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市場調查報告書
商品編碼
1821504

腫瘤學的AI市場:2035年前的產業趨勢和全球預測 - 各癌症類型，各終端用戶類型，各地區

AI in Oncology Market: Industry Trends and Global Forecasts, Till 2035 - Distribution by Type of Cancer, Type of End User, Geographical Regions
出版日期: | 出版商: Roots Analysis | 英文 220 Pages | 商品交期: 最快1-2個工作天內

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腫瘤學人工智慧市場：概覽

預計到2035年，腫瘤學人工智慧市場規模將從目前的24億美元增長至91億美元，預測期內的複合年增長率為14.1%。

市場區隔與機會分析依下列參數進行：

各癌症類型

  • 固態惡性腫瘤
  • 乳癌
  • 肺癌症
  • 前列腺癌症
  • 大腸癌症
  • 腦瘤
  • 其他

各終端用戶類型

  • 醫院
  • 製藥公司
  • 研究機關
  • 其他

各地區

  • 北美
  • 歐洲
  • 亞太地區
  • 其他地區

腫瘤學人工智慧市場：成長與趨勢

人工智慧在製藥業被廣泛用於資料收集、評估和即時解讀。事實上，基於人工智慧的軟體解決方案的整合使臨床醫生能夠及早發現癌症，並開發個人化療法來治療各種腫瘤適應症。此外，腫瘤學領域的人工智慧技術顯著降低了癌症檢測和治療的成本。在人工智慧技術前景的驅動下，專家認為，人工智慧在腫瘤學領域的應用具有巨大的未來創收潛力。

全球癌症風險的上升顯著增加了對先進癌症診斷和治療方法的需求。眾所周知，癌症是全球主要的死亡原因。此外，國際癌症研究機構預測，到2030年，癌症相關死亡人數可能會增加72%。因此，技術創新和不斷上升的癌症發病率等市場驅動因素正在推動腫瘤人工智慧市場的變革性成長。然而，克服監管障礙和資料隱私等挑戰對於在未來幾年充分發揮其潛力仍然至關重要。

腫瘤人工智慧市場關鍵洞察

本報告深入探討了腫瘤人工智慧市場的現狀，並識別了行業內的潛在成長機會。主要發現包括：

  • 目前的市場格局特點是，有超過70家企業致力於開發基於人工智慧的腫瘤領域軟體解決方案。
AI in Oncology Market-IMG1
  • 超過 50% 的參與者正在醫院中使用基於機器學習的解決方案進行診斷。
  • 為了獲得競爭優勢，產業利害關係人正積極升級現有能力，並強化以人工智慧為中心的服務組合。
  • 近期合作活動的增加也證明了人們對該市場的興趣日益濃厚。
  • 許多公共和私人投資者期待豐厚的回報，已投資了相當於 60 億美元的資金。
AI in Oncology Market-IMG2
  • 過去五年，學術界和產業界利益相關者已授予或提交了超過 2,770 項專利，專門用於開發基於人工智慧的腫瘤學軟體解決方案。
AI in Oncology Market-IMG3
  • 預計未來十年市場將以 14.1% 的健康速度成長，並且不同適應症、分子類型和地理的機會可能非常多樣化。

腫瘤AI市場：關鍵細分市場

依癌症類型劃分，全球腫瘤AI市場分為實體惡性腫瘤、乳癌、肺癌、攝護腺癌、大腸癌、腦腫瘤等。預計今年實體惡性腫瘤領域將佔大部分市場佔有率，這一趨勢未來不太可能改變。這一高市場佔有率的驅動因素是全球癌症負擔的增加，尤其是實體腫瘤，這需要創新、可擴展且精準的工具，從而催生了該領域寶貴的AI應用。

依最終用戶類型劃分，市場分為醫院、製藥公司、研究機構和其他。目前，醫院領域佔腫瘤AI市場的最大佔有率。這一趨勢在短期內不太可能改變。

依地區劃分，全球腫瘤AI市場分為北美、歐洲、亞太地區及其他地區。我們的研究表明，歐洲目前佔腫瘤學人工智慧市場的大部分佔有率（33%），而且這一趨勢在未來不太可能改變。這是人口老化、對先進癌症診斷的需求不斷增長以及慢性病管理增加的結果，使得人工智慧解決方案成為一項重要的投資。此外，在預測期（至2035年），亞太市場很可能會以相對較高的複合年增長率（14.7%）成長。這是由於該地區癌症患者數量的增加，推動了對先進診斷和治療解決方案的需求。

初步研究概述

本研究中提出的觀點和見解受到與多位利害關係人討論的影響。本研究報告包含以下產業參與者的詳細訪談記錄：

  • A公司執行長
  • B公司執行長
  • C公司執行長
  • D公司行銷·通訊擔當副社長

腫瘤學的AI市場上參與企業案例

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

腫瘤學的AI市場調查對象

  • 市場規模和機會分析本報告按關鍵細分市場對全球腫瘤人工智慧市場進行了全面分析，包括 [A] 抗體類型、[B] 癌症類型、 [C] 最終用戶類型和 [D] 地區。
  • 市場格局：基於多個相關參數對腫瘤學人工智慧市場中的公司進行深入評估，例如 A] 成立年份、[B] 公司規模、[C] 總部位置、[D] 最終用戶類型、[E] 提供的服務類型、[F] 使用的人工智慧技術類型、[G] 平台類型等。
  • 競爭分析：對腫瘤學人工智慧解決方案提供者進行全面的競爭分析，考察因素包括 A] 公司實力、[B] 產品組合實力等。
  • 公司簡介：腫瘤學人工智慧市場中主要服務提供者的詳細公司簡介，重點關注 A] 公司概況、[B] 財務資訊（如有）、[C] 服務組合以及 [D] 近期發展和未來展望。
  • 專利分析：根據各種相關參數，對腫瘤學人工智慧市場迄今提交/授予的專利進行深入分析，例如 A] 專利出版年份、[B] 專利類型、[C] 專利管轄區、[D] CPC 符號、[F] 申請人類型、[G] 管轄區、[H] 主要參與者、[i] 估值分析和 [J] 專利。
  • 合作關係與分析：根據多個參數，對腫瘤學人工智慧市場利益相關者達成的交易進行深入分析，例如：A) 合作年份、B) 合作類型、C) 癌症類型、D) 最活躍的參與者（合作夥伴關係數量）、E) 合作活動的區域分佈。
  • 資金與投資分析：基於相關參數對人工智慧藥物研發公司籌集的資金進行深入分析，例如：A) 融資年份，B) 投資金額（按年份），C) 融資類型，D) 投資金額（按公司規模），E) 投資者類型，F) 投資金額（按投資者類型），G) 最活躍的參與者，H) 最活躍的投資者，I) 區域分析。
  • 藍海分析：基於各種框架對參與者進行評估，例如：A) 價值創新，B) 戰略畫布，C) 四大行動框架，D) ERRC 網格，E) 六條路徑框架，F) 先驅者-遷移者-定居者 (PMS) 地圖，G) 三層非客戶，F) 藍海買方戰略序列，F) 效用效用。

目錄

第1章 序文

第2章 摘要整理

第3章 簡介

  • 章概要
  • 人工智能概要
  • 人工智能的種類
  • 醫療保健的AI
  • 醫療保健中人工智慧的主要課題
  • 未來展望

第4章 市場概要

  • 章概要
  • 腫瘤學的AI:軟體供應商的市場形勢
  • 腫瘤學的AI:軟體解決方案的市場形勢

第5章 企業簡介

  • 章概要
  • Roche Diagnostics
  • IBM Watson Health
  • CancerCenter.AI
  • GE Healthcare
  • Concert AI
  • Path AI
  • Berg
  • Median Technologies
  • iCAD
  • JLK Inspection

第6章 企業的競爭力分析

  • 章概要
  • 前提主要的參數
  • 調查手法
    • 企業的競爭力:北美的中小企業
    • 企業的競爭力:歐洲的中小企業
    • 企業的競爭力:亞太地區的中小企業
    • 企業的競爭力:北美中規模企業
    • 企業的競爭力:歐洲中規模企業
    • 企業的競爭力:亞太地區中規模企業
    • 企業的競爭力:北美和歐洲的大企業

第7章 專利分析

  • 章概要
  • 與範圍調查手法
  • 腫瘤學的AI:專利分析
  • 腫瘤學的AI:專利基準分析

第8章 夥伴關係和合作

  • 章概要
  • 夥伴關係模式
  • 腫瘤學的AI:最近的夥伴關係和合作

第9章 資金籌措投資分析

  • 章概要
  • 資金籌措模式的種類
  • 腫瘤學的AI:資金籌措和投資分析的清單
  • 投資摘要
  • 結論

第10章 藍海策略：新創企業進入競爭市場的策略指南

  • 章概要
  • 青·海洋策略概要
  • 結論

第11章 市場規模的評估機會分析

  • 章概要
  • 與主要的前提調查手法
  • 腫瘤學的人工智能的全球市場，2022年～2035年
  • 腫瘤學市場上人工智能:各癌症類型分析，2022年～2035年
  • 腫瘤學市場上人工智能:各終端用戶類型分析，2022年～2035年
  • 腫瘤學市場上人工智能:各主要地區分析，2022年～2035年

第12章 結論

第13章 執行洞察

第14章 附錄1:表格形式資料

第15章 附錄2:企業·團體一覽

Product Code: RA100373

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.
AI in Oncology Market - IMG1
  • 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.
AI in Oncology Market - IMG2
  • 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.
AI in Oncology Market - IMG3
  • 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

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  • 15% Free Content Customization
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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

List of Tables

  • Table 4.1 AI in Oncology: List of Software providers
  • Table 4.2 AI in Oncology Software providers: Information on Type of Service(s) Offered
  • Table 4.3 AI in Oncology Software providers: Information on the Type of AI Technology Used
  • Table 4.4 AI in Oncology Software providers: Information on Type of Platform
  • Table 5.1 Roche Diagnostics: Key Highlights
  • Table 5.2 IBM Watson Health: Key Highlights
  • Table 5.3 CancerCenter.ai: Key Highlights
  • Table 5.4 CancerCenter.ai: Recent Developments and Future Outlook
  • Table 5.5 GE Healthcare: Key Highlights
  • Table 5.6 GE Healthcare: Recent Developments and Future Outlook
  • Table 5.7 Concert AI: Key Highlights
  • Table 5.8 Concert AI: Recent Developments and Future Outlook
  • Table 5.9 Path AI: Key Highlights
  • Table 5.10 PathAI: Recent Developments and Future Outlook
  • Table 5.11 BERG: Key Highlights
  • Table 5.12 BERG: Recent Developments and Future Outlook
  • Table 5.13 Median Technologies: Key Highlights
  • Table 5.14 Median Technologies: Recent Developments and Future Outlook
  • Table 5.15 iCAD: Key Highlights
  • Table 5.16 iCAD: Recent Developments and Future Outlook
  • Table 5.17 JLK Inspection: Key Highlights
  • Table 7.1 Patent Analysis: CPC Symbols
  • Table 7.2 Patent Analysis: Most Popular CPC Symbols
  • Table 7.3 Patent Analysis: List of Top CPC Symbols
  • Table 7.4 Patent Analysis: Categorization based on Weighted Valuation Scores
  • Table 7.5 Patent Analysis: List of Relatively High Value Patents
  • Table 8.1 Partnerships and Collaborations: List of Partnerships and Collaborations,
  • Table 9.1 AI in Oncology: List of Funding and Investments,
  • Table 9.2 Funding and Investment Analysis: Summary of Investments (Number of Instances)
  • Table 9.3 Funding and Investment Analysis: Summary of Investments (Total Amount Invested)
  • Table 9.4 Funding and Investment Analysis: Summary of Venture Capital Funding
  • Table 14.1 AI in Oncology Software providers: Distribution by Year of Establishment
  • Table 14.2 AI in Oncology Software providers: Distribution by Company Size
  • Table 14.3 AI in Oncology Software providers: Distribution by Location of Headquarters (Region-wise)
  • Table 14.4 AI in Oncology Software providers: Distribution by Location of Headquarters (Country-wise)
  • Table 14.5 AI in Oncology Software providers: Distribution by Type of End-User
  • Table 14.6 AI in Oncology Software providers: Distribution by Year of Establishment, Company Size and Location of Headquarters
  • Table 14.7 AI in Oncology- based Software Solutions: Distribution by Type of Service(s) Offered
  • Table 14.8 AI in Oncology- based Software Solutions: Distribution by Type of AI Technology Used
  • Table 14.9 AI in Oncology- based Software Solutions: Distribution by Type of Platform
  • Table 14.10 AI in Oncology- based Software Solutions: Distribution by Type of Service(s) Offered and Type of End User
  • Table 14.11 AI in Oncology-based Software Solutions: Distribution by Type of Platform and Type of AI Technology Used
  • Table 14.12 Roche Diagnostics: Annual Revenues (CHF Billion)
  • Table 14.13 IBM Watson Health: Annual Revenues (USD Billion)
  • Table 14.14 GE Healthcare: Annual Revenues (USD Billion)
  • Table 14.15 Median Technologies: Annual Revenues (EUR Million)
  • Table 14.16 iCAD: Annual Revenues (USD Million)
  • Table 14.17 Patent Analysis: Distribution by Type of Patents
  • Table 14.18 Patent Analysis: Cumulative Distribution by Publication Year
  • Table 14.19 Patent Analysis: Year-Wise Distribution of Filed Patent Applications and Granted Patents
  • Table 14.20 Patent Analysis: Distribution by Jurisdiction
  • Table 14.21 Patent Analysis: Cumulative Distribution by Type of Industry
  • Table 14.22 Patent Analysis: Distribution by Patent Age
  • Table 14.23 Patent Analysis: Distribution by Legal Status
  • Table 14.24 Leading Industry Players: Distribution by Number of Patents
  • Table 14.25 Leading Non-Industry Players: Distribution by Number of Patents
  • Table 14.26 Patent Analysis: Distribution by Key Inventors
  • Table 14.27 AI in Oncology: Patent Valuation Analysis
  • Table 14.28 Partnerships and Collaborations: Distribution by Year of Partnership
  • Table 14.29 Partnerships and Collaborations: Distribution by Type of Partnership
  • Table 14.30 Partnerships and Collaborations: Distribution by Year and Type of Partnership
  • Table 14.31 Partnerships and Collaborations: Distribution by Company Size and Type of Partnership
  • Table 14.32 Most Active Partners: Distribution by Type of Partnership
  • Table 14.33 Partnerships and Collaborations: Distribution by Type of Cancer
  • Table 14.34 Partnerships and Collaborations: Distribution by Type of Partner
  • Table 14.35 Partnerships and Collaborations: Distribution by Year and Type of Partner
  • Table 14.36 Partnerships and Collaborations: Intercontinental and Intracontinental Agreement
  • Table 14.37 Partnerships and Collaborations: Local and International Agreement
  • Table 14.38 Partnerships and Collaborations: Distribution by Country
  • Table 14.39 Partnerships and Collaborations: Distribution by Region
  • Table 14.40 Most Active Players: Distribution by number of Partnerships
  • Table 14.41 Funding and Investment Analysis: Cumulative Year-wise Distribution by Number of Instances,
  • Table 14.42 Funding and Investment Analysis: Cumulative Year-wise Distribution by Amount Invested, (USD Billion)
  • Table 14.43 Funding and Investment Analysis: Distribution of Instances by Type of Funding
  • Table 14.44 Funding and Investment Analysis: Distribution of Amount Invested and Type of Funding (USD Million)
  • Table 14.45 Most Active Players: Distribution by Number of Instances
  • Table 14.46 Most Active Players: Distribution by Amount Invested (USD Million)
  • Table 14.47 Funding and Investment Analysis: Distribution of Funding Instances by Area of Application
  • Table 14.48 Funding and Investment Analysis: Distribution of Instances by Focus Area
  • Table 14.49 Funding and Investment Analysis: Distribution by Geography
  • Table 14.50 Funding and Investment Analysis: Distribution of Instances by Type of Cancer
  • Table 14.51 Most Active Investors: Distribution by Number of Instances
  • Table 14.52 Funding and Investment Analysis: Distribution by Type of Lead Investors
  • Table 14.53 Funding and Investment Analysis: Summary of Amount Invested (USD Million)
  • Table 14.54 Global Artificial Intelligence in Oncology Market Till 2035, Conservative, Base and Optimistic Scenarios, Till 2035 (USD Billion)
  • Table 14.55 Artificial Intelligence in Oncology Market: Distribution by Type of Cancer, Till 2035
  • Table 14.56 Artificial Intelligence in Oncology Market for Breast Cancer, Conservative, Base and Optimistic Scenarios, Till 2035 (USD Billion)
  • Table 14.57 Artificial Intelligence in Oncology Market for Lung Cancer, Conservative, Base and Optimistic Scenarios, Till 2035 (USD Billion)
  • Table 14.58 Artificial Intelligence in Oncology Market for Prostate Cancer, Conservative, Base and Optimistic Scenarios, Till 2035 (USD Billion)
  • Table 14.59 Artificial Intelligence in Oncology Market for Colorectal Cancer, Conservative, Base and Optimistic Scenarios, Till 2035 (USD Billion)
  • Table 14.60 Artificial Intelligence in Oncology Market for Brain Tumor, Conservative, Base and Optimistic Scenarios, Till 2035 (USD Billion)
  • Table 14.61 Artificial Intelligence in Oncology Market for Solid Malignancies, Conservative, Base and Optimistic Scenarios, Till 2035 (USD Billion)
  • Table 14.62 Artificial Intelligence in Oncology Market for Other Cancers, Conservative, Base and Optimistic Scenarios, Till 2035 (USD Billion)
  • Table 14.63 Artificial Intelligence in Oncology Market: Distribution by Type of End-Users, Till 2035
  • Table 14.64 Artificial Intelligence in Oncology Market for Hospitals, Conservative, Base and Optimistic Scenarios, Till 2035 (USD Billion)
  • Table 14.65 Artificial Intelligence in Oncology Market for Pharmaceutical Companies, Conservative, Base and Optimistic Scenarios, Till 2035 (USD Billion)
  • Table 14.66 Artificial Intelligence in Oncology Market for Research Institutes, Conservative, Base and Optimistic Scenarios, Till 2035 (USD Billion)
  • Table 14.67 Artificial Intelligence in Oncology Market for Other End-Users, Conservative, Base and Optimistic Scenarios, Till 2035 (USD Billion)
  • Table 14.68 Artificial Intelligence in Oncology Market: Distribution by Key Geographical Regions, Till 2035
  • Table 14.69 Artificial Intelligence in Oncology Market for North America, Conservative, Base and Optimistic Scenarios, Till 2035 (USD Billion)
  • Table 14.70 Artificial Intelligence in Oncology Market for Europe, Conservative, Base and Optimistic Scenarios, Till 2035 (USD Billion)
  • Table 14.71 Artificial Intelligence in Oncology Market for Asia Pacific, Conservative, Base and Optimistic Scenarios, Till 2035 (USD Billion)
  • Table 14.72 Artificial Intelligence in Oncology Market for Rest of the World, Conservative, Base and Optimistic Scenarios, Till 2035 (USD Billion)

List of Figures

  • Figure 2.1 Executive Summary: Market Landscape
  • Figure 2.2 Executive Summary: Patent Analysis
  • Figure 2.3 Executive Summary: Partnerships and Collaboration Analysis
  • Figure 2.4 Executive Summary: Funding and Investment Analysis
  • Figure 2.5 Executive Summary: Market Forecast and Opportunity Analysis
  • Figure 3.1 Historical Evolution of AI
  • Figure 3.2 Relationship between AI, ML and DL
  • Figure 3.3 Type of Artificial Intelligence
  • Figure 3.4 Artificial Intelligence Software Solutions: Distribution by Oncology-related Field
  • Figure 3.5 Artificial Intelligence Software Solutions: Distribution by Various Types of Cancers Detected
  • Figure 4.1 AI in Oncology Software providers: Distribution by Year of Establishment
  • Figure 4.2 AI in Oncology Software providers: Distribution by Company Size
  • Figure 4.3 AI in Oncology Software providers: Distribution by Location of Headquarters (Region-wise)
  • Figure 4.4 AI in Oncology Software providers: Distribution by Location of Headquarters (Country-wise)
  • Figure 4.5 AI in Oncology Software providers: Distribution by Type of End-User
  • Figure 4.6 AI in Oncology Software providers: Distribution by Year of Establishment, Company Size and Location of Headquarters
  • Figure 4.7 AI in Oncology- based Software Solutions: Distribution by Type of Service(s) Offered
  • Figure 4.8 AI in Oncology- based Software Solutions: Distribution by Type of AI Technology Used
  • Figure 4.9 AI in Oncology- based Software Solutions: Distribution by Type of Platform
  • Figure 4.10 AI in Oncology- based Software Solutions: Distribution by Type of Service(s) Offered and Type of end-user
  • Figure 4.11 AI in Oncology Software Solutions: Distribution by Type of Platform and Type of AI Technology Used
  • Figure 4.12 AI in Oncology-based Software Solutions: Distribution by Type of Service(s) Offered, Location of Headquarters and Type of AI Technology Used
  • Figure 5.1 Roche Diagnostics: Annual Revenues, Since 2017 (CHF Billion)
  • Figure 5.2 Roche Diagnostics: Service Portfolio
  • Figure 5.3 IBM Watson Health: Annual Revenues, Since 2017 (USD Billion)
  • Figure 5.4 IBM Watson Health: Service Portfolio
  • Figure 5.5 CancerCenter.ai: Service Portfolio
  • Figure 5.6 GE Healthcare: Annual Revenues, Since 2017 (USD Billion)
  • Figure 5.7 PathAI: Service Portfolio
  • Figure 5.8 BERG: Service Portfolio
  • Figure 5.9 Median Technologies: Annual Revenues, Since 2017 (EUR Million)
  • Figure 5.10 iCAD: Annual Revenues, Since 2017 (USD Million)
  • Figure 5.11 iCAD: Distribution of Revenues by Business Units (USD Million)
  • Figure 5.12 JLK Inspection: Service Portfolio
  • Figure 6.1 Company Competitiveness Analysis: Small Companies in North America
  • Figure 6.2 Company Competitiveness Analysis: Small Companies in Europe
  • Figure 6.3 Company Competitiveness Analysis: Small Companies in Asia Pacific
  • Figure 6.4 Company Competitiveness Analysis: Mid-sized companies in North America
  • Figure 6.5 Company Competitiveness Analysis: Mid-sized companies in Europe
  • Figure 6.6 Company Competitiveness Analysis: Mid-sized companies in Asia Pacific
  • Figure 6.7 Company Competitiveness Analysis: Large Companies in North America and Europe
  • Figure 7.1 Patent Analysis: Distribution by Type of Patents
  • Figure 7.2 Patent Analysis: Cumulative Distribution by Publication Year
  • Figure 7.3 Patent Analysis: Year-wise Distribution of Filed Patent Applications and Granted Patents
  • Figure 7.4 Patent Analysis: Distribution by Jurisdiction
  • Figure 7.5 Patent Analysis: Cumulative Distribution by Type of Industry
  • Figure 7.6 Patent Analysis: Distribution by Patent Age
  • Figure 7.7 Patent Analysis: Distribution by Legal Status
  • Figure 7.8 Patent Analysis: Distribution by CPC Symbols
  • Figure 7.9 Leading Industry Players: Distribution by Number of Patents
  • Figure 7.10 Leading Non-Industry Players: Distribution by Number of Patents
  • Figure 7.11 Patent Analysis: Distribution by Key Inventors
  • Figure 7.12 Patent Analysis (Top 10 CPC Symbols): Benchmarking by Leading Industry Players
  • Figure 7.13 AI in Oncology: Patent Valuation Analysis
  • Figure 8.1 Partnerships and Collaborations: Distribution by Year of Partnership, 2017- 2022
  • Figure 8.2 Partnerships and Collaborations: Distribution by Type of Partnership
  • Figure 8.3 Partnerships and Collaborations: Distribution by Year and Type of Partnership
  • Figure 8.4 Partnerships and Collaborations: Distribution by Company Size and Type of Partnership
  • Figure 8.5 Most Active Partners: Distribution by Number of Partnerships
  • Figure 8.6 Most Active Players: Distribution by Type of Partnership
  • Figure 8.7 Partnerships and Collaborations: Distribution by Type of Cancer
  • Figure 8.8 Partnerships and Collaborations: Distribution by Type of Partner
  • Figure 8.9 Partnerships and Collaborations: Distribution by Year and Type of Partner
  • Figure 8.10 Partnerships and Collaborations: Intercontinental and Intracontinental Agreement
  • Figure 8.11 Partnerships and Collaborations: Local and International Agreement
  • Figure 8.12 Partnerships and Collaborations: Distribution by Country
  • Figure 8.13 Partnerships and Collaborations: Distribution by Region
  • Figure 9.1 Funding and Investment Analysis: Cumulative Year-wise Distribution by Number of Instances,
  • Figure 9.2 Funding and Investment Analysis: Cumulative Year-wise Distribution by Amount Invested, (USD Billion)
  • Figure 9.3 Funding and Investment Analysis: Distribution of Instances by Type of Funding
  • Figure 9.4 Funding and Investment Analysis: Distribution of Amount Invested by Year and Type of Funding, (USD Million)
  • Figure 9.5 Funding and Investment Analysis: Distribution by Amount Invested and Type of Funding (USD Billion)
  • Figure 9.6 Funding and Investment Analysis: Distribution of Funding Instances by Area of Application
  • Figure 9.7 Funding and Investment Analysis: Distribution of Instances by Focus Area
  • Figure 9.8 Funding and Investment Analysis: Distribution of Instances by Type of Cancer
  • Figure 9.9 Funding and Investment Analysis: Distribution by Geography
  • Figure 9.10 Most Active Players: Distribution by Number of Instances
  • Figure 9.11 Most Active Players: Distribution by Amount Invested (USD Million)
  • Figure 9.12 Funding and Investment Analysis: Distribution by Type of Investors
  • Figure 9.13 Most Active Investors: Distribution by Number of Instances
  • Figure 9.14 Funding and Investment Analysis: Summary of Amount Invested, (USD Billion)
  • Figure 9.15 Funding and Investment Analysis: Concluding Remarks
  • Figure 10.1 Red Ocean Strategy vs Blue Ocean Strategy
  • Figure 10.2 Blue Ocean Strategy: Strategy Canvas
  • Figure 10.3 Blue Ocean Strategy: Eliminate-Raise-Reduce-Create (ERRC) Grid
  • Figure 10.4 Blue Ocean Strategy: Pioneer-Migrator-Settler (PMS) Map
  • Figure 10.5 Blue Ocean Strategy: Three Tiers of Noncustomers
  • Figure 10.6 Blue Ocean Strategy: Sequence of Blue Ocean Strategy
  • Figure 10.7 Blue Ocean Strategy: Buyer Utility Map
  • Figure 10.8 Blue Ocean Strategy: The Price Corridor of the Mass
  • Figure 11.1 Global Artificial Intelligence in Oncology Market, Till 2035 (USD Billion)
  • Figure 11.2 Artificial Intelligence in Oncology Market: Distribution by Type of Cancer, Till 2035 (USD Billion)
  • Figure 11.3 Artificial Intelligence in Oncology Market for Breast Cancer, Till 2035 (USD Billion)
  • Figure 11.4 Artificial Intelligence in Oncology Market for Lung Cancer, Till 2035 (USD Billion)
  • Figure 11.5 Artificial Intelligence in Oncology Market for Prostate Cancer, Till 2035 (USD Billion)
  • Figure 11.6 Artificial Intelligence in Oncology Market for Colorectal Cancer, Till 2035 (USD Billion)
  • Figure 11.7 Artificial Intelligence in Oncology Market for Brain Tumor, Till 2035 (USD Billion)
  • Figure 11.8 Artificial Intelligence in Oncology Market for Solid Malignancies, Till 2035 (USD Billion)
  • Figure 11.9 Artificial Intelligence in Oncology Market for Other Cancers, Till 2035 (USD Billion)
  • Figure 11.10 Artificial Intelligence in Oncology Market: Distribution by Type of End-User, Till 2035 (USD Billion)
  • Figure 11.11 Artificial Intelligence in Oncology Market for Hospitals, Till 2035 (USD Billion)
  • Figure 11.12 Artificial Intelligence in Oncology Market for Pharmaceutical Companies, Till 2035 (USD Billion)
  • Figure 11.13 Artificial Intelligence in Oncology Market for Research Institutes, Till 2035 (USD Billion)
  • Figure 11.14 Artificial Intelligence in Oncology Market for Other End-Users, Till 2035 (USD Billion)
  • Figure 11.15 Artificial Intelligence in Oncology Market: Distribution by Geography, Till 2035 (USD Billion)
  • Figure 11.16 Artificial Intelligence in Oncology Market for North America, Till 2035 (USD Billion)
  • Figure 11.17 Artificial Intelligence in Oncology Market for Europe, Till 2035 (USD Billion)
  • Figure 11.18 Artificial Intelligence in Oncology Market for Asia Pacific, Till 2035 (USD Billion)
  • Figure 11.19 Artificial Intelligence in Oncology Market for Rest of the World, Till 2035 (USD Billion)
  • Figure 12.1 Concluding Remarks: AI in Oncology Market Landscape
  • Figure 12.2 Concluding Remarks: Patent Analysis
  • Figure 12.3 Concluding Remarks: Partnerships and Collaborations Analysis
  • Figure 12.4 Concluding Remarks: Funding and Investment Analysis
  • Figure 12.5 Concluding Remarks: Market Forecast and Opportunity Analysis