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Global AI-Based Digital Pathology Solutions Market

AI-Based Digital Pathology Solutions Market Size, Share & Trends Analysis Report By Type of Neural Network, Type Of Assay, Type Of Target Disease Indication, By Application, By End-User, By Region, And Segment Forecasts, 2024-2031

Report ID : 1492 | Published : 2024-02-20 | Pages: 175 | Format: PDF/EXCEL

The Global AI-Based Digital Pathology Solutions Market is predicted to grow at an 8.59% CAGR during the forecast period for 2024-2031.

Key Industry Insights & Findings from the Report:

  • The increasing focus on cost management and efficiency improvement in hospitals, the increasing demand for technologically advanced solutions, and the increasing frequency of misdiagnoses drive market growth.
  • Government-funded research programs that encourage the development of innovative digital tools for pathology are expected to fuel industry expansion.
  • North America dominated the market and accounted for a revenue share of global revenue in 2023.
  • Interoperability worries and high initial and ongoing operating expenses will likely slow the market's growth.

ai based digital pathology

Artificial Intelligence (AI) has been proven to be a faster and more effective approach to identifying and assessing pathological characteristics in samples than previous techniques. The drug discovery process is made more efficient and effective by implementing AI, and the diagnosis process can be accelerated and strengthened. In addition, AI aids pathologists in making accurate diagnoses by using data to verify their findings. It can alert them when their conclusions are contrary to what is expected based on the algorithms. As a result, AI-based pathology solutions may become increasingly popular.

By combining Artificial Intelligence (AI) with digital pathology, pathologists can now perform image analytics on a more significant number of slides in a shorter period by combining AI and digital pathology as a validation tool. Pathologists can improve outcomes by focusing on specific regions and improving efficiency accordingly. Digital pathology is enhancing patient engagement with the use of artificial intelligence, with devices and apps providing access to electronic health records, radiology images, etc.

It is becoming increasingly common to use artificial intelligence in healthcare, particularly in pathological diagnosis, to improve patient care. For example, a clinical decision support system is an AI-based tool designed to streamline workflow processes and enhance hospital patient care. The Roche Group announced in October 2021 that it had agreed with PathAI, an artificial intelligence-based pathology technology leader. The agreement outlines the development and distribution of an embedded image analysis workflow to be used by pathologists under this development and distribution contract. An AI-based medical device will be developed as a result of this partnership, which will include a scanner, an assay, a management system, and an algorithm.

Research collaborations and the growth of digital documentation are driving an increase in adoption across all scientific disciplines. The increasing penetration of healthcare IT solutions has boosted the demand for digital pathology solutions. In recent years, many organizations have adopted resolutions to decrease costs, reduce resource bottlenecks, automate processes, and effectively share content. Advancements in technologies, such as microarrays and predictive models, including hybrid models and API algorithms, will also fuel the demand for digital image analysis.

Several factors contribute to the restraints on the market, including the requirement for high capital, which hinders the company's global reach expansion, and a lack of tools necessary to conduct a computational analysis. Also, many factors could limit the market's growth, including a shortage of experienced professionals and a lack of awareness of modern spatial-based technology.

Competitive Landscape

Some major key players in the AI-Based Digital Pathology market 

  • PathAI,
  • Paige.AI,
  • Akoya Biosciences,
  • Aiforia,
  • aetherAI,
  • CellCarta,
  • Deep Bio Inc.,
  • DoMore Diagnostics,
  • PROSCIA,
  • Pramana, Inc.,
  • Visiopharm A/S,
  • Roche Tissue Diagnostics,
  • Indica Labs,
  • Ibex Medical Analytics,
  • LDPath,
  • OracleBio Limited,
  • Verily,
  • Mindpeak GmbH,
  • Proscia Inc.,
  • SamanTree Medical SA,
  • Tempus AI,
  • Techcyte, Inc.,
  • Tribun Health

Market Segmentation:

The AI-Based Digital Pathology market is segmented by type of neural network, assay type, type of target disease indication, application, and end-user. All of these segments are subdivided into respective segments. The type of neural network segment has artificial, convolutional, fully convolutional, recurrent neural, and others, respectively. The type of assay category comprises ER assay, HER2 assay, Ki67 assay, PD-L1 assay, PR assay, and other assays. The target disease indication segment includes breast cancer, colorectal cancer, cervical cancer, gastrointestinal cancer, lung cancer, prostate cancer, and other indications. Also, the application segment includes diagnosis, research, and other applications. The last segment is the end-user segment which contains academic institutions, hospitals/healthcare institutions, laboratories/diagnostic institutions, research institutes and other end-users.

In 2021, North America dominated the market with a significant share. A major factor driving North America's share of the AI-based digital pathology market is improved healthcare infrastructure, increased per capita income, and the availability of state-of-the-art research laboratories and institutes. The FDA categorizes DP as a Class II device for primary diagnosis. Digital pathology is poised to become an increasingly vital tool to enhance disease diagnosis and improve the quality of pathology services. The market is expected to benefit from this development across the nation.

Recent Developments:

  • In January 2024, Roche announced that it had entered into a final merger agreement to acquire Carmot Therapeutics, Inc. ("Carmot"), a privately held US company in Berkeley, California. A variety of preclinical programs and clinically stage subcutaneous and oral incretins with best-in-class potential to treat obesity in patients with and without diabetes are part of Carmot's research and development portfolio.
  • In November 2023, Leica Biosystems further strengthened its partnership with hospitals and laboratories worldwide later to make use of the innovative digital pathology workflows. Building on their prior partnership, Leica Biosystems has selected Paige to supply their Aperio GT 450 digital pathology slide scanners with view and manage digital pathology images software and a range of embedded AI technologies.

AI-Based Digital Pathology Market Report Scope

Report Attribute

Specifications

Growth Rate CAGR

CAGR of 8.59% from 2024 to 2031

Quantitative Units

Representation of revenue in US$ Million and CAGR from 2024 to 2031

Historic Year

2019 to 2023

Forecast Year

2024-2031

Report Coverage

The forecast of revenue, the position of the company, the competitive market structure, growth prospects, and trends

Segments Covered

Type of Neural Network, Type Of Assay, Type Of Target Disease Indication, Application, End-User

Regional Scope

North America; Europe; Asia Pacific; Latin America; Middle East & Africa

Country Scope

U.S.; Canada; U.K.; Germany; China; India; Japan; Brazil; Mexico ;The UK; France; Italy; Spain; China; Japan; India; South Korea; South East Asia; South Korea; South East Asia

Competitive Landscape

PathAI, Paige.AI, Akoya Biosciences, Aiforia, aetherAI, CellCarta, Deep Bio Inc., DoMore Diagnostics, PROSCIA, Pramana, Inc., Visiopharm A/S, Roche Tissue Diagnostics, Indica Labs, Ibex Medical Analytics, LDPath, OracleBio Limited, Verily, Mindpeak GmbH, Proscia Inc., SamanTree Medical SA, Tempus AI, Techcyte, Inc., Tribun Health.

Customization Scope

Free customization report with the procurement of the report, Modifications to the regional and segment scope. Particular Geographic competitive landscape.

Pricing And Available Payment Methods

Explore pricing alternatives that are customized to your particular study requirements.

 

 

Chapter 1. Methodology and Scope

1.1. Research Methodology

1.2. Research Scope & Assumptions

Chapter 2. Executive Summary

Chapter 3. Global Artificial Intelligence (AI)-based Digital Pathology Market Snapshot

Chapter 4. Global Artificial Intelligence (AI)-based Digital Pathology Market Variables, Trends & Scope

4.1. Market Segmentation & Scope

4.2. Drivers

4.3. Challenges

4.4. Trends

4.5. Investment and Funding Analysis

4.6. Industry Analysis – Porter’s Five Forces Analysis

4.7. Competitive Landscape & Market Share Analysis

4.8. Impact of Covid-19 Analysis

Chapter 5. Market Segmentation 1: By Neural Network, Estimates & Trend Analysis

5.1. By Neural Network, & Market Share, 2019 & 2031

5.2. Market Size (Value US$ Mn) & Forecasts and Trend Analyses, 2019 to 2031 for the following By Neural Network:

5.2.1. Artificial Neural Network

5.2.2. Convolutional Neural Network

5.2.3. Fully Convolutional Network

5.2.4. Recurrent Neural Network

5.2.5. Other Neural Networks

Chapter 6. Market Segmentation 2: By Assay Estimates & Trend Analysis

6.1. By Assay & Market Share, 20219 & 2031

6.2. Market Size (Value US$ Mn) & Forecasts and Trend Analyses, 2019 to 2031 for the following By Assay:

6.2.1. ER Assay

6.2.2. HER2 Assay

6.2.3. Ki67 Assay

6.2.4. PD-L1 Assay

6.2.5. PR Assay

6.2.6. Other Assays

Chapter 7. Market Segmentation 3: By Applications Estimates & Trend Analysis

7.1. By Applications & Market Share, 2019 & 2031

7.2. Market Size (Value US$ Mn) & Forecasts and Trend Analyses, 2019 to 2031 for the following By Applications:

7.2.1. Diagnostics

7.2.2. Research

7.2.3. Other Areas of Application

Chapter 8. Market Segmentation 4: By End-Users Estimates & Trend Analysis

8.1. By End-Users & Market Share, 2019 & 2031

8.2. Market Size (Value US$ Mn) & Forecasts and Trend Analyses, 2019 to 2031 for the following By End-Users:

8.2.1. Academic Institutions

8.2.2. Hospitals/Healthcare Institutions

8.2.3. Laboratories/Diagnostic Institutions

8.2.4. Research Institutes

8.2.5. Other End-Users

Chapter 9. Market Segmentation 5: By Target Disease Indication Estimates & Trend Analysis

9.1. By Target Disease Indication & Market Share, 2019 & 2031

9.2. Market Size (Value US$ Mn) & Forecasts and Trend Analyses, 2019 to 2031 for the following By Target Disease Indication:

9.2.1. Breast Cancer

9.2.2. Colorectal Cancer

9.2.3. Cervical Cancer

9.2.4. Gastrointestinal Cancer

9.2.5. Lung Cancer

9.2.6. Prostate Cancer

9.2.7. Other Indications

Chapter 10. Artificial Intelligence (AI)-based Digital Pathology Market Segmentation 6: Regional Estimates & Trend Analysis

10.1. North America

10.1.1. North America Artificial Intelligence (AI)-based Digital Pathology Market revenue (US$ Million) estimates and forecasts By Neural Network, 2024-2031

10.1.2. North America Artificial Intelligence (AI)-based Digital Pathology Market revenue (US$ Million) estimates and forecasts By Assay, 2024-2031

10.1.3. North America Artificial Intelligence (AI)-based Digital Pathology Market revenue (US$ Million) estimates and forecasts By Applications, 2024-2031

10.1.4. North America Artificial Intelligence (AI)-based Digital Pathology Market revenue (US$ Million) estimates and forecasts By End-Users, 2024-2031

10.1.5. North America Artificial Intelligence (AI)-based Digital Pathology Market revenue (US$ Million) estimates and forecasts by Target Disease Indication, 2024-2031

10.1.6. North America Artificial Intelligence (AI)-based Digital Pathology Market revenue (US$ Million) estimates and forecasts by country, 2024-2031

10.2. Europe

10.2.1. Europe Artificial Intelligence (AI)-based Digital Pathology Market revenue (US$ Million) By Neural Network, 2024-2031

10.2.2. Europe Artificial Intelligence (AI)-based Digital Pathology Market revenue (US$ Million) By Assay, 2024-2031

10.2.3. Europe Artificial Intelligence (AI)-based Digital Pathology Market revenue (US$ Million) By Applications, 2024-2031

10.2.4. Europe Artificial Intelligence (AI)-based Digital Pathology Market revenue (US$ Million) estimates and forecasts By End-Users, 2024-2031

10.2.5. Europe Artificial Intelligence (AI)-based Digital Pathology Market revenue (US$ Million) estimates and forecasts by Target Disease Indication, 2024-2030

10.2.6. Europe Artificial Intelligence (AI)-based Digital Pathology Market revenue (US$ Million) by country, 2024-2031

10.3. Asia Pacific

10.3.1. Asia Pacific Artificial Intelligence (AI)-based Digital Pathology Market revenue (US$ Million) By Neural Network, 2024-2031

10.3.2. Asia Pacific Artificial Intelligence (AI)-based Digital Pathology Market revenue (US$ Million) By Assay, 2024-2031

10.3.3. Asia Pacific Artificial Intelligence (AI)-based Digital Pathology Market revenue (US$ Million) By Applications, 2024-2031

10.3.4. Asia Pacific Artificial Intelligence (AI)-based Digital Pathology Market revenue (US$ Million) estimates and forecasts By End-Users, 2024-2031

10.3.5. Asia Pacific Artificial Intelligence (AI)-based Digital Pathology Market revenue (US$ Million) estimates and forecasts by Target Disease Indication, 2024-2031

10.3.6. Asia Pacific Artificial Intelligence (AI)-based Digital Pathology Market revenue (US$ Million) by country, 2024-2031

10.4. Latin America

10.4.1. Latin America Artificial Intelligence (AI)-based Digital Pathology Market revenue (US$ Million) By Neural Network, (US$ Million) 2024-2031

10.4.2. Latin America Artificial Intelligence (AI)-based Digital Pathology Market revenue (US$ Million) By Assay, (US$ Million) 2024-2031

10.4.3. Latin America Artificial Intelligence (AI)-based Digital Pathology Market revenue (US$ Million) By Applications, (US$ Million) 2024-2031

10.4.4. Latin America Artificial Intelligence (AI)-based Digital Pathology Market revenue (US$ Million) estimates and forecasts By End-Users, 2024-2031

10.4.5. Latin America Artificial Intelligence (AI)-based Digital Pathology Market revenue (US$ Million) estimates and forecasts by Target Disease Indication, 2024-2031

 

10.4.6. Latin America Artificial Intelligence (AI)-based Digital Pathology Market revenue (US$ Million) by country, 2024-2031

10.5. Middle East & Africa

10.5.1. Middle East & Africa Artificial Intelligence (AI)-based Digital Pathology Market revenue (US$ Million) By Neural Network, (US$ Million) 2024-2031

10.5.2. Middle East & Africa Artificial Intelligence (AI)-based Digital Pathology Market revenue (US$ Million) By Assay, (US$ Million) 2024-2031

10.5.3. Middle East & Africa Artificial Intelligence (AI)-based Digital Pathology Market revenue (US$ Million) By Applications, (US$ Million) 2024-2031

10.5.4. Middle East & Africa Artificial Intelligence (AI)-based Digital Pathology Market revenue (US$ Million) estimates and forecasts By End-Users, 2024-2030

10.5.5. Middle East & Africa Artificial Intelligence (AI)-based Digital Pathology Market revenue (US$ Million) estimates and forecasts by Target Disease Indication, 2024-2030

10.5.6. Middle East & Africa Artificial Intelligence (AI)-based Digital Pathology Market revenue (US$ Million) by country, 2024-2031

Chapter 11. Competitive Landscape

11.1. Major Mergers and Acquisitions/Strategic Alliances

11.2. Company Profiles

11.2.1. PathAI

11.2.2. Paige.AI

11.2.3. Akoya Biosciences

11.2.4. Aiforia

11.2.5. aetherAI

11.2.6. CellCarta

11.2.7. Deep Bio Inc.

11.2.8. DoMore Diagnostics

11.2.9. PROSCIA

11.2.10. Pramana, Inc.

11.2.11. Visiopharm A/S

11.2.12. Roche Tissue Diagnostics

11.2.13. Indica Labs

11.2.14. Ibex Medical Analytics

11.2.15. LDPath

11.2.16. OracleBio Limited

11.2.17. Verily

11.2.18. Mindpeak GmbH

11.2.19. Proscia Inc.

11.2.20. SamanTree Medical SA

11.2.21. Tempus AI

11.2.22. Techcyte, Inc.

11.2.23. Tribun Health

11.2.24. Other Prominent Players

Segmentation of AI-Based Digital Pathology Solutions Market-

Global AI-Based Digital Pathology Solutions Market, by Type of Neural Network, (Value US$ Mn)

  • Artificial Neural Network
  • Convolutional Neural Network
  • Fully Convolutional Network
  • Recurrent Neural Network
  • Other Neural Networks

 ai based digital pathology

 

Global AI-Based Digital Pathology Solutions Market, by Type Of Assay, (Value US$ Mn)

  • ER Assay
  • HER2 Assay
  • Ki67 Assay
  • PD-L1 Assay
  • PR Assay
  • Other Type of Assays

 

Global AI-Based Digital Pathology Solutions Market, by Type Of Target Disease Indication, (Value US$ Mn)

  • Breast Cancer
  • Colorectal Cancer
  • Cervical Cancer
  • Gastrointestinal Cancer
  • Lung Cancer
  • Prostate Cancer
  • Other Indications

 

Global AI-Based Digital Pathology Solutions Market, by Application, (Value US$ Mn)

  • Diagnostics
  • Research
  • Other Applications

 

Global AI-Based Digital Pathology Solutions Market, by End-User, (Value US$ Mn)

  • Academic Institutions
  • Hospitals/Healthcare Institutions
  • Laboratories/Diagnostic Institutions
  • Research Institutes
  • Other End Users

 

Global AI-Based Digital Pathology Solutions Market, by Region, (Value US$ Mn)

  • North America
  • Europe
  • Asia Pacific
  • Latin America
  • Middle East & Africa

 

North America AI-Based Digital Pathology Solutions Market, by Country, (Value US$ Mn)

  • U.S.
  • Canada

 

Europe AI-Based Digital Pathology Solutions Market, by Country, (Value US$ Mn)

  • Germany
  • France
  • Italy
  • Spain
  • Russia
  • Rest of Europe

 

Asia Pacific AI-Based Digital Pathology Solutions Market, by Country, (Value US$ Mn)

  • India
  • China
  • Japan
  • South Korea
  • Australia & New Zealand

 

Latin America AI-Based Digital Pathology Solutions Market, by Country, (Value US$ Mn)

  • Brazil
  • Mexico
  • Rest of Latin America

 

Middle East & Africa AI-Based Digital Pathology Solutions Market, by Country, (Value US$ Mn)

  • GCC Countries
  • South Africa
  • Rest of Middle East & Africa

 

InsightAce Analytic follows a standard and comprehensive market research methodology focused on offering the most accurate and precise market insights. The methods followed for all our market research studies include three significant steps – primary research, secondary research, and data modeling and analysis - to derive the current market size and forecast it over the forecast period. In this study, these three steps were used iteratively to generate valid data points (minimum deviation), which were cross-validated through multiple approaches mentioned below in the data modeling section.

Through secondary research methods, information on the market under study, its peer, and the parent market was collected. This information was then entered into data models. The resulted data points and insights were then validated by primary participants.

Based on additional insights from these primary participants, more directional efforts were put into doing secondary research and optimize data models. This process was repeated till all data models used in the study produced similar results (with minimum deviation). This way, this iterative process was able to generate the most accurate market numbers and qualitative insights.

Secondary research

The secondary research sources that are typically mentioned to include, but are not limited to:

  • Company websites, financial reports, annual reports, investor presentations, broker reports, and SEC filings.
  • External and internal proprietary databases, regulatory databases, and relevant patent analysis
  • Statistical databases, National government documents, and market reports
  • Press releases, news articles, and webcasts specific to the companies operating in the market

The paid sources for secondary research like Factiva, OneSource, Hoovers, and Statista

Primary Research:

Primary research involves telephonic interviews, e-mail interactions, as well as face-to-face interviews for each market, category, segment, and subsegment across geographies

The contributors who typically take part in such a course include, but are not limited to: 

  • Industry participants: CEOs, CBO, CMO, VPs, marketing/ type managers, corporate strategy managers, and national sales managers, technical personnel, purchasing managers, resellers, and distributors.
  • Outside experts: Valuation experts, Investment bankers, research analysts specializing in specific markets
  • Key opinion leaders (KOLs) specializing in unique areas corresponding to various industry verticals
  • End-users: Vary mainly depending upon the market

Data Modeling and Analysis:

In the iterative process (mentioned above), data models received inputs from primary as well as secondary sources. But analysts working on these models were the key. They used their extensive knowledge and experience about industry and topic to make changes and fine-tuning these models as per the product/service under study.

The standard data models used while studying this market were the top-down and bottom-up approaches and the company shares analysis model. However, other methods were also used along with these – which were specific to the industry and product/service under study.

To know more about the research methodology used for this study, kindly contact us/click here.

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Frequently Asked Questions

What is the AI-Based Digital Pathology Solutions Market Growth?

PathAI, Paige.AI, Akoya Biosciences, Aiforia, aetherAI, CellCarta, Deep Bio Inc., DoMore Diagnostics, PROSCIA, Pramana, Inc., Visiopharm A/S, and Othe

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