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
- Artificial Neural Network
- Convolutional Neural Network
- Fully Convolutional Network,
- Recurrent Neural Network
- Other Neural Network
Type of Assay
- ER Assay
- HER2 Assay
- KI67, PR Assay
- Other Type of Assay
Type of End-User
- Academic Institutions
- Hospitals / Healthcare Institutions
- Laboratories / Diagnostic Institutions
- Research Institutes
- Other End-Users
Area of Application
- Diagnostics
- Research
- Other Areas of Application
Target Disease Indication
- Breast Cancer
- Colorectal Cancer
- Cervical Cancer
- Gastrointestinal Cancer
- Lung Cancer
- Prostate Cancer
- Other Indications
Key Geographical Regions
- North America
- Europe
- Asia-Pacific
- Middle East and North Africa
- Latin America
AI-based Digital Pathology Market: Growth and Trends
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.
AI-based Digital Pathology Market: Key Segments
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
Primary Research Overview
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
AI-based Digital Pathology Market: Research Coverage
- 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).
Key Questions Answered in this Report
- 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?
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