Product Code: HIT 9224
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.
Scope of the Report |
Years Considered for the Study | 2022-2030 |
Base Year | 2023 |
Forecast Period | 2024-2030 |
Units Considered | Value (USD Million) |
Segments | By Application, Therapeutic Area, Component, Tools, Deployment, End User |
Regions covered | North America, Europe, Asia Pacific, Latin America, and Middle East Africa. |
"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
- 14.1.7 MICROSOFT CORPORATION
- 14.1.7.1 Business overview
- 14.1.7.2 Products/Services/Solutions offered
- 14.1.7.3 Recent developments
- 14.1.8 IBM
- 14.1.8.1 Business overview
- 14.1.8.2 Products/Services/Solutions offered
- 14.1.8.3 Recent developments
- 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
- 14.1.12 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
- 14.1.16 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
- 14.1.18 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