한글목차

정밀의료용 AI 시장 규모는 2024년 7억 8,000만 달러에서 예측 기간 중 30.7%의 CAGR로 추이하며, 2030년에는 39억 2,000만 달러 규모로 성장할 것으로 예측됩니다.

정밀의료용 AI 시장은 진단 및 예측 분석의 강화에 힘입어 성장하고 있습니다. 웨어러블 기기는 환자의 영상 및 기타 관련 매개변수를 모니터링하여 질병이 나타나기 훨씬 전에 질병의 징후와 치료 결과를 탐색합니다. 또한 AI는 기존 진단 및 치료의 생산성을 향상시켜 정밀의료를 보다 저렴하고 광범위하게 적용할 수 있게 해주고, 보다 저렴한 의료 서비스 제공에 대한 움직임도 성장 요인 중 하나입니다. 반면, 도입 비용, 양질의 데이터에 대한 접근성 부족, 데이터 보안 및 프라이버시 문제 등 여러 가지 문제점이 있습니다. 또한 규제 요건을 포함한 기존 의료 프로세스에 AI를 통합하는 복잡한 특성으로 인해 확산이 지연될 수 있습니다.

"예측 기간 중 툴별로는 자연 언어 처리(NLP)가 가장 빠른 성장률을 보일 것으로 전망"

자연 언어 처리(NLP)는 비정형 데이터를 정형 데이터와 통합하여 환자의 병력을 더 잘 이해하고 치료 맞춤화 제안을 개선하는 데 도움이 될 수 있습니다. 또한 NLP 기반 용도는 간결한 보고서를 제공하고 의약품 발명 및 질병 진단 과정을 가속화하는 많은 과학적 데이터와 문헌을 검토하여 매우 빠른 의사결정을 지원하는 데 사용되고 있습니다. 정밀의료 통합 솔루션에 대한 수요 증가와 함께 EHR 시스템의 도입이 확대되고 있는 것도 NLP 기술 시장을 자극하고 있습니다. 다양한 의료 데이터에 대한 적용 가능성과 더 나은 결과를 약속하는 NLP는 시장의 판도를 바꾸고 있습니다.

"최종사용자별로는 2023년 의료 서비스 프로바이더가 가장 큰 시장 점유율을 차지할 것으로 예상"

의료 서비스 프로바이더는 진단, 치료 계획 및 환자 결과를 개선하는 데 사용되는 AI 툴의 최전선 사용자라는 사실로 인해 가장 큰 점유율을 차지하고 있습니다. 병원 및 클리닉은 환자 데이터 분석, 치료 매핑 및 의사결정의 질을 향상시키기 위해 AI 플랫폼을 채택하고 있습니다. 현재 의료 영상, 유전체, 맞춤형 치료 분야에서 AI 기술 도입이 급증하고 있으며, 의료 서비스 프로바이더는 신속하고 효과적인 방식으로 맞춤형 치료를 제공할 수 있게 되었습니다. 또한 AI 솔루션에 대한 지출 증가와 효율적인 고품질 의료 시스템에 대한 수요 증가는 의료 서비스 프로바이더 시장 침투를 촉진하는 두 가지 요인으로 작용하고 있습니다.

"아시아태평양이 예측 기간 중 가장 높은 CAGR을 나타낼 것으로 예상"

아시아태평양의 정밀의료용 AI 시장은 헬스케어 인프라 시설에 대한 자원 배분 강화, AI 기술 채택 촉진, 유전체 연구 구상 증가로 인해 예측 기간 중 가장 높은 CAGR을 나타낼 것으로 예상됩니다. 중국, 일본, 인도와 같은 국가들은 정부와 민간 조직의 노력으로 AI를 비롯한 첨단 기술을 통해 헬스케어 시스템을 혁신하기 위해 노력하고 있습니다. 동시에 인구 고령화도 이 지역의 성장을 가속하고 있으며, 특히 종양 및 만성질환 관리를 위한 정밀치료에 대한 높은 수요를 창출하고 있습니다. 또한 이 지역에는 이 기술을 전문으로 하는 세계 기업과 현지 기업 모두 유입되어 기술 혁신과 활용의 속도를 촉진하고 있습니다.

세계의 정밀의료용 AI 시장을 조사했으며, 시장 개요, 시장 성장에 대한 각종 영향요인 분석, 기술·특허의 동향, 법규제 환경, 사례 연구, 시장 규모 추이·예측, 각종 구분·지역별 상세 분석, 경쟁 환경, 주요 기업의 개요 등을 정리하여 전해드립니다.

목차

제1장 서론

제2장 조사 방법

제3장 개요

제4장 주요 인사이트

제5장 시장 개요

• 시장 역학
  • 촉진요인
  • 억제요인
  • 기회
  • 과제
• 고객 사업에 영향을 미치는 동향/파괴적 변화
• 업계 동향
• 에코시스템 분석
• 밸류체인 분석
• 기술 분석
• 규제 분석
• 가격 분석
• Porter's Five Forces 분석
• 특허 분석
• 주요 이해관계자와 구입 기준
• 최종사용자 분석
• 주요 컨퍼런스와 이벤트
• 사례 연구 분석
• 투자와 자금조달 시나리오
• 비즈니스 모델
• 정밀의료 시장에서 AI/생성형 AI의 영향

제6장 정밀의료용 AI 시장 : 용도별

• Drug Discovery·의약품 개발
  • Drug Discovery
  • 질병의 이해
  • DRUG REPURPOSING
  • 신규 의약품 설계
  • 약제 최적화
  • 안전성·독성
  • 임상 개발
• 진단·스크리닝
  • 리스크 평가·환자 층별화
  • 질환 스크리닝
  • 질환 진단
  • 질환 진행, 병기 분류, 예후
• 치료
  • 치료 선택·계획
  • 치료 모니터링
  • 치료 후 감시·팔로 업

제7장 정밀의료용 AI 시장 : 치료 영역별

• 종양
• 희귀질환
• 감염증
• 신경
• 심장병
• 혈액
• 기타

제8장 정밀의료용 AI 시장 : 컴포넌트별

• 소프트웨어
• 서비스

제9장 정밀의료용 AI 시장 : 툴별

• 기계학습
  • 딥러닝
  • 지도형 기계학습
  • 강화 기계학습
  • 비지도형 기계학습
  • 기타
• 자연언어처리(NLP)
• 상황 인식 처리 & 컴퓨팅
• 컴퓨터 비전
• 영상 분석
• 기타

제10장 정밀의료용 AI 시장 : 도입별

• 클라우드 기반 모델
• 온프레미스 모델
• 하이브리드 모델

제11장 정밀의료용 AI 시장 : 최종사용자별

• 헬스케어 프로바이더
• 제약·바이오테크놀러지 기업
• 의료기기·설비 회사
• 연구 센터·학술기관·정부기관
• 기타

제12장 정밀의료용 AI 시장 : 지역별

• 북미
  • 북미 : 거시경제 전망
  • 미국
  • 캐나다
• 유럽
  • 유럽 : 거시경제 전망
  • 영국
  • 독일
  • 프랑스
  • 이탈리아
  • 스페인
  • 기타
• 아시아태평양
  • 아시아태평양 : 거시경제 전망
  • 일본
  • 중국
  • 인도
  • 기타
• 라틴아메리카
  • 라틴아메리카 : 거시경제 전망
  • 브라질
  • 멕시코
  • 기타
• 중동 및 아프리카
  • 중동 및 아프리카 : 거시경제 전망
  • GCC 국가
  • 기타

제13장 경쟁 구도

• 주요 기업의 전략/유력 기업
• 매출 분석
• 시장 점유율 분석
• 기업 평가 매트릭스 : 주요 기업
• 기업 평가 매트릭스 : 스타트업/중소기업
• 기업 가치 평가와 재무 지표
• 브랜드/제품 비교
• 경쟁 시나리오

제14장 기업 개요

• 주요 기업
  • NVIDIA CORPORATION
  • EXSCIENTIA
  • GOOGLE
  • ILLUMINA, INC.
  • TEMPUS AI, INC.
  • BENEVOLENTAI
  • MICROSOFT CORPORATION
  • IBM
  • GE HEALTHCARE
  • DEEP GENOMICS
  • SIEMENS HEALTHINEERS AG
  • BIOXCEL THERAPEUTICS, INC.
  • INSILICO MEDICINE
  • PATHAI, INC.
  • VERGE GENOMICS
  • GUARDANT HEALTH, INC.
  • GRAIL, INC.
  • FOUNDATION MEDICINE, INC.
  • PROSCIA INC.
  • FLATIRON HEALTH
• 기타 기업
  • PREDICTIVE ONCOLOGY
  • PAIGE AI, INC.
  • DENSITAS INC.
  • ZEPHYR AI, INC.
  • NUCLEAI, INC.

제15장 부록

영문목차

The AI in precision medicine market is projected to reach USD 3.92 billion by 2030 from USD 0.78 billion in 2024, at a CAGR of 30.7% from 2024 to 2030. The market for AI in precision medicine is propelled by the enhanced diagnostics as well as predictive analytics. Wearable devices monitor patient's imaging and other related parameters and search for signs of disease, long before it shows itself, or the outcomes of treatments. Additionally, the movement towards cheaper healthcare provision is also the other factor. AI increases the productivity of conventional diagnosis and treatment procedures; thus, it makes precision medicine cheap and widely applicable. On the contrary, factors such as costs associated with implementation, inadequate access to high-quality data and issues with data security and privacy present challenges. Furthermore, the intricate nature of incorporating AI into already existing healthcare processes including regulatory requirements may also slow down its uptake.

"Natural language processing (NLP) had the fastest growth rate in the AI in precision medicine market during the forecast period, by tools."

Natural Language Processing (NLP) is anticipated to register the highest growth rate within the AI in precision medicine market as a result of its efficiency in deriving meaning from adequate unstructured medical data which consist of clinical notes, research works, and patient records. NLP helps to integrate unstructured data with structured data helps to get a better view of patient's history and suggestions regarding customizing treatment are improved. For instance, Tempus utilizes NLP techniques in fresh oncology treatment plans to find trends in the use of electronic health records. Furthermore, NLP-based applications are used to provide concise reports and help in making decisions very fast by shifting through a lot of scientific data and literature which hastens the process of drug invention and the diagnosis of diseases. The growing implementation of EHR systems alongside the rising need for precision medicine integrated solutions stimulates the market for NLP technology. Its applicability in dealing with different healthcare data and promise of better results makes it a game changer in the market.

"By end user, the healthcare providers to account for largest market share in 2023."

By end user, AI in precision medicine market is bifurcated into healthcare providers, pharmaceutical & biotechnology companies, medical device/equipment companies, research centers, academic institutes, & government organizations, and others. The healthcare providers accounted for the largest share of the market for AI in precision medicine owing to the fact that they are the foremost practitioners of the AI tools used to enhance diagnosis, treatment planning and patient outcome. Hospitals and clinics employ AI platforms for patient data analysis, therapeutic mapping, and improving the quality of decision making. The current rampant deployment of the AI technology in the fields of medical imaging, genomics and custom care provision has made it possible for providers to give customized therapies in a quick and effective manner. In addition, the rising expenditure on AI solutions and the increasing demand for efficient and high quality healthcare systems are two factors that facilitate penetration of the market by healthcare providers.

"Asia Pacific is estimated to register the highest CAGR over the forecast period."

The AI in precision medicine market is geographically segmented into North America, Europe, Asia Pacific, Latin America, and Middle East & Africa. The Asia Pacific's AI in precision medicine market is projected to register highest CAGR during the forecast period due to enhanced allocation of resources towards healthcare infrastructure facilities, promotion of adoption of AI technology, and growing initiatives in genomic research. Countries like China, Japan and India are turning towards advanced technologies like Artificial Intelligence to transform the health care systems in these nations, due to government and private organization efforts. At the same time, the aging population creates a high demand for precision therapeutics, especially for oncology and chronic illness management, which also promotes growth in this region. In addition, an influx of both global and local companies specializing in the technology in the region, stimulates speed of innovation and use of the technology.

Breakdown of supply-side primary interviews by company type, designation, and region:

• By Company Type: Tier 1 (40%), Tier 2 (35%), and Tier 3 (25%)
• By Designation: Managers (40%), Directors (35%), and Others (25%)
• By Region: North America (40%), Europe (30%), Asia Pacific (20%), Latin America (5%) and Middle East Africa (5%)

List of Companies Profiled in the Report:

• NVIDIA Corporation (US)
• Google, Inc. (US)
• Microsoft (US)
• IBM (US)
• Illumina, Inc. (US)
• Exscientia (UK)
• Insilico Medicine (US)
• GE Healthcare (US)
• Tempus AI, Inc. (US)
• Siemens Healthineers AG (Germany)
• BioXcel Therapeutics, Inc. (US)
• BenevolentAI (UK)
• PathAI, Inc. (US)
• Guardant Health (US)
• GRAIL, Inc. (US)
• FOUNDATION MEDICINE, INC. (US)
• FLATIRON HEALTH (US)
• Proscia Inc. (US)
• DEEP GENOMICS. (Canada)
• Verge Genomics (US)
• Predictive Oncology (US)
• Paige AI, Inc. (US)
• Densitas Inc. (Canada)
• Zephyr AI (US)
• Iktos (France)

Research Coverage:

This research report categorizes the AI in precision medicine market by application (drug discovery & development, diagnostics & screening, and therapeutics), therapeutic area (oncology, rare diseases, infectious diseases, neurology, cardiology, haematology, and others), component (hardware, software, and services), tools (machine learning, natural language processing (NLP), context-aware processing and computing, computer vision, image analysis (including optical character recognition), and others), deployment (cloud-based model, on-premise model, and hybrid model), end user (healthcare providers, pharmaceutical & biotechnology companies, medical device/equipment companies, research centers, academic institutes, & government organizations, and others) and region. The scope of the report covers detailed information regarding the major factors, such as drivers, restraints, challenges, and opportunities, influencing the growth of the AI in precision medicine market. A thorough analysis of the key industry players has been done to provide insights into their business overview, offerings, and key strategies such as acquisitions, collaborations, partnerships, mergers, product/service launches & enhancements, and approvals in the AI in precision medicine market. Competitive analysis of upcoming startups in the AI in precision medicine market ecosystem is covered in this report.

Reasons to Buy the Report

The report will help market leaders/new entrants in this market with information on the closest approximations of the revenue numbers for the overall AI in precision medicine market and the subsegments. This report will help stakeholders understand the competitive landscape and gain more insights to better position their businesses and plan suitable go-to-market strategies. The report also helps stakeholders understand the market pulse and provides information on key market drivers, restraints, challenges, and opportunities.

The report provides insights on the following pointers:

• Analysis of key drivers: (Rising Demand for Personalized Healthcare), restraints (Limited access to high-quality data), opportunities (Expanding genomic research), and challenges (Regulatory and ethical complexities) influencing the growth of the AI in precision medicine market.
• Product Development/Innovation: Detailed insights on upcoming technologies, research & development activities, and new product & service launches in the AI in precision medicine market.
• Market Development: Comprehensive information about lucrative markets - the report analyses the AI in precision medicine market across varied regions.
• Market Diversification: Exhaustive information about new products & services, untapped geographies, recent developments, and investments in the AI in precision medicine market.
• Competitive Assessment: In-depth assessment of market shares, growth strategies, and service offerings of leading players such as NVIDIA Corporation (US), Google, Inc. (US), Microsoft (US), IBM (US), Illumina, Inc. (US), Exscientia (UK), etc. among others in AI in precision medicine market.

TABLE OF CONTENTS

1 INTRODUCTION

• 1.1 STUDY OBJECTIVES
• 1.2 MARKET DEFINITION
• 1.3 STUDY SCOPE
  • 1.3.1 MARKETS COVERED & REGIONAL SCOPE
  • 1.3.2 INCLUSIONS & EXCLUSIONS
  • 1.3.3 YEARS CONSIDERED
• 1.4 CURRENCY CONSIDERED
• 1.5 STAKEHOLDERS

2 RESEARCH METHODOLOGY

• 2.1 RESEARCH DATA
  • 2.1.1 SECONDARY DATA
    • 2.1.1.1 Key data from secondary sources
  • 2.1.2 PRIMARY DATA
    • 2.1.2.1 Key data from primary sources
• 2.2 MARKET SIZE ESTIMATION
• 2.3 MARKET SHARE ESTIMATION
• 2.4 DATA TRIANGULATION
• 2.5 RESEARCH ASSUMPTIONS
• 2.6 LIMITATIONS
  • 2.6.1 METHODOLOGY-RELATED LIMITATIONS
  • 2.6.2 SCOPE-RELATED LIMITATIONS
• 2.7 RISK ASSESSMENT

3 EXECUTIVE SUMMARY

4 PREMIUM INSIGHTS

• 4.1 ARTIFICIAL INTELLIGENCE IN PRECISION MEDICINE MARKET OVERVIEW
• 4.2 ARTIFICIAL INTELLIGENCE IN PRECISION MEDICINE MARKET, BY REGION
• 4.3 NORTH AMERICA: ARTIFICIAL INTELLIGENCE IN PRECISION MEDICINE MARKET, BY END USER & REGION
• 4.4 ARTIFICIAL INTELLIGENCE IN PRECISION MEDICINE MARKET: GEOGRAPHIC SNAPSHOT
• 4.5 ARTIFICIAL INTELLIGENCE IN PRECISION MEDICINE MARKET: DEVELOPED VS. EMERGING MARKETS

5 MARKET OVERVIEW

• 5.1 INTRODUCTION
• 5.2 MARKET DYNAMICS
• 5.3 MARKET DYNAMICS
  • 5.3.1 DRIVERS
    • 5.3.1.1 Increase in investments in R&D and rise in demand for personalized medication
    • 5.3.1.2 Advancements in genomic research and data availability
    • 5.3.1.3 Growth in cross-industry collaborations and partnerships
    • 5.3.1.4 Role of regulatory landscape in driving AI adoption in healthcare
  • 5.3.2 RESTRAINTS
    • 5.3.2.1 Increase in data breach concerns
    • 5.3.2.2 High cost of implementation of precision medicine solutions
    • 5.3.2.3 Accuracy challenges in AI adoption for healthcare
  • 5.3.3 OPPORTUNITIES
    • 5.3.3.1 Role of predictive analytics in advancing AI for healthcare
    • 5.3.3.2 Leveraging research pipelines and new drug development for AI in healthcare
  • 5.3.4 CHALLENGES
    • 5.3.4.1 Impact of fairness and bias on AI in healthcare
    • 5.3.4.2 Interoperability challenges due to complexity of AI solutions
• 5.4 TRENDS/DISRUPTIONS IMPACTING CUSTOMER BUSINESSES
• 5.5 INDUSTRY TRENDS
  • 5.5.1 AI'S GROWING ROLE IN PATIENT-SPECIFIC DATA INTEGRATION AND ANALYSIS
  • 5.5.2 ADVANCEMENTS IN AI-POWERED PREDICTIVE ANALYTICS FOR TREATMENT OPTIMIZATION
• 5.6 ECOSYSTEM ANALYSIS
• 5.7 VALUE CHAIN ANALYSIS
• 5.8 TECHNOLOGY ANALYSIS
  • 5.8.1 KEY TECHNOLOGIES
    • 5.8.1.1 Predictive analytics
    • 5.8.1.2 Neural networks
    • 5.8.1.3 Knowledge graphs
    • 5.8.1.4 Cell and gene therapies
    • 5.8.1.5 AI-driven single-cell analysis
  • 5.8.2 COMPLEMENTARY TECHNOLOGY
    • 5.8.2.1 High-performance computing (HPC)
    • 5.8.2.2 Next-generation sequencing
    • 5.8.2.3 Real-world evidence/Real-world data
    • 5.8.2.4 EHR Integration
    • 5.8.2.5 Digital health platforms
  • 5.8.3 ADJACENT TECHNOLOGIES
    • 5.8.3.1 Cloud computing
    • 5.8.3.2 Blockchain technology
    • 5.8.3.3 Internet of Things (IoT) and wearables
    • 5.8.3.4 Robotics and automation
    • 5.8.3.5 3D printing for personalized implants and devices
• 5.9 REGULATORY ANALYSIS
  • 5.9.1 REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS
  • 5.9.2 REGULATORY SCENARIO
• 5.10 PRICING ANALYSIS
  • 5.10.1 INDICATIVE PRICING FOR KEY PLAYERS
  • 5.10.2 INDICATIVE PRICE OF KEY COMPONENTS, BY REGION
• 5.11 PORTER'S FIVE FORCES ANALYSIS
  • 5.11.1 THREAT OF NEW ENTRANTS
  • 5.11.2 THREAT OF SUBSTITUTES
  • 5.11.3 BARGAINING POWER OF SUPPLIERS
  • 5.11.4 BARGAINING POWER OF BUYERS
  • 5.11.5 INTENSITY OF COMPETITIVE RIVALRY
• 5.12 PATENT ANALYSIS
  • 5.12.1 PATENT PUBLICATION TRENDS
  • 5.12.2 JURISDICTION ANALYSIS: TOP APPLICANT COUNTRIES FOR AI IN PRECISION MEDICINE
  • 5.12.3 KEY PATENTS IN AI IN PRECISION MEDICINE MARKET
• 5.13 KEY STAKEHOLDERS AND BUYING CRITERIA
  • 5.13.1 KEY STAKEHOLDERS IN BUYING PROCESS
  • 5.13.2 KEY BUYING CRITERIA
• 5.14 END-USER ANALYSIS
  • 5.14.1 UNMET NEEDS
  • 5.14.2 END-USER EXPECTATIONS
• 5.15 KEY CONFERENCES & EVENTS
• 5.16 CASE STUDY ANALYSIS
  • 5.16.1 SANOFI LEVERAGED AI-DRIVEN PRECISION MEDICINE TO IDENTIFY PATIENT SUBTYPES AND NOVEL TARGETS IN INFLAMMATORY BOWEL DISEASE
  • 5.16.2 IBM'S AI-DRIVEN SOLUTION IMPROVED CLINICAL TRIAL ENROLLMENT AT MAYO CLINIC BY ENHANCING PATIENT MATCHING
  • 5.16.3 ENHANCING PATIENT IDENTIFICATION FOR RARE ONCOLOGY BIOMARKERS THROUGH GENOMIC TESTING AND STRATEGIC COLLABORATION
• 5.17 INVESTMENT AND FUNDING SCENARIO
• 5.18 BUSINESS MODELS
• 5.19 IMPACT OF AI/GEN AI IN PRECISION MEDICINE MARKET
  • 5.19.1 KEY USE CASES
  • 5.19.2 CASE STUDIES OF AI/GENERATIVE AI IMPLEMENTATION
    • 5.19.2.1 Enhancing patient outcomes with AI-driven predictive analytics at Johns Hopkins Hospital
  • 5.19.3 IMPACT OF AI/GEN AI ON INTERCONNECTED AND ADJACENT ECOSYSTEMS
    • 5.19.3.1 AI in drug discovery market
    • 5.19.3.2 Genomics market
    • 5.19.3.3 Artificial intelligence market
    • 5.19.3.4 Pharmacogenomics market
  • 5.19.4 USER READINESS AND IMPACT ASSESSMENT
    • 5.19.4.1 User readiness
      • 5.19.4.1.1 Healthcare providers
      • 5.19.4.1.2 Pharmaceutical & biotechnology companies

6 ARTIFICIAL INTELLIGENCE IN PRECISION MEDICINE MARKET, BY APPLICATION

• 6.1 INTRODUCTION
• 6.2 DRUG DISCOVERY & DEVELOPMENT
  • 6.2.1 DRUG DISCOVERY
  • 6.2.2 UNDERSTANDING DISEASES
    • 6.2.2.1 Rise in data mining to link targets to diseases
  • 6.2.3 DRUG REPURPOSING
    • 6.2.3.1 Use of graphs for targeted approach to reduce timelines and costs
  • 6.2.4 DE NOVO DRUG DESIGN
    • 6.2.4.1 Availability of large-scale biomedical datasets and urgent demand for novel treatments for complex diseases
  • 6.2.5 DRUG OPTIMIZATION
    • 6.2.5.1 Need to process extensive data on molecular properties, target interactions, and clinical outcomes
  • 6.2.6 SAFETY & TOXICITY
    • 6.2.6.1 Building generalizable model for toxicity and off-target effect prediction
  • 6.2.7 CLINICAL DEVELOPMENT
    • 6.2.7.1 Designing and conducting clinical trials for personalized dosing, targeted therapies
• 6.3 DIAGNOSTICS & SCREENING
  • 6.3.1 RISK ASSESSMENT & PATIENT STRATIFICATION
    • 6.3.1.1 Leveraging AI to personalize treatment plan
  • 6.3.2 DISEASE SCREENING
    • 6.3.2.1 Leveraging machine learning to peruse and resolve complex patient data
  • 6.3.3 DISEASE DIAGNOSIS
    • 6.3.3.1 Identifying biomarkers for precise treatment
  • 6.3.4 DISEASE PROGRESSION, STAGING, AND PROGNOSIS
    • 6.3.4.1 Using AI to track disease conditions
• 6.4 THERAPEUTICS
  • 6.4.1 THERAPY SELECTION & PLANNING
    • 6.4.1.1 Leveraging generative models to predict and design suitable treatment
  • 6.4.2 THERAPY MONITORING
    • 6.4.2.1 Need to effectively track safety and efficacy of treatment
  • 6.4.3 POST-TREATMENT SURVEILLANCE & FOLLOW-UP
    • 6.4.3.1 AI algorithms to identify subtle patterns in data, allowing for early detection of potential issues

7 ARTIFICIAL INTELLIGENCE IN PRECISION MEDICINE MARKET, BY THERAPEUTIC AREA

• 7.1 INTRODUCTION
• 7.2 ONCOLOGY
  • 7.2.1 HIGH PREVALENCE OF CANCER AND SHORTAGE OF EFFECTIVE CANCER DRUGS
• 7.3 RARE DISEASES
  • 7.3.1 COMBATING CHALLENGING THERAPEUTICS DUE TO COMPLEX AND HETEROGENEOUS NATURE OF RARE DISEASES
• 7.4 INFECTIOUS DISEASES
  • 7.4.1 NEED FOR INNOVATION IN INFECTIOUS DISEASE TREATMENT, ESPECIALLY AFTER IMPACT OF COVID-19
• 7.5 NEUROLOGY
  • 7.5.1 SHORTAGE AND COMPLEXITY OF NEURODEGENERATIVE DISEASES
• 7.6 CARDIOLOGY
  • 7.6.1 WIDE RANGE AND INCIDENCE OF CARDIOVASCULAR DISEASES
• 7.7 HEMATOLOGY
  • 7.7.1 AI-DRIVEN ALGORITHMS TO ANALYZE BLOOD SAMPLES, IMAGING DATA, AND GENOMIC PROFILES TO DETECT ABNORMALITIES
• 7.8 OTHER THERAPEUTIC AREAS

8 ARTIFICIAL INTELLIGENCE IN PRECISION MEDICINE MARKET, BY COMPONENT

• 8.1 INTRODUCTION
• 8.2 SOFTWARE
  • 8.2.1 SCALABILITY AND FLEXIBILITY OF AI SOFTWARE TO ENHANCE EFFICIENCY OF CLINICAL WORKFLOWS
• 8.3 SERVICES
  • 8.3.1 NEED FOR EXPERT ASSISTANCE AMONG HEALTHCARE ORGANIZATIONS IN ADOPTING AND OPTIMIZING AI TECHNOLOGIES

9 AI IN PRECISION MEDICINE MARKET, BY TOOL

• 9.1 INTRODUCTION
• 9.2 MACHINE LEARNING
  • 9.2.1 DEEP LEARNING
    • 9.2.1.1 Convolutional neural networks
      • 9.2.1.1.1 Interpreting complex biological data to enable personalizing healthcare
    • 9.2.1.2 Recurrent neural networks (RNNs)
      • 9.2.1.2.1 Optimizing clinical data to model patient trajectories by analyzing longitudinal data
    • 9.2.1.3 Generative adversarial networks (GANs)
      • 9.2.1.3.1 GAN to focus on new molecules and biological datasets
    • 9.2.1.4 Graph neural networks (GNNs)
      • 9.2.1.4.1 Predicting drug-drug interactions to optimize personalized treatment
    • 9.2.1.5 Other deep learning tools
  • 9.2.2 SUPERVISED MACHINE LEARNING
  • 9.2.3 REINFORCEMENT MACHINE LEARNING
  • 9.2.4 UNSUPERVISED MACHINE LEARNING
  • 9.2.5 OTHER MACHINE LEARNING TOOLS
• 9.3 NATURAL LANGUAGE PROCESSING
  • 9.3.1 ABUNDANCE OF UNSTRUCTURED DATA IN CLINICAL RESEARCH TO BE INTERPRETED
• 9.4 CONTEXT-AWARE PROCESSING & COMPUTING
  • 9.4.1 TAILORING PATIENT CARE IN REAL TIME TO ENHANCE PRECISION MEDICINE
• 9.5 COMPUTER VISION
  • 9.5.1 INCREASE IN USE OF IMAGING BIOMARKERS TO SUPPORT SURGICAL PRECISION
• 9.6 IMAGE ANALYSIS
  • 9.6.1 HARNESSING MACHINE LEARNING TO AUTOMATE TECHNIQUES SUCH AS QUANTITATIVE IMAGING AND RADIOMICS
• 9.7 OTHER TOOLS

10 ARTIFICIAL INTELLIGENCE IN PRECISION MEDICINE MARKET, BY DEPLOYMENT

• 10.1 INTRODUCTION
• 10.2 CLOUD-BASED MODEL
  • 10.2.1 RESEARCH COLLABORATION AND COST-EFFICIENCY OF CLOUD DEPLOYMENT
• 10.3 ON-PREMISE MODEL
  • 10.3.1 EASIER TO SECURE PATIENT DATA AND ENSURE COMPLIANCE IN ON-PREMISE AI-DRIVEN PRECISION MEDICINE
• 10.4 HYBRID MODEL
  • 10.4.1 HYBRID MODELS TO ENHANCE FLEXIBILITY AND SECURITY

11 ARTIFICIAL INTELLIGENCE IN PRECISION MEDICINE MARKET, BY END USER

• 11.1 INTRODUCTION
• 11.2 HEALTHCARE PROVIDERS
  • 11.2.1 REVOLUTIONIZING PATIENT CARE AND TREATMENT DELIVERY THROUGH ADVANCED TECHNOLOGIES
• 11.3 PHARMACEUTICAL & BIOTECHNOLOGY COMPANIES
  • 11.3.1 DRIVING DRUG DEVELOPMENT EFFICIENCY TO DESIGN ADAPTIVE TRIAL PROTOCOLS AND OPTIMIZE TREATMENT
• 11.4 MEDICAL DEVICE & EQUIPMENT COMPANIES
  • 11.4.1 INTEGRATION OF AI IN MEDICAL DEVICES TO ENHANCE PRECISION AND PERSONALIZED HEALTHCARE
• 11.5 RESEARCH CENTERS, ACADEMIC INSTITUTES, AND GOVERNMENT ORGANIZATIONS
  • 11.5.1 AI IN ACADEMIC INSTITUTES AND PUBLIC SECTOR COLLABORATIONS TO ACCELERATE INNOVATION AND RESEARCH
• 11.6 OTHER END USERS

12 ARTIFICIAL INTELLIGENCE IN PRECISION MEDICINE MARKET, BY REGION

• 12.1 INTRODUCTION
• 12.2 NORTH AMERICA
  • 12.2.1 NORTH AMERICA: MACROECONOMIC OUTLOOK
  • 12.2.2 US
    • 12.2.2.1 US to dominate North American market with advanced regulatory system
  • 12.2.3 CANADA
    • 12.2.3.1 Emergence of new AI-based startups and high health expenditure
• 12.3 EUROPE
  • 12.3.1 EUROPE: MACROECONOMIC OUTLOOK
  • 12.3.2 UK
    • 12.3.2.1 Favorable government R&D investment and collaborations focused on drug discovery
  • 12.3.3 GERMANY
    • 12.3.3.1 Growing R&D investment by pharma and biotech companies
  • 12.3.4 FRANCE
    • 12.3.4.1 Strong government support through investments in initiatives
  • 12.3.5 ITALY
    • 12.3.5.1 Government Initiatives addressing local healthcare challenges through studies aimed at broader precision medicine strategies
  • 12.3.6 SPAIN
    • 12.3.6.1 High investments by pharmaceutical companies
  • 12.3.7 REST OF EUROPE
• 12.4 ASIA PACIFIC
  • 12.4.1 ASIA PACIFIC: MACROECONOMIC OUTLOOK
  • 12.4.2 JAPAN
    • 12.4.2.1 High investment in R&D and government initiatives focused on treatment outcomes
  • 12.4.3 CHINA
    • 12.4.3.1 Government funding to advance data analysis and international collaborations to develop targeted therapies
  • 12.4.4 INDIA
    • 12.4.4.1 High growth of pharmaceutical and medical device industries
  • 12.4.5 REST OF ASIA PACIFIC
• 12.5 LATIN AMERICA
  • 12.5.1 LATIN AMERICA: MACROECONOMIC OUTLOOK
  • 12.5.2 BRAZIL
    • 12.5.2.1 Increase in governmental support through initiatives such as Brazilian Artificial Intelligence Plan
  • 12.5.3 MEXICO
    • 12.5.3.1 High potential to become leader in terms of readiness in technology
  • 12.5.4 REST OF LATIN AMERICA
• 12.6 MIDDLE EAST & AFRICA
  • 12.6.1 MIDDLE EAST & AFRICA: MACROECONOMIC OUTLOOK
  • 12.6.2 GCC COUNTRIES
    • 12.6.2.1 Increasing emphasis on personalized medicines and developing healthcare infrastructure
  • 12.6.3 REST OF MIDDLE EAST & AFRICA

13 COMPETITIVE LANDSCAPE

• 13.1 INTRODUCTION
• 13.2 KEY PLAYER STRATEGY/RIGHT TO WIN
• 13.3 REVENUE ANALYSIS, 2019-2023
• 13.4 MARKET SHARE ANALYSIS, 2023
  • 13.4.1 RANKING OF KEY MARKET PLAYERS
• 13.5 COMPANY EVALUATION MATRIX: KEY PLAYERS, 2023
  • 13.5.1 STARS
  • 13.5.2 EMERGING LEADERS
  • 13.5.3 PERVASIVE PLAYERS
  • 13.5.4 PARTICIPANTS
  • 13.5.5 COMPANY FOOTPRINT: KEY PLAYERS, 2023
    • 13.5.5.1 Company footprint
    • 13.5.5.2 Therapeutic area footprint
    • 13.5.5.3 End user footprint
    • 13.5.5.4 Component footprint
    • 13.5.5.5 Deployment footprint
    • 13.5.5.6 Region footprint
• 13.6 COMPANY EVALUATION MATRIX: STARTUPS/SMES, 2023
  • 13.6.1 PROGRESSIVE COMPANIES
  • 13.6.2 RESPONSIVE COMPANIES
  • 13.6.3 DYNAMIC COMPANIES
  • 13.6.4 STARTING BLOCKS
  • 13.6.5 COMPETITIVE BENCHMARKING: STARTUPS/SMES, 2023
    • 13.6.5.1 Detailed list of key startup/SME players
    • 13.6.5.2 Competitive benchmarking of key emerging players/startups, by region
• 13.7 COMPANY VALUATION AND FINANCIAL METRICS
  • 13.7.1 COMPANY VALUATION
  • 13.7.2 FINANCIAL METRICS
• 13.8 BRAND/PRODUCT COMPARISON
• 13.9 COMPETITIVE SCENARIO
  • 13.9.1 PRODUCT LAUNCHES
  • 13.9.2 DEALS
  • 13.9.3 EXPANSIONS
  • 13.9.4 OTHER DEVELOPMENTS

14 COMPANY PROFILES

• 14.1 KEY PLAYERS
  • 14.1.1 NVIDIA CORPORATION
    • 14.1.1.1 Business overview
    • 14.1.1.2 Products/Services/Solutions offered
    • 14.1.1.3 Recent developments
      • 14.1.1.3.1 Product launches
      • 14.1.1.3.2 Deals
    • 14.1.1.4 MnM view
      • 14.1.1.4.1 Right to win
      • 14.1.1.4.2 Strategic choices
      • 14.1.1.4.3 Weaknesses & competitive threats
  • 14.1.2 EXSCIENTIA
    • 14.1.2.1 Business overview
    • 14.1.2.2 Products/Services/Solutions offered
    • 14.1.2.3 Recent developments
      • 14.1.2.3.1 Product launches
      • 14.1.2.3.2 Deals
      • 14.1.2.3.3 Expansions
      • 14.1.2.3.4 Other developments
    • 14.1.2.4 MnM view
      • 14.1.2.4.1 Right to win
      • 14.1.2.4.2 Strategic choices
      • 14.1.2.4.3 Weaknesses and competitive threats
  • 14.1.3 GOOGLE
    • 14.1.3.1 Business overview
    • 14.1.3.2 Products/Services/Solutions offered
    • 14.1.3.3 Recent developments
      • 14.1.3.3.1 Product launches
      • 14.1.3.3.2 Deals
      • 14.1.3.3.3 Expansions
    • 14.1.3.4 MnM view
      • 14.1.3.4.1 Right to win
      • 14.1.3.4.2 Strategic choices
      • 14.1.3.4.3 Weaknesses and competitive threats
  • 14.1.4 ILLUMINA, INC.
    • 14.1.4.1 Business overview
    • 14.1.4.2 Products/Services/Solutions offered
    • 14.1.4.3 Recent developments
      • 14.1.4.3.1 Product launches
      • 14.1.4.3.2 Deals
    • 14.1.4.4 MnM view
      • 14.1.4.4.1 Right to win
      • 14.1.4.4.2 Strategic choices
      • 14.1.4.4.3 Weaknesses and competitive threats
  • 14.1.5 TEMPUS AI, INC.
    • 14.1.5.1 Business overview
    • 14.1.5.2 Products/Services/Solutions offered
    • 14.1.5.3 Recent developments
      • 14.1.5.3.1 Product launches
      • 14.1.5.3.2 Deals
      • 14.1.5.3.3 Expansions
      • 14.1.5.3.4 Other developments
    • 14.1.5.4 MnM view
      • 14.1.5.4.1 Right to win
      • 14.1.5.4.2 Strategic choices
      • 14.1.5.4.3 Weaknesses and competitive threats
  • 14.1.6 BENEVOLENTAI
    • 14.1.6.1 Business overview
    • 14.1.6.2 Products/Services/Solutions offered
    • 14.1.6.3 Recent developments
      • 14.1.6.3.1 Deals
  • 14.1.7 MICROSOFT CORPORATION
    • 14.1.7.1 Business overview
    • 14.1.7.2 Products/Services/Solutions offered
    • 14.1.7.3 Recent developments
      • 14.1.7.3.1 Deals
  • 14.1.8 IBM
    • 14.1.8.1 Business overview
    • 14.1.8.2 Products/Services/Solutions offered
    • 14.1.8.3 Recent developments
      • 14.1.8.3.1 Deals
  • 14.1.9 GE HEALTHCARE
    • 14.1.9.1 Business overview
    • 14.1.9.2 Products/Services/Solutions offered
    • 14.1.9.3 Recent developments
      • 14.1.9.3.1 Product launches
      • 14.1.9.3.2 Deals
      • 14.1.9.3.3 Other developments
  • 14.1.10 DEEP GENOMICS
    • 14.1.10.1 Business overview
    • 14.1.10.2 Products/Services/Solutions offered
    • 14.1.10.3 Recent developments
      • 14.1.10.3.1 Product launches
      • 14.1.10.3.2 Deals
      • 14.1.10.3.3 Other developments
  • 14.1.11 SIEMENS HEALTHINEERS AG
    • 14.1.11.1 Business overview
    • 14.1.11.2 Products/Solutions/Services offered
    • 14.1.11.3 Recent developments
      • 14.1.11.3.1 Deals
  • 14.1.12 BIOXCEL THERAPEUTICS, INC.
    • 14.1.12.1 Business overview
    • 14.1.12.2 Products/Solutions/Services offered
    • 14.1.12.3 Recent developments
      • 14.1.12.3.1 Deals
      • 14.1.12.3.2 Other developments
  • 14.1.13 INSILICO MEDICINE
    • 14.1.13.1 Business overview
    • 14.1.13.2 Products/Services/Solutions offered
    • 14.1.13.3 Recent developments
      • 14.1.13.3.1 Product launches
      • 14.1.13.3.2 Deals
      • 14.1.13.3.3 Other developments
  • 14.1.14 PATHAI, INC.
    • 14.1.14.1 Business overview
    • 14.1.14.2 Products/Services/Solutions offered
    • 14.1.14.3 Recent developments
      • 14.1.14.3.1 Product launches
      • 14.1.14.3.2 Deals
      • 14.1.14.3.3 Other developments
  • 14.1.15 VERGE GENOMICS
    • 14.1.15.1 Business overview
    • 14.1.15.2 Products/Services/Solutions offered
    • 14.1.15.3 Recent developments
      • 14.1.15.3.1 Deals
  • 14.1.16 GUARDANT HEALTH, INC.
    • 14.1.16.1 Business overview
    • 14.1.16.2 Products/Services/Solutions offered
    • 14.1.16.3 Recent developments
      • 14.1.16.3.1 Product launches
      • 14.1.16.3.2 Deals
      • 14.1.16.3.3 Other developments
  • 14.1.17 GRAIL, INC.
    • 14.1.17.1 Business overview
    • 14.1.17.2 Products/Services/Solutions offered
    • 14.1.17.3 Recent developments
      • 14.1.17.3.1 Deals
  • 14.1.18 FOUNDATION MEDICINE, INC.
    • 14.1.18.1 Business overview
    • 14.1.18.2 Products/Services/Solutions offered
    • 14.1.18.3 Recent developments
      • 14.1.18.3.1 Deals
      • 14.1.18.3.2 Other developments
  • 14.1.19 PROSCIA INC.
    • 14.1.19.1 Business overview
    • 14.1.19.2 Products/Services/Solutions offered
    • 14.1.19.3 Recent developments
      • 14.1.19.3.1 Product launches
      • 14.1.19.3.2 Deals
      • 14.1.19.3.3 Other developments
  • 14.1.20 FLATIRON HEALTH
    • 14.1.20.1 Business overview
    • 14.1.20.2 Products/Services/Solutions offered
    • 14.1.20.3 Recent developments
      • 14.1.20.3.1 Deals
      • 14.1.20.3.2 Other developments
• 14.2 OTHER PLAYERS
  • 14.2.1 PREDICTIVE ONCOLOGY
  • 14.2.2 PAIGE AI, INC.
  • 14.2.3 DENSITAS INC.
  • 14.2.4 ZEPHYR AI, INC.
  • 14.2.5 NUCLEAI, INC.

15 APPENDIX

• 15.1 DISCUSSION GUIDE
• 15.2 KNOWLEDGESTORE: MARKETSANDMARKETS' SUBSCRIPTION PORTAL
• 15.3 CUSTOMIZATION OPTIONS
• 15.4 RELATED REPORTS
• 15.5 AUTHOR DETAILS