AI-based Digital Pathology Market: Industry Trends and Global Forecasts, Till 2035 - Distribution by Type of Neural Network, Type of Assay, Type of End-User, Area of Application, Target Disease Indication and Key Geographies:
Description
AI-based Digital Pathology Market: Overview
As per Roots Analysis, the global AI-based digital pathology market is estimated to grow from USD 1.01 billion in the current year to USD 2.32 billion by 2035, at a CAGR of 8.7% during the forecast period, till 2035.
Type of Neural Network
In recent years, advancements in technology and an emphasis on precision medicine have paved the way for the development of artificial intelligence (AI), which has spurred digital pathology techniques for both quantitative and qualitative assessment of samples. The improved technique allows for the examination of slides via computer displays, replacing conventional microscopic approaches. Additionally, converting glass slides into images allows for samples to be transmitted from diagnostic centers to pathologists much more quickly. It is essential to highlight that the integration of AI has significantly enhanced the understanding of tissue micro-environment. AI involvement in diagnosis enables the determination of optimal treatment strategies suited to patient profiles, utilizing digital methods for categorizing patients and selecting individuals for diagnostic evaluations.
Given the vast amount of data generated in pathology, AI is expected to offer an opportunity for innovation across all pathology subdomains, enabling a transformative model for care delivery in both imaging and non-imaging areas. As a result of the aforementioned advantages over conventional techniques in pathology, the AI-based digital pathology sector has seen significant growth in recent times, with these solutions becoming increasingly popular in research, development, and clinical settings.
AI-based Digital Pathology Market: Key Insights
The report delves into the current state of the AI-based digital pathology market and identifies potential growth opportunities within the industry. Some key findings from the report include:
Convolutional Neural Network is Likely to Dominate the AI-based Digital Pathology Market During the Forecast Period
In terms of the type of neural network, the market is segmented into artificial neural network, convolutional neural network, fully convolutional network, recurrent neural network and other neural network. The maximum share of the AI-based digital pathology market is captured by convolutional neural network. It is worth highlighting that the AI-based digital pathology market for artificial neural networks is likely to grow at a higher CAGR.
Currently, Ki67 Assays Occupy the Largest Share of the AI-based Digital Pathology Market
In terms of type of assay, the market is segmented into ER assay, HER2 assay, Ki67 assay, PR assay and other type of assay. The majority of the AI-based digital pathology market share is captured by Ki67 assay. This is due to the fact that the expression of Ki67 assays is highly related to cell proliferation and hence, is frequently employed in routine pathology, as a proliferation marker to quantify the growth fraction of cells in human malignancies.
Currently, Research Institutes Occupy the Largest Share of the AI-based Digital Pathology Market
In terms of type of end-user, the market is segmented into academic institutions, hospitals/ healthcare institutions, laboratories / diagnostic institutions, research institutes and other end-users. Currently, research institutes hold the maximum share of the AI-based digital pathology market and the trend will be similar in the coming years.
Diagnostics Segment is the Fastest Growing Segment of the AI-based Digital Pathology Market During the Forecast Period
In terms of area of application, the market is segmented into diagnostics, research and other areas of application. It is worth highlighting that, at present, the research segment holds a larger share of the AI-based digital pathology market. However, the AI-based digital pathology market for diagnostics is likely to grow at a higher CAGR.
Breast Cancer is Likely to Dominate the AI-based Digital Pathology Market During the Forecast Period
In terms of the target disease indication, the market is segmented into breast cancer, colorectal cancer, cervical cancer, gastrointestinal cancer, lung cancer, prostate cancer and other indications. It is worth highlighting that majority of the current AI-based digital pathology market is captured by breast cancer. This trend is likely to remain the same in the coming decade.
North America Accounts for the Largest Share of the Market
In terms of key geographical regions, the market is segmented into North America, Europe, Asia Pacific, Latin America, Middle East and North Africa, and the Rest of the World. The majority of the share is expected to be captured by players based in North America. It is worth highlighting that, over the years, the market in Europe is expected to grow at a higher CAGR.
Example Players in the AI-based Digital Pathology Market
The opinions and insights presented in this study were influenced by discussions conducted with multiple stakeholders. The research report features detailed transcripts of interviews held with the following industry stakeholders:
As per Roots Analysis, the global AI-based digital pathology market is estimated to grow from USD 1.01 billion in the current year to USD 2.32 billion by 2035, at a CAGR of 8.7% during the forecast period, till 2035.
Type of Neural Network
- Artificial Neural Network
- Convolutional Neural Network
- Fully Convolutional Network,
- Recurrent Neural Network
- Other Neural Network
- ER Assay
- HER2 Assay
- KI67, PR Assay
- Other Type of Assay
- Academic Institutions
- Hospitals / Healthcare Institutions
- Laboratories / Diagnostic Institutions
- Research Institutes
- Other End-Users
- Diagnostics
- Research
- Other Areas of Application
- Breast Cancer
- Colorectal Cancer
- Cervical Cancer
- Gastrointestinal Cancer
- Lung Cancer
- Prostate Cancer
- Other Indications
- North America
- Europe
- Asia-Pacific
- Middle East and North Africa
- Latin America
In recent years, advancements in technology and an emphasis on precision medicine have paved the way for the development of artificial intelligence (AI), which has spurred digital pathology techniques for both quantitative and qualitative assessment of samples. The improved technique allows for the examination of slides via computer displays, replacing conventional microscopic approaches. Additionally, converting glass slides into images allows for samples to be transmitted from diagnostic centers to pathologists much more quickly. It is essential to highlight that the integration of AI has significantly enhanced the understanding of tissue micro-environment. AI involvement in diagnosis enables the determination of optimal treatment strategies suited to patient profiles, utilizing digital methods for categorizing patients and selecting individuals for diagnostic evaluations.
Given the vast amount of data generated in pathology, AI is expected to offer an opportunity for innovation across all pathology subdomains, enabling a transformative model for care delivery in both imaging and non-imaging areas. As a result of the aforementioned advantages over conventional techniques in pathology, the AI-based digital pathology sector has seen significant growth in recent times, with these solutions becoming increasingly popular in research, development, and clinical settings.
AI-based Digital Pathology Market: Key Insights
The report delves into the current state of the AI-based digital pathology market and identifies potential growth opportunities within the industry. Some key findings from the report include:
- Presently, close to 80 players claim to provide AI-based digital pathology services to multiple end-users located across different geographical locations.
- Leveraging their expertise, stakeholders are offering a range of AI-based services for pathology applications; such solutions are primarily being employed by research institutes and laboratory / diagnostic institutions.
- Companies engaged in this domain are offering a range of features through their proprietary products, intended for both research and diagnostic applications.
- Having realized the opportunity associated with this segment, investors have collectively invested ~USD 2 billion, across 60 funding instances.
- A number of factors, such as inclusion of research, as well as the incorporation of AI in the clinical workflow, have led to a rise in the adoption of AI-based digital pathology tools, on a global scale.
- Driven by the rise in demand for AI-based digital pathology solutions and the growing preference for more accessible healthcare services, this market is anticipated to grow at an annualized rate of 8.70% till 2035.
Convolutional Neural Network is Likely to Dominate the AI-based Digital Pathology Market During the Forecast Period
In terms of the type of neural network, the market is segmented into artificial neural network, convolutional neural network, fully convolutional network, recurrent neural network and other neural network. The maximum share of the AI-based digital pathology market is captured by convolutional neural network. It is worth highlighting that the AI-based digital pathology market for artificial neural networks is likely to grow at a higher CAGR.
Currently, Ki67 Assays Occupy the Largest Share of the AI-based Digital Pathology Market
In terms of type of assay, the market is segmented into ER assay, HER2 assay, Ki67 assay, PR assay and other type of assay. The majority of the AI-based digital pathology market share is captured by Ki67 assay. This is due to the fact that the expression of Ki67 assays is highly related to cell proliferation and hence, is frequently employed in routine pathology, as a proliferation marker to quantify the growth fraction of cells in human malignancies.
Currently, Research Institutes Occupy the Largest Share of the AI-based Digital Pathology Market
In terms of type of end-user, the market is segmented into academic institutions, hospitals/ healthcare institutions, laboratories / diagnostic institutions, research institutes and other end-users. Currently, research institutes hold the maximum share of the AI-based digital pathology market and the trend will be similar in the coming years.
Diagnostics Segment is the Fastest Growing Segment of the AI-based Digital Pathology Market During the Forecast Period
In terms of area of application, the market is segmented into diagnostics, research and other areas of application. It is worth highlighting that, at present, the research segment holds a larger share of the AI-based digital pathology market. However, the AI-based digital pathology market for diagnostics is likely to grow at a higher CAGR.
Breast Cancer is Likely to Dominate the AI-based Digital Pathology Market During the Forecast Period
In terms of the target disease indication, the market is segmented into breast cancer, colorectal cancer, cervical cancer, gastrointestinal cancer, lung cancer, prostate cancer and other indications. It is worth highlighting that majority of the current AI-based digital pathology market is captured by breast cancer. This trend is likely to remain the same in the coming decade.
North America Accounts for the Largest Share of the Market
In terms of key geographical regions, the market is segmented into North America, Europe, Asia Pacific, Latin America, Middle East and North Africa, and the Rest of the World. The majority of the share is expected to be captured by players based in North America. It is worth highlighting that, over the years, the market in Europe is expected to grow at a higher CAGR.
Example Players in the AI-based Digital Pathology Market
- Aiforia Technologies
- Akoya Biosciences
- Ibex Medical Analytics
- Indica Labs
- Paige
- PathAI
- PROSCIA
- Roche Tissue Diagnostics
- Visiopharm
The opinions and insights presented in this study were influenced by discussions conducted with multiple stakeholders. The research report features detailed transcripts of interviews held with the following industry stakeholders:
- Chief Executive Officer and Chairman, Company A
- Laboratory Director and Chief Pathologist, Company B
- Vice President (Research and Technology), Company C
- Vice President (Sales and Marketing), Company D
- Market Sizing and Opportunity Analysis: The report features an in-depth analysis of the AI-based digital pathology market, focusing on key market segments, including [A] type of neural network, [B] type of assay, [C] type of end-user, [D] area of application, [E] target disease indication and [F] key geographical regions.
- Market Landscape: A comprehensive evaluation of AI-based digital pathology companies, considering various parameters, such as [A] geographical reach, [B] year of establishment, [C] company size (in terms of number of employees), [D] location of headquarters, [E] type of product, [F] type of service, [G] type of feature, [H] additional features, [I] area of application, [J] target disease indication, [K] type of assay, [L] type of end-user and [M] information on number of available software.
- Key Insights: 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 an insightful hybrid representation of AI-based digital pathology companies based on [E] company size and [F] location of headquarters.
- Company Profiles: In-depth profiles of key AI-based digital pathology companies offering AI-based digital pathology services, focusing on [A] company overviews, [B] recent developments and [C] an informed future outlook.
- Company Competitiveness Analysis: A comprehensive competitive analysis of AI-based digital pathology companies, examining factors, such as portfolio strength and funding activity.
- Funding and Investment Analysis: A detailed evaluation of the investments made in digital pathology market based on several relevant parameters, such as [A] number of instances, [B] amount invested, [C] type of funding, [D] area of application, [E] geography and [F] most active players engaged in the AI-based digital pathology domain.
- Demand Analysis: Informed estimates of the annual demand for AI-based digital pathology based on several relevant parameters, such as [A] geography (North America, Europe, Asia, Latin America, MENA and Rest of the World) and [B] end-users (hospitals, research and other end-users).
- How many companies are currently engaged in this market?
- Which are the leading companies in this market?
- What factors are likely to influence the evolution of this market?
- What is the current and future market size?
- What is the CAGR of this market?
- How is the current and future market opportunity likely to be distributed across key market segments?
- The report provides a comprehensive market analysis, offering detailed revenue projections of the overall market and its specific sub-segments. This information is valuable to both established market leaders and emerging entrants.
- Stakeholders can leverage the report to gain a deeper understanding of the competitive dynamics within the market. By analyzing the competitive landscape, businesses can make informed decisions to optimize their market positioning and develop effective go-to-market strategies.
- The report offers stakeholders a comprehensive overview of the market, including key drivers, barriers, opportunities, and challenges. This information empowers stakeholders to stay abreast of market trends and make data-driven decisions to capitalize on growth prospects.
Table of Contents
212 Pages
- 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: Developers Landscape
- 4.2.1. Analysis By Year Of Establishment
- 4.2.2. Analysis By Company Size
- 4.2.3. Analysis By Location Of Headquarters
- 4.2.4. Analysis By Geographical Reach
- 4.3. Ai-based Digital Pathology Providers: Market Landscape
- 4.3.1. Analysis By Type Of Product
- 4.3.2. Analysis By Type Of Service Offered
- 4.3.3. Analysis By Type Of Feature
- 4.3.4. Analysis By Additional Features
- 4.3.5. Analysis By Target Disease Indication
- 4.3.6. Analysis By Type Of Assay
- 4.3.7. Analysis By Area Of Application
- 4.3.8. Analysis By Type Of End-user
- 4.3.9. Analysis By Number Of Available Software
- 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 Type Of Funding And Area Of Application
- 8.3.7. Analysis By Geography
- 8.3.8. Most Active Players: Analysis By Number Of Funding Instances
- 8.3.9. 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, Till 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, Till 2035
- 10.4. Ai-based Digital Pathology Market: Analysis By Type Of Neural Network, Current Year And 2035
- 10.4.1. Ai-based Digital Pathology Market For Artificial Neural Network, Till 2035
- 10.4.2. Ai-based Digital Pathology Market For Convolutional Neural Network, Till 2035
- 10.4.3. Ai-based Digital Pathology Market For Fully Convolutional Network, Till 2035
- 10.4.4. Ai-based Digital Pathology Market For Recurrent Neural Network, Till 2035
- 10.4.5. Ai-based Digital Pathology Market For Other Neural Networks, Till 2035
- 10.5. Ai-based Digital Pathology Market: Analysis By Type Of Assay, Current Year And 2035
- 10.5.1. Ai-based Digital Pathology Market For Er Assay, Till 2035
- 10.5.2. Ai-based Digital Pathology Market For Her2 Assay, Till 2035
- 10.5.3. Ai-based Digital Pathology Market For Ki67 Assay, Till 2035
- 10.5.4. Ai-based Digital Pathology Market For Pd-l1 Assay, Till 2035
- 10.5.5. Ai-based Digital Pathology Market For Pr Assay, Till 2035
- 10.5.6. Ai-based Digital Pathology Market For Other Type Of Assays, Till 2035
- 10.6. Ai-based Digital Pathology Market: Analysis By Type Of End-user, Current Year And 2035
- 10.6.1. Ai-based Digital Pathology Market For Academic Institutions, Till 2035
- 10.6.2. Ai-based Digital Pathology Market For Hospitals / Healthcare Institutions, Till 2035
- 10.6.3. Ai-based Digital Pathology Market For Laboratories / Diagnostic Institutions, Till 2035
- 10.6.4. Ai-based Digital Pathology Market For Research Institutes, Till 2035
- 10.6.5. Ai-based Digital Pathology Market For Other End-users, Till 2035
- 10.7. Ai-based Digital Pathology Market: Analysis By Area Of Application, Current Year And 2035
- 10.7.1. Ai-based Digital Pathology Market For Diagnostics, Till 2035
- 10.7.2. Ai-based Digital Pathology Market For Research, Till 2035
- 10.7.3. Ai-based Digital Pathology Market For Other Areas Of Application, Till 2035
- 10.8. Ai-based Digital Pathology Market: Analysis By Target Disease Indication, Current Year And 2035
- 10.8.1. Ai-based Digital Pathology Market For Breast Cancer, Till 2035
- 10.8.2. Ai-based Digital Pathology Market For Colorectal Cancer, Till 2035
- 10.8.3. Ai-based Digital Pathology Market For Cervical Cancer, Till 2035
- 10.8.4. Ai-based Digital Pathology Market For Gastrointestinal Cancer, Till 2035
- 10.8.5. Ai-based Digital Pathology Market For Lung Cancer, Till 2035
- 10.8.6. Ai-based Digital Pathology Market For Prostate Cancer, Till 2035
- 10.8.7. Ai-based Digital Pathology Market For Other Indications, Till 2035
- 10.9. Ai-based Digital Pathology Market: Analysis By Key Geographies, Current Year And 2035
- 10.9.1. Ai-based Digital Pathology Market In North America, Till 2035
- 10.9.1.1. Ai-based Digital Pathology Market In The Us, Till 2035
- 10.9.1.2. Ai-based Digital Pathology Market In Canada, Till 2035
- 10.9.2. Ai-based Digital Pathology Market In Europe, Till 2035
- 10.9.2.1. Ai-based Digital Pathology Market In Uk, Till 2035
- 10.9.2.2. Ai-based Digital Pathology Market In Germany, Till 2035
- 10.9.2.3. Ai-based Digital Pathology Market In Spain, Till 2035
- 10.9.2.4. Ai-based Digital Pathology Market In Italy, Till 2035
- 10.9.2.5. Ai-based Digital Pathology Market In France, Till 2035
- 10.9.3. Ai-based Digital Pathology Market In Asia, Till 2035
- 10.9.3.1. Ai-based Digital Pathology Market In China, Till 2035
- 10.9.3.2. Ai-based Digital Pathology Market In Japan, Till 2035
- 10.9.3.3. Ai-based Digital Pathology Market In South Korea, Till 2035
- 10.9.4. Ai-based Digital Pathology Market In Latin America, Till 2035
- 10.9.4.1. Ai-based Digital Pathology Market In Brazil, Till 2035
- 10.9.5. Ai-based Digital Pathology Market In Mena, Till 2035
- 10.9.5.1. Ai-based Digital Pathology Market In Saudi Arabia, Till 2035
- 10.9.6. Ai-based Digital Pathology Market In Rest Of The World, Till 2035
- 10.9.6.1. Ai-based Digital Pathology Market In Australia, Till 2035
- 11. Concluding Remarks
- 12. Executive Insights
- 12.1. Chapter Overview
- 12.2. Company A
- 12.2.1. Company Snapshot
- 12.2.2. Interview Transcript: Chief Executive Officer And Chairman
- 12.3. Company B
- 12.3.1. Company Snapshot
- 12.3.2. Interview Transcript: Laboratory Director And Chief Pathologist
- 12.4. Company C
- 12.4.1. Company Snapshot
- 12.4.2. Interview Transcript: Vice President, Research And Technology
- 12.5. Company D
- 12.5.1. Company Snapshot
- 12.5.2. Interview Transcript: Vice President, Sales And Marketing
- 12.6. Company E
- 12.6.1. Company Snapshot
- 12.6.2. Interview Transcript: Vice President, Business Development And Strategic Partnerships
- 13. Appendix 1: Tabulated Data
- 14. Appendix Ii: List Of Companies And Organization
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