종양학 AI 시장 : 업계 동향과 세계 예측(-2035년) - 암 유형별, 최종사용자 유형별, 지역별

Ai in Oncology Market: Overview

The AI in oncology market is estimated to grow from USD 2.4 billion in the current year to USD 9.1 billion by 2035, representing a higher CAGR of 14.1% during the forecast period.

The market sizing and opportunity analysis has been segmented across the following parameters:

Type of Cancer

• Solid Malignancies
• Breast cancer
• Lung cancer
• Prostate cancer
• Colorectal cancer
• Brain tumor
• Others

Type of End User

• Hospitals
• Pharmaceutical Companies
• Research Institutes
• Others

Geographical Regions

• North America
• Europe
• Asia-Pacific
• Rest of the World

Ai in Oncology Market: Growth and Trends

AI has been immensely utilized for data collection, evaluation, and real-time interpretation in the pharmaceutical industry. In fact, the integration of AI-based software solutions enables clinicians to detect cancer at an early stage and develop personalized therapies to treat a wide range of oncological indications. Additionally, AI-powered technology in oncology significantly reduces the cost of cancer testing and treatment. Driven by the significance offered by AI technology, experts believe that the use of AI in oncology market has enormous potential to generate revenue in the future.

Due to the rise in cancer risk across the globe, there has been a significant rise in the demand for advanced cancer diagnostic and treatment methods to treat patients. It is a widely known fact that cancer is the leading cause of deaths worldwide. Further, International Agency for Cancer Research suggests that the number of cancer-associated deaths is likely to increase by 72%, by 2030. Therefore, drivers such as technological innovation and rising cancer incidence position the AI in oncology market for transformative growth. However, overcoming challenges such as regulatory hurdles and data privacy would remain critical in realizing its full potential in the coming years.

Ai in Oncology Market: Key Insights

The report delves into the current state of the AI in oncology market and identifies potential growth opportunities within industry. Some key findings from the report include:

• The current market landscape features the presence of over 70 players engaged in the development of AI-based software solutions for the oncology sector.

• Over 50% of the players use their machine learning powered solutions for diagnostic purposes in hospitals; geographically, the software providers are well distributed.
• In pursuit of gaining a competitive edge, industry stakeholders are actively upgrading their existing capabilities and enhancing their AI-focused service portfolios.
• The growing interest in this market is prevalent from the recent rise in partnership activity; ~50% of the deals were inked to enable utilization and integration of proprietary AI-based technology solutions
• Foreseeing lucrative returns, many public and private investors have made investments worth ~USD 6 billion; 70% of the funding initiatives were led by venture capitalists.

• Over 2,770 patents have been granted / filed by academic and industry stakeholders in the last five years, exclusively for the development of AI-based software solutions for oncology.

• The market is expected to witness a healthy growth of 14.1% in the coming decade; the opportunity is likely to be well distributed across various target indications, types of molecules and different regions.

Ai in Oncology Market: Key Segments

Solid Malignancies Holds the Largest Share

Based on the type of cancer, the global AI in oncology market is segmented across type of cancer, such as solid malignancies, breast cancer, lung cancer, prostate cancer, colorectal cancer, brain tumor and others. The solid malignancies segment is likely to capture the majority of the market share in the current year, and this trend is unlikely to change in the future. The high market share can be attributed to the increased global cancer burden, particularly in solid tumors, which has necessitated innovative, scalable, and precise tools, thus creating valuable AI applications valuable in this sector.

Currently, Hospitals Segment Occupies the Largest Share of the AI in Oncology Market

Based on the type of end-user, the market is segmented into hospitals, pharmaceutical companies, research institutes and others. In the current year, the hospital segment holds the maximum share of AI in oncology market. This trend is unlikely to change in the near future.

Asia-Pacific to Propel in the AI in Oncology Sector in the Coming Years

Based on the geographical regions, the global AI in oncology market is segmented across North America, Europe and Asia-Pacific and rest of the world. Our research suggests that Europe captures the majority (33%) of AI in oncology market share in the current year and this trend is unlikely to change in the future. This is a result of the ageing population, rise in the need for advanced cancer diagnostics and chronic disease management areas, wherein AI solutions provide substantial investments. Further, the market in Asia-Pacific is likely to grow at a relatively high CAGR (14.7%), during the forecast period till 2035. This is attributed to the increase in the number of cancer cases in the region, driving demand for advanced diagnostic and treatment solutions.

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, Company A
• Chief Executive Officer, Company B
• Chief Executive Officer, Company C
• Vice President, Marketing and Communications, Company D

Example Players in the AI in Oncology Market

• Berg (A part of BPGbio)
• CancerCenter.AI
• Concert AI
• GE Healthcare
• IBM Watson Health
• iCAD
• JLK Inspection
• Median Technologies
• Path AI
• Roche Diagnostics

Ai in Oncology Market: Research Coverage

• Market Sizing and Opportunity Analysis: The report features a thorough analysis of the global AI in oncology market, in terms of the key market segments, including [A] type of antibody manufactured, [B] type of cancer, [C] type of end user and [D] geographical regions.
• Market Landscape: An in-depth assessment of the companies involved in AI in oncology market, based on several relevant parameters, such as [A] year of establishment, [B] company size, [C] location of headquarters, [D] type of end-user, [E] type of services offered, [F] type of AI technology used, and [G] type of platform.
• Company Competitiveness Analysis: A comprehensive competitive analysis of AI in oncology solution providers, examining factors, such as [A] company strength and [B] portfolio strength.
• Company Profiles: Detailed profiles of key service providers engaged in the AI in oncology market, focused on [A] overview of the company, [B] financial information (if available), [C] service portfolio, and [D] recent developments and an informed future outlook.
• Patent Analysis: An in-depth analysis of patents filed / granted till date in the AI in oncology market domain, based on various relevant parameters, such as [A] patent publication year, [B] type of patent, [C] patent jurisdiction, [D] CPC symbols, [F] type of applicant, [G] jurisdiction, [H] leading players, [I] benchmarking analysis and [J] patent valuation.
• Partnerships and Analysis: An insightful analysis of the deals inked by stakeholders in the AI in oncology market, based on several parameters, such as [A] year of partnership, [B] type of partnership,[C] type of cancer, [D] most active players (in terms of the number of partnerships signed) and [E] geographical distribution of partnership activity.
• Funding and Investment Analysis: An in-depth analysis of the fundings raised by AI in drug discovery companies, based on relevant parameters, such as [A] year of funding, [B] amount invested by year, [C] type of funding, [D] amount invested by company size, [E] type of investor, [F] amount invested by type of investor, [G] most active players, [H] most active investors and [I] geographical analysis.
• Blue Ocean Analysis: A strategic guide for start-ups to enter into a highly competitive market, assessing players based on various frameworks, such as [A] value innovation, [B] strategy canvas, [C] four action framework [D] eliminate-raise-reduce-create (ERRC) grid [E] six path framework [F] pioneer-migrator-settler (PMS) map [G] three tiers of noncustomers [F] sequence of blue ocean strategy and [F] buyer utility map.

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?

Reasons to Buy this Report

• 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.

Additional Benefits

• Complimentary PPT Insights Packs
• Complimentary Excel Data Packs for all Analytical Modules in the Report
• 15% Free Content Customization
• Detailed Report Walkthrough Session with Research Team
• Free Updated report if the report is 6-12 months old or older

TABLE OF CONTENTS

1. PREFACE

• 1.1. Overview
• 1.2. Scope of the Report
• 1.3. Market Segmentation
• 1.4. Research Methodology
• 1.5. Key Questions Answered
• 1.6. Chapter Outlines

2. EXECUTIVE SUMMARY

• 2.1 Chapter Overview

3. INTRODUCTION

• 3.1. Chapter Overview
• 3.2. Overview of Artificial Intelligence
• 3.3. Types Of Artificial Intelligence
• 3.4. AI in Healthcare
• 3.5. Key Challenges Associated with Use of AI in Healthcare Sector
• 3.6. Future Perspectives

4. MARKET OVERVIEW

• 4.1. Chapter Overview
• 4.2. AI in Oncology: Market Landscape of Software providers
  • 4.2.1. Analysis by Year of Establishment
  • 4.2.2. Analysis by Company Size
  • 4.2.3. Analysis by Location of Headquarters (Region-wise)
  • 4.2.4. Analysis by Location of Headquarters (Country-wise)
  • 4.2.5. Analysis by Type of End-User
  • 4.2.6. Analysis by Year of Establishment, Company size and Location of Headquarters
• 4.3. AI in Oncology: Market Landscape of Software Solutions
  • 4.3.1. Analysis by Type of Service(s) Offered
  • 4.3.2. Analysis by Type of AI Technology Used
  • 4.3.3. Analysis by Type of Platform
  • 4.3.4. Analysis by Type of Service(s) Offered and Type of End-User
  • 4.3.5. Analysis by Type of Platform and Type of AI Technology Used
  • 4.3.6. Analysis by Type of Service(s) Offered, Location of Headquarters and Type of AI Technology Used

5. COMPANY PROFILES

• 5.1. Chapter Overview
• 5.2. Roche Diagnostics
  • 5.2.1. Company Overview
  • 5.2.2. Financial Information
  • 5.2.3. Service Portfolio
  • 5.2.4. Recent Developments and Future Outlook
• 5.3. IBM Watson Health
  • 5.3.1. Company Overview
  • 5.3.2. Financial Information
  • 5.3.3. Service Portfolio
  • 5.3.4. Recent Developments and Future Outlook
• 5.4. CancerCenter.AI
  • 5.4.1. Company Overview
  • 5.4.2. Service Portfolio
  • 5.4.3. Recent Development and Future Outlooks
• 5.5. GE Healthcare
  • 5.5.1. Company Overview
  • 5.5.2. Financial Information
  • 5.5.3. Service Portfolio
  • 5.5.4. Recent Development and Future Outlook
• 5.6. Concert AI
  • 5.6.1. Company Overview
  • 5.6.2. Service Portfolio
  • 5.6.3. Recent Developments and Future Outlook
• 5.7. Path AI
  • 5.7.1. Company Overview
  • 5.7.2. Service portfolio
  • 5.7.3. Recent Development and Future Outlook
• 5.8. Berg
  • 5.8.1. Company Overview
  • 5.8.2. Service Portfolio
  • 5.8.3. Recent Development and Future Outlook
• 5.9. Median Technologies
  • 5.9.1. Company Overview
  • 5.9.2. Financial Information
  • 5.9.3. Service Portfolio
  • 5.9.4. Recent Development and Future Outlook
• 5.10. iCAD
  • 5.10.1. Company Overview
  • 5.10.2. Financial Information
  • 5.10.3. Service Portfolio
  • 5.10.4. Recent Developments and Future Outlook
• 5.11. JLK Inspection
  • 5.11.1. Company Overview
  • 5.11.2. Service Portfolio
  • 5.11.3. Recent Development and Future Outlook

6. COMPANY COMPETITIVENESS ANALYSIS

• 6.1. Chapter Overview
• 6.2. Assumptions and Key Parameters
• 6.3. Methodology
  • 6.3.1. Company Competitiveness: Small Companies in North America
  • 6.3.2. Company Competitiveness: Small Companies in Europe
  • 6.3.3. Company Competitiveness: Small Companies in Asia Pacific
  • 6.3.4. Company Competitiveness: Mid-sized companies in North America
  • 6.3.5. Company Competitiveness: Mid-sized companies in Europe
  • 6.3.6. Company Competitiveness: Mid-sized companies in Asia Pacific
  • 6.3.7. Company Competitiveness: Large companies in North America and Europe

7. PATENT ANALYSIS

• 7.1. Chapter Overview
• 7.2. Scope and Methodology
• 7.3. AI in Oncology: Patent Analysis
  • 7.3.1. Analysis by Type of Patent
  • 7.3.2. Analysis by Patent Publication Year
  • 7.3.3. Analysis by Year-wise Trend of Filed Patent Applications and Granted Patents
  • 7.3.4. Analysis by Jurisdiction
  • 7.3.5. Analysis by Type of Industry
  • 7.3.6. Analysis by Patent Age
  • 7.3.7. Analysis by Legal Status
  • 7.3.8. Analysis by CPC Symbols
  • 7.3.9. Most Active Players: Analysis by Number of Patents
  • 7.3.10. Analysis by Key Inventors
• 7.4. AI in Oncology: Patent Benchmarking Analysis
  • 7.4.1. Analysis by Patent Characteristics
  • 7.4.2. AI in Oncology: Patent Valuation Analysis

8. PARTNERSHIPS AND COLLABORATIONS

• 8.1. Chapter Overview
• 8.2. Partnership Models
• 8.3 AI in Oncology: Recent Partnerships and Collaborations
  • 8.3.1. Analysis by Year of Partnership
  • 8.3.2. Analysis by Type of Partnership
  • 8.3.3. Analysis by Year and Type of Partnership
  • 8.3.4. Analysis by Company Size and Type of Partnership
  • 8.3.5. Most Active Partners: Analysis by Number of Partnerships
  • 8.3.6. Most Active Players: Analysis by Type of Partnership
  • 8.3.7. Analysis by Type of Cancer
  • 8.3.8. Analysis by Type of Partner
  • 8.3.9. Analysis by Year and Type of Partner
  • 8.3.10. Intercontinental and Intracontinental Agreements
  • 8.3.11. Local and International Agreements
  • 8.3.12. Country-Wise Distribution
  • 8.3.13. Analysis by Region

9. FUNDING AND INVESTMENT ANALYSIS

• 9.1. Chapter Overview
• 9.2. Types of Funding Models
• 9.3. AI in Oncology: List of Funding and Investment Analysis
  • 9.3.1. Analysis by Year and Number of Funding Instances
  • 9.3.2. Analysis by Year and Amount Invested
  • 9.3.3 Analysis by Type of Funding and Number of Instances
  • 9.3.4. Analysis by Year, Type of Funding and Amount Invested
  • 9.3.5. Analysis by Type of Funding and Amount Invested
  • 9.3.6. Analysis by Area of Application
  • 9.3.7. Analysis by Focus Area
  • 9.3.8. Analysis by Type of Cancer Indication
  • 9.3.9. Analysis by Geography
  • 9.3.10. Most Active Players by Number of Instances
  • 9.3.11. Most Active Players by Amount Invested
  • 9.3.12. Analysis by Type of Investors
  • 9.3.13. Analysis by Lead Investors
• 9.4. Summary of Investments
• 9.5. Concluding Remarks

10. BLUE OCEAN STRATEGY: A STRATEGIC GUIDE FOR START-UPS TO ENTER INTO HIGHLY COMPETITIVE MARKET

• 10.1. Chapter Overview
• 10.2. Overview of Blue Ocean Strategy
  • 10.2.1 Red Ocean
  • 10.2.2 Blue Ocean
  • 10.2.3 Difference between Red Ocean Strategy and Blue Ocean Strategy
  • 10.2.4. AI in Oncology: Blue Ocean Strategy and Shift Tools
    • 10.2.4.1. Value Innovation
    • 10.2.4.2. Strategy Canvas
    • 10.2.4.3. Four Action Framework
    • 10.2.4.4. Eliminate-Raise-Reduce-Create (ERRC) Grid
    • 10.2.4.5. Six Path Framework
    • 10.2.4.6. Pioneer-Migrator-Settler (PMS) Map
    • 10.2.4.7. Three Tiers of Noncustomers
    • 10.2.4.8. Sequence of Blue Ocean Strategy
    • 10.2.4.9. Buyer Utility Map
    • 10.2.4.10. The Price Corridor of the Mass
    • 10.2.4.11. Four Hurdles to Strategy Execution
    • 10.2.4.12. Tipping Point Leadership
    • 10.2.4.13. Fair Process
• 10.3. Conclusion

11. MARKET SIZING AND OPPORTUNITY ANALYSIS

• 11.1. Chapter Overview
• 11.2 Key Assumptions and Methodology
• 11.3. Global Artificial Intelligence in Oncology Market, 2022-2035
• 11.4. Artificial Intelligence in Oncology Market: Analysis by Type of Cancer, 2022- 2035
  • 11.4.1. Artificial Intelligence in Oncology Market for Breast Cancer, 2022-2035
  • 11.4.2. Artificial Intelligence in Oncology Market for Lung Cancer, 2022-2035
  • 11.4.3. Artificial Intelligence in Oncology Market for Prostate Cancer, 2022-2035
  • 11.4.4. Artificial Intelligence in Oncology Market for Colorectal Cancer, 2022-2035
  • 11.4.5. Artificial Intelligence in Oncology Market for Brain Tumor, 2022-2035
  • 11.4.6. Artificial Intelligence in Oncology Market for Solid Malignancies, 2022-2035
  • 11.4.7. Artificial Intelligence in Oncology Market for Other Cancers, 2022-2035
• 11.5. Artificial Intelligence in Oncology Market: Analysis by Type of End-User, 2022-2035
  • 11.5.1. Artificial Intelligence in Oncology Market for Hospitals, 2022-2035
  • 11.5.2. Artificial Intelligence in Oncology Market for Pharmaceutical Companies, 2022-2035
  • 11.5.3. Artificial Intelligence in Oncology Market for Research Institutes, 2022-2035
  • 11.5.4. Artificial Intelligence in Oncology Market for Other End-Users, 2022-2035
• 11.6. Artificial Intelligence in Oncology Market: Analysis by Key Geographical Regions, 2022-2035
  • 11.6.1. Artificial Intelligence in Oncology Market for North America, 2022-2035
  • 11.6.2. Artificial Intelligence in Oncology Market for Europe, 2022-2035
  • 11.6.3. Artificial Intelligence in Oncology Market for Asia Pacific, 2022-2035
  • 11.6.4. Artificial Intelligence in Oncology Market for Rest of the World, 2022-2035

12. CONCLUSION

• 12.1. Chapter Overview

13. EXECUTIVE INSIGHTS

• 13.1. Chapter Overview
• 13.2. Company A
  • 13.2.1. Company Snapshot
  • 13.2.2. Interview Transcript: Vice President, Marketing and Communications
• 13.3. Company B
  • 13.3.1. Company Snapshot
  • 13.3.2. Interview Transcript: Chief Executive Officer
• 13.4. Company C
  • 13.4.1. Company Snapshot
  • 13.4.2. Interview Transcript: Chief Executive Officer
• 13.5. Company D
  • 13.5.1. Company Snapshot
  • 13.5.2. Interview Transcript: Chief Executive Officer
• 13.6. Company E
  • 13.6.1 Company Snapshot
  • 13.6.2 Interview Transcript: Chief Executive Officer

14. APPENDIX 1: TABULATED DATA

15. APPENDIX 2: LIST OF COMPANIES AND ORGANIZATIONS