced solutions for faster diagnosis, the rising integration of Machine Learning (ML) and artificial intelligence (AI) technologies and increasing investment in healthcare supported by market players focused on developing advanced solutions.
Integrating artificial intelligence (AI) and machine learning (ML) algorithms into digital pathology workflows is revolutionizing the field, enabling faster and more accurate analysis of pathology images. AI-powered tools can assist pathologists in detecting patterns, predicting disease progression, and giving clinically relevant insights crucial for disease detection. For instance, In September 2024, Paige introduced Paige Alba, a clinical-grade multimodal co-pilot aimed at transforming personalized medicine and precision oncology. Alba provides real-time, AI-driven insights from patient data, enhancing clinical decision-making at unprecedented speed and scale. This innovation represents a major leap toward Artificial General Intelligence (AGI) in healthcare, bringing the industry closer to a future where AI not only supports but collaborates with clinicians in diagnosing and treating complex diseases such as cancer.
Several companies operating in the market also focusing on developing innovative solutions to enhance the application and performance of computational pathology. For instance, in August 2023, Microsoft and Paige researchers developed Virchow2 and Virchow2G, second-generation foundation models for computational pathology. These large language models are trained on vast amounts of pathology data to understand the complex relationships between clinical information, pathology findings, and disease outcomes.
Virchow2 and Virchow2G can generate human-readable text, answer questions, and assist in tasks like report generation and case summarization. The models are designed to be fine-tuned for specific tasks, enabling their use in various computational pathology applications. This advancement represents a significant step forward in leveraging AI to enhance pathologists' decision-making and improve patient care in computational pathology. Similarly, transitioning from traditional microscopy to digital pathology further contributes to the market growth. This shift enhances accessibility and facilitates remote consultations and collaborative efforts among pathologists worldwide.
The COVID-19 pandemic has accelerated this trend as healthcare systems search for alternatives to execute operations while ensuring compliance with safety protocols. Furthermore, regulatory bodies significantly contribute to digital pathology's growth, leading to approvals for various digital imaging systems and software applications. As organizations invest in infrastructure to support digital workflows, the market is expected to witness significant growth driven by enhanced operational efficiencies and improved diagnostic capabilities.
Computational Pathology Market Report Highlights:
- Based on component, software segment dominated the market in 2024 owing to the various advantages offered by these solutions that help in enhancing clinical workflows.
- Based on application, disease diagnosis dominated the application segment with a revenue share of 45.7% in 2024 owing to the rising demand for more effective and accurate diagnosis tools in hospitals and diagnostics centers globally.
- Based on technology, machine learning dominated the market in 2024 owing to the rising development of computational pathology solutions with integrated ML technologies that offer better performance and outcomes in healthcare facilities.
- Based on end use, hospitals and diagnostic labs segment held the largest market share of 51.09% in 2024, driven by the increasing demand for advanced diagnostic tools and efficient workflow solutions.
- North America held the largest market share of 40.5% in 2024. This can be attributed to the regions developed healthcare infrastructure and increasing access to the computational pathology solutions coupled with the rising incidents of the chronic diseases such as cancer.
- Major players are employing various strategies such as product launches, collaborations, acquisitions, and mergers to expand their service portfolios and enhance their geographical presence, leading to significant competition within the market. For instance, in February 2023, ClaraPath acquired Crosscope to integrate tissue processing robotics with AI-powered digital pathology, aiming to create the "lab of the future." This combination enhances workflow efficiency by automating tissue processing while leveraging AI technologies for advanced image analysis and diagnostics.
Table of Contents
Chapter 1. Research Methodology and Scope
- 1.1. Market Segmentation & Scope
- 1.1.1. Regional scope
- 1.1.2. Component
- 1.1.3. Technology
- 1.1.4. Application
- 1.1.5. End Use
- 1.1.6. Estimates and forecast timeline.
- 1.2. Research Methodology
- 1.3. Information Procurement
- 1.3.1. Purchased database.
- 1.3.2. GVR's internal database
- 1.3.3. Secondary sources
- 1.3.4. Primary research
- 1.3.5. Details of primary research
- 1.4. Information or Data Analysis
- 1.4.1. Data analysis models
- 1.5. Market Formulation & Validation
- 1.6. Model Details
- 1.6.1. Commodity flow analysis (Model 1)
- 1.6.2. Approach 1: Commodity flow approach
- 1.7. List of Secondary Sources
- 1.8. List of Primary Sources
- 1.9. Objectives
Chapter 2. Executive Summary
- 2.1. Market Outlook
- 2.2. Segment Outlook
- 2.2.1. Component
- 2.2.2. Technology
- 2.2.3. Application
- 2.2.4. End Use
- 2.2.5. Regional outlook
- 2.3. Competitive Insights
Chapter 3. Computational Pathology Market Variables, Trends & Scope
- 3.1. Market Dynamics
- 3.1.1. Market driver analysis
- 3.1.2. Market restraint analysis
- 3.1.3. Market Opportunity Analysis
- 3.2. Computational Pathology Market Analysis Tools
- 3.2.1. Industry Analysis - Porter's
- 3.2.1.1. Supplier power
- 3.2.1.2. Buyer power
- 3.2.1.3. Substitution threat
- 3.2.1.4. Threat of new entrant
- 3.2.1.5. Competitive rivalry
- 3.2.2. PESTEL Analysis
- 3.2.2.1. Political landscape
- 3.2.2.2. Economic landscape
- 3.2.2.3. Social landscape
- 3.2.2.4. Technological landscape
- 3.2.2.5. Environmental landscape
- 3.2.2.6. Legal landscape
- 3.2.3. Emerging Technology Trends
- 3.2.4. COVID-19 Impact Analysis
- 3.2.5. Case Study Analysis
Chapter 4. Computational Pathology Market: Component Estimates & Trend Analysis
- 4.1. Component Market Share, 2024 & 2030
- 4.2. Segment Dashboard
- 4.3. Global Computational Pathology Market by Component Outlook
- 4.4. Software
- 4.4.1. Market estimates and forecast 2018 to 2030 (USD Million)
- 4.5. Services
- 4.5.1. Market estimates and forecast 2018 to 2030 (USD Million)
Chapter 5. Computational Pathology Market: Application Estimates & Trend Analysis
- 5.1. Application Market Share, 2024 & 2030
- 5.2. Segment Dashboard
- 5.3. Global Computational Pathology Market by Application Outlook
- 5.4. Disease Diagnosis
- 5.4.1. Market estimates and forecast 2018 to 2030 (USD Million)
- 5.5. Drug Discovery & Development
- 5.5.1. Market estimates and forecast 2018 to 2030 (USD Million)
- 5.6. Academic Research
- 5.6.1. Market estimates and forecast 2018 to 2030 (USD Million)
Chapter 6. Computational Pathology Market: Technology Estimates & Trend Analysis
- 6.1. Technology Market Share, 2024 & 2030
- 6.2. Segment Dashboard
- 6.3. Global Computational Pathology Market by Technology Outlook
- 6.4. Machine Learning (ML)
- 6.4.1. Market estimates and forecast 2018 to 2030 (USD Million)
- 6.4.2. Deep Learning
- 6.4.2.1. Market estimates and forecast 2018 to 2030 (USD Million)
- 6.4.3. Others
- 6.4.3.1. Market estimates and forecast 2018 to 2030 (USD Million)
- 6.5. Natural Language Processing (NLP) Models
- 6.5.1. Market estimates and forecast 2018 to 2030 (USD Million)
- 6.6. Computer Vision
- 6.6.1. Market estimates and forecast 2018 to 2030 (USD Million)
- 6.7. Others
- 6.7.1. Market estimates and forecast 2018 to 2030 (USD Million)
Chapter 7. Computational Pathology Market: End Use Estimates & Trend Analysis
- 7.1. End Use Market Share, 2024 & 2030
- 7.2. Segment Dashboard
- 7.3. Global Computational Pathology Market by End Use Outlook
- 7.4. Hospitals and Diagnostic Labs
- 7.4.1. Market estimates and forecast 2018 to 2030 (USD Million)
- 7.5. Biotechnology and Pharmaceutical Companies
- 7.5.1. Market estimates and forecast 2018 to 2030 (USD Million)
- 7.6. Academic and Research Institutes
- 7.6.1. Market estimates and forecast 2018 to 2030 (USD Million)
- 7.7. Others
- 7.7.1. Market estimates and forecast 2018 to 2030 (USD Million)
Chapter 8. Computational Pathology Market: Regional Estimates & Trend Analysis, By Component, By Application, By Technology, By End Use
- 8.1. Regional Market Share Analysis, 2024 & 2030
- 8.2. Regional Market Dashboard
- 8.3. Global Regional Market Snapshot
- 8.4. Market Size & Forecasts Trend Analysis, 2018 to 2030:
- 8.5. North America
- 8.5.1. U.S.
- 8.5.1.1. Key country dynamics
- 8.5.1.2. Regulatory framework
- 8.5.1.3. Competitive scenario
- 8.5.1.4. U.S. market estimates and forecasts 2018 to 2030 (USD Million)
- 8.5.2. Canada
- 8.5.2.1. Key country dynamics
- 8.5.2.2. Regulatory framework
- 8.5.2.3. Competitive scenario
- 8.5.2.4. Canada market estimates and forecasts 2018 to 2030 (USD Million)
- 8.5.3. Mexico
- 8.5.3.1. Key country dynamics
- 8.5.3.2. Regulatory framework
- 8.5.3.3. Competitive scenario
- 8.5.3.4. Canada market estimates and forecasts 2018 to 2030 (USD Million)
- 8.6. Europe
- 8.6.1. UK
- 8.6.1.1. Key country dynamics
- 8.6.1.2. Regulatory framework
- 8.6.1.3. Competitive scenario
- 8.6.1.4. UK market estimates and forecasts 2018 to 2030 (USD Million)
- 8.6.2. Germany
- 8.6.2.1. Key country dynamics
- 8.6.2.2. Regulatory framework
- 8.6.2.3. Competitive scenario
- 8.6.2.4. Germany market estimates and forecasts 2018 to 2030 (USD Million)
- 8.6.3. France
- 8.6.3.1. Key country dynamics
- 8.6.3.2. Regulatory framework
- 8.6.3.3. Competitive scenario
- 8.6.3.4. France market estimates and forecasts 2018 to 2030 (USD Million)
- 8.6.4. Italy
- 8.6.4.1. Key country dynamics
- 8.6.4.2. Regulatory framework
- 8.6.4.3. Competitive scenario
- 8.6.4.4. Italy market estimates and forecasts 2018 to 2030 (USD Million)
- 8.6.5. Spain
- 8.6.5.1. Key country dynamics
- 8.6.5.2. Regulatory framework
- 8.6.5.3. Competitive scenario
- 8.6.5.4. Spain market estimates and forecasts 2018 to 2030 (USD Million)
- 8.6.6. Norway
- 8.6.6.1. Key country dynamics
- 8.6.6.2. Regulatory framework
- 8.6.6.3. Competitive scenario
- 8.6.6.4. Norway market estimates and forecasts 2018 to 2030 (USD Million)
- 8.6.7. Sweden
- 8.6.7.1. Key country dynamics
- 8.6.7.2. Regulatory framework
- 8.6.7.3. Competitive scenario
- 8.6.7.4. Sweden market estimates and forecasts 2018 to 2030 (USD Million)
- 8.6.8. Denmark
- 8.6.8.1. Key country dynamics
- 8.6.8.2. Regulatory framework
- 8.6.8.3. Competitive scenario
- 8.6.8.4. Denmark market estimates and forecasts 2018 to 2030 (USD Million)
- 8.7. Asia Pacific
- 8.7.1. Japan
- 8.7.1.1. Key country dynamics
- 8.7.1.2. Regulatory framework
- 8.7.1.3. Competitive scenario
- 8.7.1.4. Japan market estimates and forecasts 2018 to 2030 (USD Million)
- 8.7.2. China
- 8.7.2.1. Key country dynamics
- 8.7.2.2. Regulatory framework
- 8.7.2.3. Competitive scenario
- 8.7.2.4. China market estimates and forecasts 2018 to 2030 (USD Million)
- 8.7.3. India
- 8.7.3.1. Key country dynamics
- 8.7.3.2. Regulatory framework
- 8.7.3.3. Competitive scenario
- 8.7.3.4. India market estimates and forecasts 2018 to 2030 (USD Million)
- 8.7.4. Australia
- 8.7.4.1. Key country dynamics
- 8.7.4.2. Regulatory framework
- 8.7.4.3. Competitive scenario
- 8.7.4.4. Australia market estimates and forecasts 2018 to 2030 (USD Million)
- 8.7.5. South Korea
- 8.7.5.1. Key country dynamics
- 8.7.5.2. Regulatory framework
- 8.7.5.3. Competitive scenario
- 8.7.5.4. South Korea market estimates and forecasts 2018 to 2030 (USD Million)
- 8.7.6. Thailand
- 8.7.6.1. Key country dynamics
- 8.7.6.2. Regulatory framework
- 8.7.6.3. Competitive scenario
- 8.7.6.4. Singapore market estimates and forecasts 2018 to 2030 (USD Million)
- 8.8. Latin America
- 8.8.1. Brazil
- 8.8.1.1. Key country dynamics
- 8.8.1.2. Regulatory framework
- 8.8.1.3. Competitive scenario
- 8.8.1.4. Brazil market estimates and forecasts 2018 to 2030 (USD Million)
- 8.8.2. Argentina
- 8.8.2.1. Key country dynamics
- 8.8.2.2. Regulatory framework
- 8.8.2.3. Competitive scenario
- 8.8.2.4. Argentina market estimates and forecasts 2018 to 2030 (USD Million)
- 8.9. MEA
- 8.9.1. South Africa
- 8.9.1.1. Key country dynamics
- 8.9.1.2. Regulatory framework
- 8.9.1.3. Competitive scenario
- 8.9.1.4. South Africa market estimates and forecasts 2018 to 2030 (USD Million)
- 8.9.2. Saudi Arabia
- 8.9.2.1. Key country dynamics
- 8.9.2.2. Regulatory framework
- 8.9.2.3. Competitive scenario
- 8.9.2.4. Saudi Arabia market estimates and forecasts 2018 to 2030 (USD Million)
- 8.9.3. UAE
- 8.9.3.1. Key country dynamics
- 8.9.3.2. Regulatory framework
- 8.9.3.3. Competitive scenario
- 8.9.3.4. UAE market estimates and forecasts 2018 to 2030 (USD Million)
- 8.9.4. Kuwait
- 8.9.4.1. Key country dynamics
- 8.9.4.2. Regulatory framework
- 8.9.4.3. Competitive scenario
- 8.9.4.4. Kuwait market estimates and forecasts 2018 to 2030 (USD Million)
Chapter 9. Competitive Landscape
- 9.1. Recent Developments & Impact Analysis, By Key Market Participants
- 9.2. Company/Competition Categorization
- 9.3. Key company market share/position analysis, 2024
- 9.4. Company Profiles
- 9.4.1. Leica Biosystems Nussloch GmbH (Danaher)
- 9.4.1.1. Company overview
- 9.4.1.2. Financial performance
- 9.4.1.3. Product benchmarking
- 9.4.1.4. Strategic initiatives
- 9.4.2. Hamamatsu Photonics K.K.
- 9.4.2.1. Company overview
- 9.4.2.2. Financial performance
- 9.4.2.3. Product benchmarking
- 9.4.2.4. Strategic initiatives
- 9.4.3. Koninklijke Philips N.V.
- 9.4.3.1. Company overview
- 9.4.3.2. Financial performance
- 9.4.3.3. Product benchmarking
- 9.4.3.4. Strategic initiatives
- 9.4.4. Olympus Corporation
- 9.4.4.1. Company overview
- 9.4.4.2. Financial performance
- 9.4.4.3. Product benchmarking
- 9.4.4.4. Strategic initiatives
- 9.4.5. F. Hoffmann-La Roche Ltd.
- 9.4.5.1. Company overview
- 9.4.5.2. Financial performance
- 9.4.5.3. Product benchmarking
- 9.4.5.4. Strategic initiatives
- 9.4.6. Mikroscan Technologies, Inc.
- 9.4.6.1. Company overview
- 9.4.6.2. Financial performance
- 9.4.6.3. Product benchmarking
- 9.4.6.4. Strategic initiatives
- 9.4.7. Epredia (3DHISTECH Ltd.)
- 9.4.7.1. Company overview
- 9.4.7.2. Financial performance
- 9.4.7.3. Product benchmarking
- 9.4.7.4. Strategic initiatives
- 9.4.8. Visiopharm A/S
- 9.4.8.1. Company overview
- 9.4.8.2. Financial performance
- 9.4.8.3. Product benchmarking
- 9.4.8.4. Strategic initiatives
- 9.4.9. Proscia Inc.
- 9.4.9.1. Company overview
- 9.4.9.2. Financial performance
- 9.4.9.3. Product benchmarking
- 9.4.9.4. Strategic initiatives
- 9.4.10. Tempus
- 9.4.10.1. Company overview
- 9.4.10.2. Financial performance
- 9.4.10.3. Product benchmarking
- 9.4.10.4. Strategic initiatives
- 9.4.11. Huron Technologies International Inc.
- 9.4.11.1. Company overview
- 9.4.11.2. Financial performance
- 9.4.11.3. Product benchmarking
- 9.4.11.4. Strategic initiatives
- 9.4.12. ContextVision AB
- 9.4.12.1. Company overview
- 9.4.12.2. Financial performance
- 9.4.12.3. Product benchmarking
- 9.4.12.4. Strategic initiatives
- 9.4.13. CellaVision
- 9.4.13.1. Company overview
- 9.4.13.2. Financial performance
- 9.4.13.3. Product benchmarking
- 9.4.13.4. Strategic initiatives
- 9.4.14. aetherAI
- 9.4.14.1. Company overview
- 9.4.14.2. Financial performance
- 9.4.14.3. Product benchmarking
- 9.4.14.4. Strategic initiatives
- 9.4.15. CellCarta
- 9.4.15.1. Company overview
- 9.4.15.2. Financial performance
- 9.4.15.3. Product benchmarking
- 9.4.15.4. Strategic initiatives
- 9.4.16. IBEX (IBEX MEDICAL ANALYTICS)
- 9.4.16.1. Company overview
- 9.4.16.2. Financial performance
- 9.4.16.3. Product benchmarking
- 9.4.16.4. Strategic initiatives
- 9.4.17. Nucleai, Inc.
- 9.4.17.1. Company overview
- 9.4.17.2. Financial performance
- 9.4.17.3. Product benchmarking
- 9.4.17.4. Strategic initiatives