생명과학용 AI 시장(-2040년) : 배포 방식별, 제공 유형별, 기술 유형별, 응용 분야별, 주요 지역별 - 업계 동향, 예측
Artificial Intelligence in Life Sciences Market, till 2040: Distribution by Deployment Mode, Type of Offering, Type of Technology, Application Areas and Key Geographical Regions: Industry Trends and Global Forecasts
상품코드:1958434
리서치사:Roots Analysis
발행일:On Demand Report
페이지 정보:영문 179 Pages
라이선스 & 가격 (부가세 별도)
한글목차
생명과학용 AI 시장 전망
세계의 생명과학용 AI 시장 규모는 현재 56억 9,000만 달러에서 2040년까지 730억 5,000만 달러에 달할 것으로 추정되며, 2040년까지의 예측 기간에 CAGR로 20%의 성장이 전망되고 있습니다.
AI는 생물학, 제약, 생명공학, 의학 등 생명과학 분야에 혁명을 일으키고 있습니다. 이들 분야는 생물 시스템 연구와 치료법 혁신을 통해 인류의 건강 증진에 초점을 맞추었습니다. AI는 고급 컴퓨팅 프레임워크 역할을 하며, 머신러닝 알고리즘을 활용하여 방대한 데이터세트를 처리하고, 복잡한 패턴을 식별하고, 전례 없는 효율성으로 예측적 인사이트을 창출합니다.
생명과학용 AI 시장은 유전체 데이터, 환자 데이터, 임상시험 데이터의 급격한 증가로 인해 견고한 성장세를 보이고 있습니다. 이러한 방대한 데이터는 신속하고 효율적인 분석이 필요하며, AI는 기존 방식보다 높은 정확도로 대규모 데이터세트를 처리할 수 있다는 장점이 있습니다. 또한 AI는 신약개발 프로세스의 타임라인을 단축하고, 치솟는 R&D 비용을 대폭 절감하며, 임상시험의 효율성을 향상시킬 수 있습니다. 또한 머신러닝과 클라우드 컴퓨팅의 기술 발전, 그리고 제약사들의 대규모 투자로 인해 시장 성장세가 더욱 가속화되고 있습니다.
생명과학용 AI 시장 성장을 이끄는 주요 시장 성장 촉진요인들
여러 촉진요인이 생명과학용 AI 시장의 급속한 확장을 주도하고 있습니다. 유전체 분석, 환자 기록, 임상시험에서 발생하는 데이터 양의 급격한 증가는 신속하고 정밀한 분석을 필요로 합니다. AI는 기존의 수동적 접근 방식을 속도와 정확성에서 능가하며, 분자 간 상호작용을 효과적으로 예측하여 신약개발을 가속화합니다. 또한 우수한 환자 선택과 결과 예측을 통해 임상시험을 최적화하고 실패율을 최소화합니다.
정밀의료에 대한 수요 증가는 AI가 개인의 유전자 정보와 건강 프로파일을 기반으로 치료법을 맞춤화하여 치료 효과를 높이는 등 정밀의료에 대한 수요 증가로 인해 그 채택을 더욱 가속화하고 있습니다. 머신러닝 알고리즘과 클라우드 컴퓨팅의 발전으로 연구 환경 전반에 걸쳐 원활한 통합이 가능해졌습니다. 또한 대형 제약사들은 구글, IBM과 같은 기술 리더과 전략적 파트너십을 구축하고 있으며, 막대한 투자를 통해 이를 지원하고 있습니다. 이러한 요인들이 예측 기간 중 전체 생명과학용 AI 시장의 성장을 촉진하고 있습니다.
생명과학용 AI 시장 : 업계내 기업간 경쟁 구도
생명과학 분야의 AI 경쟁 환경은 주요 기술 기업, 제약업계 리더, 전문 스타트업이 혼합되어 신약 개발, 임상시험, 맞춤형 의료 분야의 혁신을 주도하고 있습니다. IBM, IQVIA, Oracle과 같은 기업은 데이터 통합, AI 모델 훈련, 규제 준수를 종합적으로 다루는 풀스택 플랫폼을 제공합니다. Roche, Pfizer, Insilico Medicine 등의 제약사들은 방대한 유전체 데이터와 임상 데이터를 분석하여 비용 절감과 시장 출시 시간 단축을 위해 AI를 활용한 신약 개발 프로세스를 가속화하고 있습니다. Atomwise, Sophia Genetics, NuMedii와 같은 새로운 도전자들은 분자 시뮬레이션, 유전체 분석, 예측 모델링과 같은 틈새 툴에 집중하고 있습니다.
생명과학을 위한 AI의 진화: 업계의 새로운 동향
생명과학을 위한 AI의 주요 동향으로는 AI를 통한 신약개발 가속화, 맞춤형 의료, 영상 진단 및 웨어러블 기술을 활용한 첨단 진단 기술 등이 있습니다. 이 외에도 AI 사이언스 팩토리를 통한 실험실 워크플로우 자동화, 규제 신청에 사용되는 특정 분야의 거대 언어 모델, 임상시험 최적화 강화, 약물감시 및 예방 의학 전략을 위한 원활한 AI 통합 등 다양한 발전이 이루어지고 있습니다. 이러한 발전은 방대한 생물학적, 임상적 데이터세트를 활용하여 환자 중심의 의료 서비스를 제공함으로써 업무 효율성, 비용 절감, 정확도 향상을 우선순위로 삼고 있습니다.
세계의 생명과학용 인공지능(AI) 시장에 대해 조사했으며, 시장 규모 추정과 기회 분석, 경쟁 구도, 기업 개요 등의 정보를 전해드립니다.
목차
섹션 1 리포트 개요
제1장 서문
제2장 조사 방법
제3장 시장 역학
제4장 거시경제 지표
섹션 2 정성적 인사이트
제5장 개요
제6장 서론
제7장 규제 시나리오
섹션 3 시장 개요
제8장 주요 기업의 종합적 데이터베이스
제9장 경쟁 구도
제10장 기업 경쟁력 분석
제11장 생명과학용 AI 시장의 스타트업 에코시스템
섹션 4 기업 개요
제12장 기업 개요
섹션 5 시장 동향
제13장 메가트렌드 분석
제14장 특허 분석
제15장 최근 발전
섹션 6 시장 기회 분석
제16장 세계의 생명과학용 AI 시장
제17장 시장 기회 : 배포 방식별
제18장 시장 기회 : 제공 유형별
제19장 시장 기회 : 기술 유형별
제20장 시장 기회 : 응용 분야별
제21장 북미의 생명과학용 AI 시장의 시장 기회
제22장 유럽의 생명과학용 AI 시장의 시장 기회
제23장 아시아의 생명과학용 AI 시장의 시장 기회
제24장 중동·북아프리카(MENA) 생명과학용 AI 시장의 시장 기회
제25장 라틴아메리카의 생명과학용 AI 시장의 시장 기회
제26장 기타 지역의 생명과학용 AI 시장의 시장 기회
제27장 시장 집중 분석 : 주요 기업별
제28장 인접 시장 분석
섹션 7 전략적 툴
제29장 주요 성공 전략
제30장 Porter's Five Forces 분석
제31장 SWOT 분석
제32장 Roots의 전략적 제안
섹션 8 기타 독점적 인사이트
제33장 1차 조사로부터의 인사이트
제34장 리포트 결론
섹션 9 부록
KSA
영문 목차
영문목차
Artificial Intelligence In Life Sciences Market Outlook
As per Roots Analysis, the global Artificial intelligence in life sciences market size is estimated to grow from USD 5.69 billion in current year to USD 73.05 billion by 2040, at a CAGR of 20% during the forecast period, till 2040.
Artificial intelligence (AI) is revolutionizing the life sciences sector, encompassing disciplines such as biology, pharmaceuticals, biotechnology, and medicine. These fields focus on advancing human health through the study of biological systems and therapeutic innovations. AI functions as an advanced computational framework, leveraging machine learning algorithms to process vast datasets, identify intricate patterns, and generate predictive insights with unprecedented efficiency.
The artificial intelligence in life sciences market is experiencing robust growth, fueled by the exponential increase in genomic, patient, and clinical trial data. Such huge data necessitates rapid, efficient analysis, where AI outperforms traditional methods by processing vast datasets with precision. Further, AI accelerates drug discovery timelines and significantly reduces elevated R&D expenditures and enhances clinical trial efficiency. Additionally, technological advancements in machine learning, cloud computing, and substantial investments by pharmaceutical giants also fuel the momentum of the market.
Strategic Insights for Senior Leaders
Transformative Role of Artificial Intelligence in Drug Discovery and Personalized Medicine
Artificial intelligence (AI) is revolutionizing drug discovery by speeding up the process, lowering costs, and enhancing success rates through methods, such as virtual screening, predictive modeling for efficacy and toxicity, and de novo drug design. Machine learning and deep learning techniques evaluate large datasets to pinpoint promising drug candidates, anticipate their behavior within the body, and even create completely new molecules. AI is also applied in drug repurposing and personalizing therapies by discovering new applications for existing medications or customizing treatments for individual patients based on their specific data.
In personalized medicine, AI integrates individual genomic profiles, lifestyle factors, and historical health data to develop tailored treatment strategies, forecast therapeutic responses, and dynamically adjust dosages or regimens. This minimized adverse effects, improving efficacy, and promoting patient adherence through automated reminders. Collectively, these capabilities reduce healthcare costs, expand access, and facilitates home-based models.
Key Drivers Propelling Growth of Artificial Intelligence (AI) in Life Sciences Market
Several key drivers propel the rapid expansion of AI in life sciences market. Exponential growth in data volumes from genomics, patient records, and clinical trials demands swift, precise analysis. AI surpasses traditional manual approaches in speed and accuracy and accelerates drug discovery by predicting molecular interactions effectively. It also optimizes clinical trials through superior patient selection and outcome forecasting, minimizing failure rates.
Rising demand for precision medicine further accelerates adoption, as AI tailors therapies to individual genetic and health profiles for enhanced efficacy. Advancements in machine learning algorithms and cloud computing facilitate seamless integration across research environments. Further, pharmaceutical giants are forging strategic partnerships with tech leaders like Google and IBM, backed by substantial investments. Collectively, these factors are propelling the growth of the overall AI in life sciences market during the forecast period.
Artificial Intelligence in Life Sciences Market: Competitive Landscape of Companies in this Industry
The competitive landscape of AI in life sciences features a mix of big tech giants, pharma leaders, and specialized startups driving innovation in drug discovery, clinical trials, and personalized medicine. Companies like IBM, IQVIA, and Oracle offer full-stack platforms that handle data integration, AI model training, and regulatory compliance. Pharma players such as Roche, Pfizer, and Insilico Medicine use AI to speed up drug development by analyzing vast genomic and clinical datasets, cutting costs and time-to-market. Emerging challengers like Atomwise, Sophia Genetics, and NuMedii focus on niche tools for molecular simulations, genomic analysis, and predictive modeling.
Artificial Intelligence in Life Sciences Evolution: Emerging Trends in the Industry
Key trends in the AI life sciences sector include accelerated AI-driven drug discovery, personalized medicine, and advanced diagnostics leveraging imaging and wearables. Additional developments encompass automation of laboratory workflows through AI-Science Factories, domain-specific large language models for regulatory applications, enhanced clinical trial optimization, and seamless AI integration for pharmacovigilance and preventative health strategies. These developments prioritize operational efficiency, cost reduction, and precision by harnessing vast biological and clinical datasets to enable proactive, patient-centric healthcare delivery.
Key Market Challenges
The Artificial intelligence in life sciences market faces several key challenges that hinder widespread adoption. High development costs for AI algorithms, genomic sequencing, and personalized therapies strain budgets, especially for smaller biotech firms. Data privacy concerns and regulatory hurdles, including stringent FDA guidelines on AI validation and ethical AI use, slow down approvals and integration into clinical workflows.
Additionally, problems like AI bias, stemming from training data that underrepresents certain patient groups can lead to unfair treatment results for diverse populations. This erodes trust among healthcare providers. Limited interoperability between disparate healthcare systems and AI platforms further complicates real-world data sharing for biomarker discovery and treatment customization. Despite these obstacles, ongoing innovations in federated learning offer pathways to overcome them, supporting sustained market growth.
Regional Analysis: North America to Hold the Largest Share in the Market
According to our estimates North America currently captures a significant share of Artificial Intelligence in life sciences market. This can be attributed to surging chronic disease burden, including cancer, diabetes, and infectious conditions. Robust R&D investments in AI-driven solutions, combined with advanced healthcare infrastructure and rapid regulatory approvals, further accelerates adoption and innovation in personalized diagnostics and therapies.
Artificial Intelligence In Life Sciences Market: Key Market Segmentation
Deployment Mode
Cloud
On Premise
Type of Offering
Software
Hardware
Services
Type of Technology
Machine Learning
Computer Vision
Natural Language Processing
Predictive Analytics
Application Area
Medical Diagnosis
Drug Discovery
Precision & Personalized Medicine
Biotechnology
Clinical Trials
Patent Monitoring
Geographical Regions
North America
US
Canada
Mexico
Other North American countries
Europe
Austria
Belgium
Denmark
France
Germany
Ireland
Italy
Netherlands
Norway
Russia
Spain
Sweden
Switzerland
UK
Other European countries
Asia
China
India
Japan
Singapore
South Korea
Other Asian countries
Latin America
Brazil
Chile
Colombia
Venezuela
Other Latin American countries
Middle East and North Africa
Egypt
Iran
Iraq
Israel
Kuwait
Saudi Arabia
UAE
Other MENA countries
Rest of the World
Example Players in Artificial Intelligence in Life Sciences Market
Atomwise
BenevolentAI
Exscientia
Foundation Medicine
GE HealthCare
IBM
Insilico Medicine
Microsoft
NVIDIA
Owkin
PathAI
Recursion
Schrodinger
Tempus AI
Artificial Intelligence In Life Sciences Market: Report Coverage
The report on the Artificial intelligence in life sciences market features insights on various sections, including:
Market Sizing and Opportunity Analysis: An in-depth analysis of the artificial intelligence in life sciences market, focusing on key market segments, including [A] deployment mode, [B] type of offering, [C] type of technology, [D] application areas and [E] key geographical regions.
Competitive Landscape: A comprehensive analysis of the companies engaged in the artificial intelligence in life sciences market, based on several relevant parameters, such as [A] year of establishment, [B] company size, [C] location of headquarters and [D] ownership structure.
Company Profiles: Elaborate profiles of prominent players engaged in the artificial intelligence in life sciences market, providing details on [A] location of headquarters, [B] company size, [C] company mission, [D] company footprint, [E] management team, [F] contact details, [G] financial information, [H] operating business segments, [I] product / technology portfolio, [J] recent developments, and an informed future outlook.
Megatrends: An evaluation of ongoing megatrends in the artificial intelligence in life sciences industry.
Recent Developments: An overview of the recent developments made in the artificial intelligence in life sciences market, along with analysis based on relevant parameters, including [A] year of initiative, [B] type of initiative, [C] geographical distribution and [D] most active players.
SWOT Analysis: An insightful SWOT framework, highlighting the strengths, weaknesses, opportunities and threats in the domain. Additionally, it provides Harvey ball analysis, highlighting the relative impact of each SWOT parameter.
Key Questions Answered in this Report
What is the current and future market size?
Who are the leading companies in this market?
What are the growth drivers that are likely to influence the evolution of this market?
What are the key partnership and funding trends shaping this industry?
Which region is likely to grow at higher CAGR till 2040?
How is the current and future market opportunity likely to be distributed across key market segments?
Reasons to Buy this Report
Detailed Market Analysis: 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.
In-depth Analysis of Trends: Stakeholders can leverage the report to gain a deeper understanding of the competitive dynamics within the market. Each report maps ecosystem activity across partnerships, funding, and patent landscapes to reveal growth hotspots and white spaces in the industry.
Opinion of Industry Experts: The report features extensive interviews and surveys with key opinion leaders and industry experts to validate market trends mentioned in the report.
Decision-ready Deliverables: The report offers stakeholders with strategic frameworks (Porter's Five Forces, value chain, SWOT), and complimentary Excel / slide packs with customization support.
Additional Benefits
Complimentary Dynamic Excel Dashboards for Analytical Modules
Exclusive 15% Free Content Customization
Personalized Interactive Report Walkthrough with Our Expert Research Team
Free Report Updates for Versions Older than 6-12 Months
TABLE OF CONTENTS
SECTION I: REPORT OVERVIEW
1. PREFACE
1.1. Introduction
1.2. Market Share Insights
1.3. Key Market Insights
1.4. Report Coverage
1.5. Key Questions Answered
1.6. Chapter Outlines
2. RESEARCH METHODOLOGY
2.1. Chapter Overview
2.2. Research Assumptions
2.3. Database Building
2.3.1. Data Collection
2.3.2. Data Validation
2.3.3. Data Analysis
2.4. Project Methodology
2.4.1. Secondary Research
2.4.1.1. Annual Reports
2.4.1.2. Academic Research Papers
2.4.1.3. Company Websites
2.4.1.4. Investor Presentations
2.4.1.5. Regulatory Filings
2.4.1.6. White Papers
2.4.1.7. Industry Publications
2.4.1.8. Conferences and Seminars
2.4.1.9. Government Portals
2.4.1.10. Media and Press Releases
2.4.1.11. Newsletters
2.4.1.12. Industry Databases
2.4.1.13. Roots Proprietary Databases
2.4.1.14. Paid Databases and Sources
2.4.1.15. Social Media Portals
2.4.1.16. Other Secondary Sources
2.4.2. Primary Research
2.4.2.1. Introduction
2.4.2.2. Types
2.4.2.2.1. Qualitative
2.4.2.2.2. Quantitative
2.4.2.3. Advantages
2.4.2.4. Techniques
2.4.2.4.1. Interviews
2.4.2.4.2. Surveys
2.4.2.4.3. Focus Groups
2.4.2.4.4. Observational Research
2.4.2.4.5. Social Media Interactions
2.4.2.5. Stakeholders
2.4.2.5.1. Company Executives (CXOs)
2.4.2.5.2. Board of Directors
2.4.2.5.3. Company Presidents and Vice Presidents
2.4.2.5.4. Key Opinion Leaders
2.4.2.5.5. Research and Development Heads
2.4.2.5.6. Technical Experts
2.4.2.5.7. Subject Matter Experts
2.4.2.5.8. Scientists
2.4.2.5.9. Doctors and Other Healthcare Providers
2.4.2.6. Ethics and Integrity
2.4.2.6.1. Research Ethics
2.4.2.6.2. Data Integrity
2.4.3. Analytical Tools and Databases
3. MARKET DYNAMICS
3.1. Forecast Methodology
3.1.1. Top-Down Approach
3.1.2. Bottom-Up Approach
3.1.3. Hybrid Approach
3.2. Market Assessment Framework
3.2.1. Total Addressable Market (TAM)
3.2.2. Serviceable Addressable Market (SAM)
3.2.3. Serviceable Obtainable Market (SOM)
3.2.4. Currently Acquired Market (CAM)
3.3. Forecasting Tools and Techniques
3.3.1. Qualitative Forecasting
3.3.2. Correlation
3.3.3. Regression
3.3.4. Time Series Analysis
3.3.5. Extrapolation
3.3.6. Convergence
3.3.7. Forecast Error Analysis
3.3.8. Data Visualization
3.3.9. Scenario Planning
3.3.10. Sensitivity Analysis
3.4. Key Considerations
3.4.1. Demographics
3.4.2. Market Access
3.4.3. Reimbursement Scenarios
3.4.4. Industry Consolidation
3.5. Robust Quality Control
3.6. Key Market Segmentations
3.7. Limitations
4. MACRO-ECONOMIC INDICATORS
4.1. Chapter Overview
4.2. Market Dynamics
4.2.1. Time Period
4.2.1.1. Historical Trends
4.2.1.2. Current and Forecasted Estimates
4.2.2. Currency Coverage
4.2.2.1. Overview of Major Currencies Affecting the Market
4.2.2.2. Impact of Currency Fluctuations on the Industry
4.2.3. Foreign Exchange Impact
4.2.3.1. Evaluation of Foreign Exchange Rates and Their Impact on Market
4.2.3.2. Strategies for Mitigating Foreign Exchange Risk
4.2.4. Recession
4.2.4.1. Historical Analysis of Past Recessions and Lessons Learnt
4.2.4.2. Assessment of Current Economic Conditions and Potential Impact on the Market
4.2.5. Inflation
4.2.5.1. Measurement and Analysis of Inflationary Pressures in the Economy
4.2.5.2. Potential Impact of Inflation on the Market Evolution
4.2.6. Interest Rates
4.2.6.1. Overview of Interest Rates and Their Impact on the Market
4.2.6.2. Strategies for Managing Interest Rate Risk
4.2.7. Commodity Flow Analysis
4.2.7.1. Type of Commodity
4.2.7.2. Origins and Destinations
4.2.7.3. Values and Weights
4.2.7.4. Modes of Transportation
4.2.8. Global Trade Dynamics
4.2.8.1. Import Scenario
4.2.8.2. Export Scenario
4.2.9. War Impact Analysis
4.2.9.1. Russian-Ukraine War
4.2.9.2. Israel-Hamas War
4.2.10. COVID Impact / Related Factors
4.2.10.1. Global Economic Impact
4.2.10.2. Industry-specific Impact
4.2.10.3. Government Response and Stimulus Measures
4.2.10.4. Future Outlook and Adaptation Strategies
4.2.11. Other Indicators
4.2.11.1. Fiscal Policy
4.2.11.2. Consumer Spending
4.2.11.3. Gross Domestic Product (GDP)
4.2.11.4. Employment
4.2.11.5. Taxes
4.2.11.6. R&D Innovation
4.2.11.7. Stock Market Performance
4.2.11.8. Supply Chain
4.2.11.9. Cross-Border Dynamics
SECTION II: QUALITATIVE INSIGHTS
5. EXECUTIVE SUMMARY
6. INTRODUCTION
6.1. Chapter Overview
6.2. Overview of Artificial Intelligence in Life Sciences Market
6.2.1. Historical Evolution
6.2.2. Key Applications
6.2.3. Impact on Healthcare
6.3. Future Perspective
7. REGULATORY SCENARIO
SECTION III: MARKET OVERVIEW
8. COMPREHENSIVE DATABASE OF LEADING PLAYERS
9. COMPETITIVE LANDSCAPE
9.1. Chapter Overview
9.2. Artificial Intelligence in Life Sciences Market: Overall Market Landscape
9.2.1. Analysis by Year of Establishment
9.2.2. Analysis by Company Size
9.2.3. Analysis by Location of Headquarters
9.2.4. Analysis by Ownership Structure
10. COMPANY COMPETITIVENESS ANALYSIS
11. STARTUP ECOSYSTEM IN THE ARTIFICIAL INTELLIGENCE IN LIFE SCIENCES MARKET
11.1. Artificial Intelligence in Life Sciences Market: Market Landscape of Startups
11.1.1. Analysis by Year of Establishment
11.1.2. Analysis by Company Size
11.1.3. Analysis by Company Size and Year of Establishment
11.1.4. Analysis by Location of Headquarters
11.1.5. Analysis by Company Size and Location of Headquarters
11.1.6. Analysis by Ownership Structure
11.2. Key Findings
SECTION IV: COMPANY PROFILES
12. COMPANY PROFILES
12.1. Chapter Overview
12.2. Atomwise*
12.2.1. Company Overview
12.2.2. Company Mission
12.2.3. Company Footprint
12.2.4. Management Team
12.2.5. Contact Details
12.2.6. Financial Performance
12.2.7. Operating Business Segments
12.2.8. Service / Product Portfolio (project specific)
12.2.9. MOAT Analysis
12.2.10. Recent Developments and Future Outlook
12.3. BenevolentAI
12.4. Exscientia
12.5. Foundation Medicine
12.6. GE HealthCare
12.7. IBM
12.8. Insilico Medicine
12.9. Microsoft
12.10. NVIDIA
12.11. Owkin
12.12. PathAI
12.12. Recursion
12.14. Schrodinger
12.15. Tempus AI
SECTION V: MARKET TRENDS
13. MEGA TRENDS ANALYSIS
14. PATENT ANALYSIS
15. RECENT DEVELOPMENTS
15.1. Chapter Overview
15.2. Recent Funding
15.3. Recent Partnerships
15.4. Other Recent Initiatives
SECTION VI: MARKET OPPORTUNITY ANALYSIS
16. GLOBAL ARTIFICIAL INTELLIGENCE IN LIFE SCIENCES MARKET
16.1. Chapter Overview
16.2. Key Assumptions and Methodology
16.3. Trends Disruption Impacting Market
16.4. Demand Side Trends
16.5. Supply Side Trends
16.6. Global Artificial Intelligence in Life Sciences Market, Historical Trends (Since 2020) and Forecasted Estimates (Till 2040)
16.7. Multivariate Scenario Analysis
16.7.1. Conservative Scenario
16.7.2. Optimistic Scenario
16.8. Investment Feasibility Index
16.9. Key Market Segmentations
17. MARKET OPPORTUNITIES BASED ON DEPLOYMENT MODE
17.1. Chapter Overview
17.2. Key Assumptions and Methodology
17.3. Revenue Shift Analysis
17.4. Market Movement Analysis
17.5. Penetration-Growth (P-G) Matrix
17.6. Artificial Intelligence in Life Sciences Market for Cloud: Historical Trends (Since 2020) and Forecasted Estimates (Till 2040)
17.7. Artificial Intelligence in Life Sciences Market for On Premise: Historical Trends (Since 2020) and Forecasted Estimates (Till 2040)
17.8. Data Triangulation and Validation
17.8.1. Secondary Sources
17.8.2. Primary Sources
17.8.3. Statistical Modeling
18. MARKET OPPORTUNITIES BASED ON TYPE OF OFFERING
18.1. Chapter Overview
18.2. Key Assumptions and Methodology
18.3. Revenue Shift Analysis
18.4. Market Movement Analysis
18.5. Penetration-Growth (P-G) Matrix
18.6. Artificial Intelligence in Life Sciences Market for Software: Historical Trends (Since 2020) and Forecasted Estimates (Till 2040)
18.7. Artificial Intelligence in Life Sciences Market for Hardware: Historical Trends (Since 2020) and Forecasted Estimates (Till 2040)
18.8. Artificial Intelligence in Life Sciences Market for Services: Historical Trends (Since 2020) and Forecasted Estimates (Till 2040)
18.9. Data Triangulation and Validation
18.9.1. Secondary Sources
18.9.2. Primary Sources
18.9.3. Statistical Modeling
19. MARKET OPPORTUNITIES BASED ON TYPE OF TECHNOLOGY
19.1. Chapter Overview
19.2. Key Assumptions and Methodology
19.3. Revenue Shift Analysis
19.4. Market Movement Analysis
19.5. Penetration-Growth (P-G) Matrix
19.6. Artificial Intelligence in Life Sciences Market for Machine Learning: Historical Trends (Since 2020) and Forecasted Estimates (Till 2040)
19.7. Artificial Intelligence in Life Sciences Market for Computer Vision: Historical Trends (Since 2020) and Forecasted Estimates (Till 2040)
19.8. Artificial Intelligence in Life Sciences Market for Natural Language Processing: Historical Trends (Since 2020) and Forecasted Estimates (Till 2040)
19.9. Artificial Intelligence in Life Sciences Market for Immunology: Historical Trends (Since 2020) and Forecasted Estimates (Till 2040)
19.10. Artificial Intelligence in Life Sciences Market for Predictive Analytics: Historical Trends (Since 2020) and Forecasted Estimates (Till 2040)
19.11. Data Triangulation and Validation
19.11.1. Secondary Sources
19.11.2. Primary Sources
19.11.3. Statistical Modeling
20. MARKET OPPORTUNITIES BASED ON APPLICATION AREAS
20.1. Chapter Overview
20.2. Key Assumptions and Methodology
20.3. Revenue Shift Analysis
20.4. Market Movement Analysis
20.5. Penetration-Growth (P-G) Matrix
20.6. Artificial Intelligence in Life Sciences Market for Medical Diagnosis: Historical Trends (Since 2020) and Forecasted Estimates (Till 2040)
20.7. Artificial Intelligence in Life Sciences Market for Drug Discovery: Historical Trends (Since 2020) and Forecasted Estimates (Till 2040)
20.8. Artificial Intelligence in Life Sciences Market for Precision & Personalized Medicine: Historical Trends (Since 2020) and Forecasted Estimates (Till 2040)
20.9. Artificial Intelligence in Life Sciences Market for Biotechnology: Historical Trends (Since 2020) and Forecasted Estimates (Till 2040)
20.10. Artificial Intelligence in Life Sciences Market for Clinical Trials: Historical Trends (Since 2020) and Forecasted Estimates (Till 2040)
20.11. Artificial Intelligence in Life Sciences Market for Patent Monitoring: Historical Trends (Since 2020) and Forecasted Estimates (Till 2040)
20.12. Data Triangulation and Validation
20.12.1. Secondary Sources
20.12.2. Primary Sources
20.12.3. Statistical Modeling
21. MARKET OPPORTUNITIES FOR ARTIFICIAL INTELLIGENCE IN LIFE SCIENCES MARKET IN NORTH AMERICA
21.1. Chapter Overview
21.2. Key Assumptions and Methodology
21.3. Revenue Shift Analysis
21.4. Market Movement Analysis
21.5. Penetration-Growth (P-G) Matrix
21.6. Artificial Intelligence in Life Sciences Market in North America: Historical Trends (Since 2020) and Forecasted Estimates (Till 2040)
21.6.1. Artificial Intelligence in Life Sciences Market in the US: Historical Trends (Since 2020) and Forecasted Estimates (Till 2040)
21.6.2. Artificial Intelligence in Life Sciences Market in Canada: Historical Trends (Since 2020) and Forecasted Estimates (Till 2040)
21.6.3. Artificial Intelligence in Life Sciences Market in Mexico: Historical Trends (Since 2020) and Forecasted Estimates (Till 2040)
21.6.4. Artificial Intelligence in Life Sciences Market in Other North American Countries: Historical Trends (Since 2020) and Forecasted Estimates (Till 2040)
21.7. Data Triangulation and Validation
22. MARKET OPPORTUNITIES FOR ARTIFICIAL INTELLIGENCE IN LIFE SCIENCES MARKET IN EUROPE
22.1. Chapter Overview
22.2. Key Assumptions and Methodology
22.3. Revenue Shift Analysis
22.4. Market Movement Analysis
22.5. Penetration-Growth (P-G) Matrix
22.6. Artificial Intelligence in Life Sciences Market in Europe: Historical Trends (Since 2020) and Forecasted Estimates (Till 2040)
22.6.1. Artificial Intelligence in Life Sciences Market in Austria: Historical Trends (Since 2020) and Forecasted Estimates (Till 2040)
22.6.2. Artificial Intelligence in Life Sciences Market in Belgium: Historical Trends (Since 2020) and Forecasted Estimates (Till 2040)
22.6.3. Artificial Intelligence in Life Sciences Market in Denmark: Historical Trends (Since 2020) and Forecasted Estimates (Till 2040)
22.6.4. Artificial Intelligence in Life Sciences Market in France: Historical Trends (Since 2020) and Forecasted Estimates (Till 2040)
22.6.5. Artificial Intelligence in Life Sciences Market in Germany: Historical Trends (Since 2020) and Forecasted Estimates (Till 2040)
22.6.6. Artificial Intelligence in Life Sciences Market in Ireland: Historical Trends (Since 2020) and Forecasted Estimates (Till 2040)
22.6.7. Artificial Intelligence in Life Sciences Market in Italy: Historical Trends (Since 2020) and Forecasted Estimates (Till 2040)
22.6.8. Artificial Intelligence in Life Sciences Market in Netherlands: Historical Trends (Since 2020) and Forecasted Estimates (Till 2040)
22.6.9. Artificial Intelligence in Life Sciences Market in Norway: Historical Trends (Since 2020) and Forecasted Estimates (Till 2040)
22.6.10. Artificial Intelligence in Life Sciences Market in Russia: Historical Trends (Since 2020) and Forecasted Estimates (Till 2040)
22.6.11. Artificial Intelligence in Life Sciences Market in Spain: Historical Trends (Since 2020) and Forecasted Estimates (Till 2040)
22.6.12. Artificial Intelligence in Life Sciences Market in Sweden: Historical Trends (Since 2020) and Forecasted Estimates (Till 2040)
22.6.13. Artificial Intelligence in Life Sciences Market in Switzerland: Historical Trends (Since 2020) and Forecasted Estimates (Till 2040)
22.6.14. Artificial Intelligence in Life Sciences Market in the UK: Historical Trends (Since 2020) and Forecasted Estimates (Till 2040)
22.6.15. Artificial Intelligence in Life Sciences Market in Other European Countries: Historical Trends (Since 2020) and Forecasted Estimates (Till 2040)
22.7. Data Triangulation and Validation
23. MARKET OPPORTUNITIES FOR ARTIFICIAL INTELLIGENCE IN LIFE SCIENCES MARKET IN ASIA
23.1. Chapter Overview
23.2. Key Assumptions and Methodology
23.3. Revenue Shift Analysis
23.4. Market Movement Analysis
23.5. Penetration-Growth (P-G) Matrix
23.6. Artificial Intelligence in Life Sciences Market in Asia: Historical Trends (Since 2020) and Forecasted Estimates (Till 2040)
23.6.1. Artificial Intelligence in Life Sciences Market in China: Historical Trends (Since 2020) and Forecasted Estimates (Till 2040)
23.6.2. Artificial Intelligence in Life Sciences Market in India: Historical Trends (Since 2020) and Forecasted Estimates (Till 2040)
23.6.3. Artificial Intelligence in Life Sciences Market in Japan: Historical Trends (Since 2020) and Forecasted Estimates (Till 2040)
23.6.4. Artificial Intelligence in Life Sciences Market in Singapore: Historical Trends (Since 2020) and Forecasted Estimates (Till 2040)
23.6.5. Artificial Intelligence in Life Sciences Market in South Korea: Historical Trends (Since 2020) and Forecasted Estimates (Till 2040)
23.6.6. Artificial Intelligence in Life Sciences Market in Other Asian Countries: Historical Trends (Since 2020) and Forecasted Estimates (Till 2040)
23.7. Data Triangulation and Validation
24. MARKET OPPORTUNITIES FOR ARTIFICIAL INTELLIGENCE IN LIFE SCIENCES MARKET IN MIDDLE EAST AND NORTH AFRICA (MENA)
24.1. Chapter Overview
24.2. Key Assumptions and Methodology
24.3. Revenue Shift Analysis
24.4. Market Movement Analysis
24.5. Penetration-Growth (P-G) Matrix
24.6. Artificial Intelligence in Life Sciences Market in Middle East and North Africa (MENA): Historical Trends (Since 2020) and Forecasted Estimates (Till 2040)
24.6.1. Artificial Intelligence in Life Sciences Market in Egypt: Historical Trends (Since 2020) and Forecasted Estimates (Till 205)
24.6.2. Artificial Intelligence in Life Sciences Market in Iran: Historical Trends (Since 2020) and Forecasted Estimates (Till 2040)
24.6.3. Artificial Intelligence in Life Sciences Market in Iraq: Historical Trends (Since 2020) and Forecasted Estimates (Till 2040)
24.6.4. Artificial Intelligence in Life Sciences Market in Israel: Historical Trends (Since 2020) and Forecasted Estimates (Till 2040)
24.6.5. Artificial Intelligence in Life Sciences Market in Kuwait: Historical Trends (Since 2020) and Forecasted Estimates (Till 2040)
24.6.6. Artificial Intelligence in Life Sciences Market in Saudi Arabia: Historical Trends (Since 2020) and Forecasted Estimates (Till 2040)
24.6.7. Artificial Intelligence in Life Sciences Market in United Arab Emirates (UAE): Historical Trends (Since 2020) and Forecasted Estimates (Till 2040)
24.6.8. Artificial Intelligence in Life Sciences Market in Other MENA Countries: Historical Trends (Since 2020) and Forecasted Estimates (Till 2040)
24.7. Data Triangulation and Validation
25. MARKET OPPORTUNITIES FOR ARTIFICIAL INTELLIGENCE IN LIFE SCIENCES MARKET IN LATIN AMERICA
25.1. Chapter Overview
25.2. Key Assumptions and Methodology
25.3. Revenue Shift Analysis
25.4. Market Movement Analysis
25.5. Penetration-Growth (P-G) Matrix
25.6. Artificial Intelligence in Life Sciences Market in Latin America: Historical Trends (Since 2020) and Forecasted Estimates (Till 2040)
25.6.1. Artificial Intelligence in Life Sciences Market in Argentina: Historical Trends (Since 2020) and Forecasted Estimates (Till 2040)
25.6.2. Artificial Intelligence in Life Sciences Market in Brazil: Historical Trends (Since 2020) and Forecasted Estimates (Till 2040)
25.6.3. Artificial Intelligence in Life Sciences Market in Chile: Historical Trends (Since 2020) and Forecasted Estimates (Till 2040)
25.6.4. Artificial Intelligence in Life Sciences Market in Colombia Historical Trends (Since 2020) and Forecasted Estimates (Till 2040)
25.6.5. Artificial Intelligence in Life Sciences Market in Venezuela: Historical Trends (Since 2020) and Forecasted Estimates (Till 2040)
25.6.6. Artificial Intelligence in Life Sciences Market in Other Latin American Countries: Historical Trends (Since 2020) and Forecasted Estimates (Till 2040)
25.7. Data Triangulation and Validation
26. MARKET OPPORTUNITIES FOR ARTIFICIAL INTELLIGENCE IN LIFE SCIENCES MARKET IN REST OF THE WORLD
26.1. Chapter Overview
26.2. Key Assumptions and Methodology
26.3. Revenue Shift Analysis
26.4. Market Movement Analysis
26.5. Penetration-Growth (P-G) Matrix
26.6. Artificial Intelligence in Life Sciences Market in Rest of the World: Historical Trends (Since 2020) and Forecasted Estimates (Till 2040)
26.6.1. Artificial Intelligence in Life Sciences Market in Australia: Historical Trends (Since 2020) and Forecasted Estimates (Till 2040)
26.6.2. Artificial Intelligence in Life Sciences Market in New Zealand: Historical Trends (Since 2020) and Forecasted Estimates (Till 2040)
26.6.3. Artificial Intelligence in Life Sciences Market in Other Countries
26.7. Data Triangulation and Validation
27. MARKET CONCENTRATION ANALYSIS: DISTRIBUTION BY LEADING PLAYERS
