Summary

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

ページTOPに戻る

Table of Contents

1 INTRODUCTION 32
1.1 STUDY OBJECTIVES 32
1.2 MARKET DEFINITION 32
1.3 STUDY SCOPE 33
1.3.1 MARKETS COVERED & REGIONAL SCOPE 33
1.3.2 INCLUSIONS & EXCLUSIONS 34
1.3.3 YEARS CONSIDERED 36
1.4 CURRENCY CONSIDERED 36
1.5 STAKEHOLDERS 36
2 RESEARCH METHODOLOGY 38
2.1 RESEARCH DATA 38
2.1.1 SECONDARY DATA 39
2.1.1.1 Key data from secondary sources 40
2.1.2 PRIMARY DATA 40
2.1.2.1 Key data from primary sources 42
2.2 MARKET SIZE ESTIMATION 44
2.3 MARKET SHARE ESTIMATION 47
2.4 DATA TRIANGULATION 48
2.5 RESEARCH ASSUMPTIONS 49
2.6 LIMITATIONS 49
2.6.1 METHODOLOGY-RELATED LIMITATIONS 49
2.6.2 SCOPE-RELATED LIMITATIONS 49
2.7 RISK ASSESSMENT 50
3 EXECUTIVE SUMMARY 51
4 PREMIUM INSIGHTS 57
4.1 ARTIFICIAL INTELLIGENCE IN PRECISION MEDICINE MARKET OVERVIEW 57
4.2 ARTIFICIAL INTELLIGENCE IN PRECISION MEDICINE MARKET, BY REGION 58
4.3 NORTH AMERICA: ARTIFICIAL INTELLIGENCE IN PRECISION MEDICINE MARKET, BY END USER & REGION 59
4.4 ARTIFICIAL INTELLIGENCE IN PRECISION MEDICINE MARKET: GEOGRAPHIC SNAPSHOT 60
4.5 ARTIFICIAL INTELLIGENCE IN PRECISION MEDICINE MARKET: DEVELOPED VS. EMERGING MARKETS 60
 
5 MARKET OVERVIEW 61
5.1 INTRODUCTION 61
5.2 MARKET DYNAMICS 61
5.3 MARKET DYNAMICS 62
5.3.1 DRIVERS 62
5.3.1.1 Increase in investments in R&D and rise in demand for personalized medication 62
5.3.1.2 Advancements in genomic research and data availability 64
5.3.1.3 Growth in cross-industry collaborations and partnerships 64
5.3.1.4 Role of regulatory landscape in driving AI adoption in healthcare 66
5.3.2 RESTRAINTS 68
5.3.2.1 Increase in data breach concerns 68
5.3.2.2 High cost of implementation of precision medicine solutions 70
5.3.2.3 Accuracy challenges in AI adoption for healthcare 71
5.3.3 OPPORTUNITIES 71
5.3.3.1 Role of predictive analytics in advancing AI for healthcare 71
5.3.3.2 Leveraging research pipelines and new drug development for AI in healthcare 72
5.3.4 CHALLENGES 73
5.3.4.1 Impact of fairness and bias on AI in healthcare 73
5.3.4.2 Interoperability challenges due to complexity of AI solutions 74
5.4 TRENDS/DISRUPTIONS IMPACTING CUSTOMER BUSINESSES 74
5.5 INDUSTRY TRENDS 75
5.5.1 AI'S GROWING ROLE IN PATIENT-SPECIFIC DATA INTEGRATION AND ANALYSIS 75
5.5.2 ADVANCEMENTS IN AI-POWERED PREDICTIVE ANALYTICS FOR TREATMENT OPTIMIZATION 76
5.6 ECOSYSTEM ANALYSIS 76
5.7 VALUE CHAIN ANALYSIS 79
5.8 TECHNOLOGY ANALYSIS 80
5.8.1 KEY TECHNOLOGIES 80
5.8.1.1 Predictive analytics 80
5.8.1.2 Neural networks 81
5.8.1.3 Knowledge graphs 81
5.8.1.4 Cell and gene therapies 81
5.8.1.5 AI-driven single-cell analysis 82
5.8.2 COMPLEMENTARY TECHNOLOGY 82
5.8.2.1 High-performance computing (HPC) 82
5.8.2.2 Next-generation sequencing 82
5.8.2.3 Real-world evidence/Real-world data 83
5.8.2.4 EHR Integration 83
5.8.2.5 Digital health platforms 84
 
5.8.3 ADJACENT TECHNOLOGIES 84
5.8.3.1 Cloud computing 84
5.8.3.2 Blockchain technology 84
5.8.3.3 Internet of Things (IoT) and wearables 85
5.8.3.4 Robotics and automation 85
5.8.3.5 3D printing for personalized implants and devices 85
5.9 REGULATORY ANALYSIS 86
5.9.1 REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS 86
5.9.2 REGULATORY SCENARIO 89
5.10 PRICING ANALYSIS 93
5.10.1 INDICATIVE PRICING FOR KEY PLAYERS 93
5.10.2 INDICATIVE PRICE OF KEY COMPONENTS, BY REGION 94
5.11 PORTER’S FIVE FORCES ANALYSIS 95
5.11.1 THREAT OF NEW ENTRANTS 96
5.11.2 THREAT OF SUBSTITUTES 96
5.11.3 BARGAINING POWER OF SUPPLIERS 96
5.11.4 BARGAINING POWER OF BUYERS 97
5.11.5 INTENSITY OF COMPETITIVE RIVALRY 97
5.12 PATENT ANALYSIS 97
5.12.1 PATENT PUBLICATION TRENDS 97
5.12.2 JURISDICTION ANALYSIS: TOP APPLICANT COUNTRIES FOR AI IN PRECISION MEDICINE 98
5.12.3 KEY PATENTS IN AI IN PRECISION MEDICINE MARKET 99
5.13 KEY STAKEHOLDERS AND BUYING CRITERIA 102
5.13.1 KEY STAKEHOLDERS IN BUYING PROCESS 102
5.13.2 KEY BUYING CRITERIA 103
5.14 END-USER ANALYSIS 104
5.14.1 UNMET NEEDS 104
5.14.2 END-USER EXPECTATIONS 105
5.15 KEY CONFERENCES & EVENTS 106
5.16 CASE STUDY ANALYSIS 107
5.16.1 SANOFI LEVERAGED AI-DRIVEN PRECISION MEDICINE TO IDENTIFY PATIENT SUBTYPES AND NOVEL TARGETS IN INFLAMMATORY BOWEL DISEASE 107
5.16.2 IBM’S AI-DRIVEN SOLUTION IMPROVED CLINICAL TRIAL ENROLLMENT AT MAYO CLINIC BY ENHANCING PATIENT MATCHING 108
5.16.3 ENHANCING PATIENT IDENTIFICATION FOR RARE ONCOLOGY BIOMARKERS THROUGH GENOMIC TESTING AND STRATEGIC COLLABORATION 108
5.17 INVESTMENT AND FUNDING SCENARIO 109
5.18 BUSINESS MODELS 109
5.19 IMPACT OF AI/GEN AI IN PRECISION MEDICINE MARKET 111
5.19.1 KEY USE CASES 112
5.19.2 CASE STUDIES OF AI/GENERATIVE AI IMPLEMENTATION 112
5.19.2.1 Enhancing patient outcomes with AI-driven predictive analytics at Johns Hopkins Hospital 112
5.19.3 IMPACT OF AI/GEN AI ON INTERCONNECTED AND ADJACENT ECOSYSTEMS 113
5.19.3.1 AI in drug discovery market 113
5.19.3.2 Genomics market 113
5.19.3.3 Artificial intelligence market 114
5.19.3.4 Pharmacogenomics market 114
5.19.4 USER READINESS AND IMPACT ASSESSMENT 114
5.19.4.1 User readiness 114
5.19.4.1.1 Healthcare providers 114
5.19.4.1.2 Pharmaceutical & biotechnology companies 114
6 ARTIFICIAL INTELLIGENCE IN PRECISION MEDICINE MARKET,
BY APPLICATION 115
6.1 INTRODUCTION 116
6.2 DRUG DISCOVERY & DEVELOPMENT 116
6.2.1 DRUG DISCOVERY 117
6.2.2 UNDERSTANDING DISEASES 117
6.2.2.1 Rise in data mining to link targets to diseases 117
6.2.3 DRUG REPURPOSING 118
6.2.3.1 Use of graphs for targeted approach to reduce timelines and costs 118
6.2.4 DE NOVO DRUG DESIGN 119
6.2.4.1 Availability of large-scale biomedical datasets and urgent demand for novel treatments for complex diseases 119
6.2.5 DRUG OPTIMIZATION 120
6.2.5.1 Need to process extensive data on molecular properties, target interactions, and clinical outcomes 120
6.2.6 SAFETY & TOXICITY 121
6.2.6.1 Building generalizable model for toxicity and off-target effect prediction 121
6.2.7 CLINICAL DEVELOPMENT 122
6.2.7.1 Designing and conducting clinical trials for personalized dosing, targeted therapies 122
6.3 DIAGNOSTICS & SCREENING 124
6.3.1 RISK ASSESSMENT & PATIENT STRATIFICATION 124
6.3.1.1 Leveraging AI to personalize treatment plan 124
6.3.2 DISEASE SCREENING 125
6.3.2.1 Leveraging machine learning to peruse and resolve complex patient data 125
6.3.3 DISEASE DIAGNOSIS 126
6.3.3.1 Identifying biomarkers for precise treatment 126
6.3.4 DISEASE PROGRESSION, STAGING, AND PROGNOSIS 127
6.3.4.1 Using AI to track disease conditions 127
 
6.4 THERAPEUTICS 128
6.4.1 THERAPY SELECTION & PLANNING 129
6.4.1.1 Leveraging generative models to predict and design suitable treatment 129
6.4.2 THERAPY MONITORING 130
6.4.2.1 Need to effectively track safety and efficacy of treatment 130
6.4.3 POST-TREATMENT SURVEILLANCE & FOLLOW-UP 131
6.4.3.1 AI algorithms to identify subtle patterns in data, allowing for early detection of potential issues 131
7 ARTIFICIAL INTELLIGENCE IN PRECISION MEDICINE MARKET,
BY THERAPEUTIC AREA 133
7.1 INTRODUCTION 134
7.2 ONCOLOGY 134
7.2.1 HIGH PREVALENCE OF CANCER AND SHORTAGE OF EFFECTIVE CANCER DRUGS 134
7.3 RARE DISEASES 136
7.3.1 COMBATING CHALLENGING THERAPEUTICS DUE TO COMPLEX AND HETEROGENEOUS NATURE OF RARE DISEASES 136
7.4 INFECTIOUS DISEASES 137
7.4.1 NEED FOR INNOVATION IN INFECTIOUS DISEASE TREATMENT, ESPECIALLY AFTER IMPACT OF COVID-19 137
7.5 NEUROLOGY 139
7.5.1 SHORTAGE AND COMPLEXITY OF NEURODEGENERATIVE DISEASES 139
7.6 CARDIOLOGY 141
7.6.1 WIDE RANGE AND INCIDENCE OF CARDIOVASCULAR DISEASES 141
7.7 HEMATOLOGY 142
7.7.1 AI-DRIVEN ALGORITHMS TO ANALYZE BLOOD SAMPLES, IMAGING DATA,
AND GENOMIC PROFILES TO DETECT ABNORMALITIES 142
7.8 OTHER THERAPEUTIC AREAS 143
8 ARTIFICIAL INTELLIGENCE IN PRECISION MEDICINE MARKET,
BY COMPONENT 145
8.1 INTRODUCTION 146
8.2 SOFTWARE 146
8.2.1 SCALABILITY AND FLEXIBILITY OF AI SOFTWARE TO ENHANCE EFFICIENCY OF CLINICAL WORKFLOWS 146
8.3 SERVICES 148
8.3.1 NEED FOR EXPERT ASSISTANCE AMONG HEALTHCARE ORGANIZATIONS IN ADOPTING AND OPTIMIZING AI TECHNOLOGIES 148
 
9 AI IN PRECISION MEDICINE MARKET, BY TOOL 150
9.1 INTRODUCTION 151
9.2 MACHINE LEARNING 151
9.2.1 DEEP LEARNING 153
9.2.1.1 Convolutional neural networks 154
9.2.1.1.1 Interpreting complex biological data to enable personalizing healthcare 154
9.2.1.2 Recurrent neural networks (RNNs) 155
9.2.1.2.1 Optimizing clinical data to model patient trajectories by analyzing longitudinal data 155
9.2.1.3 Generative adversarial networks (GANs) 156
9.2.1.3.1 GAN to focus on new molecules and biological datasets 156
9.2.1.4 Graph neural networks (GNNs) 157
9.2.1.4.1 Predicting drug-drug interactions to optimize personalized treatment 157
9.2.1.5 Other deep learning tools 158
9.2.2 SUPERVISED MACHINE LEARNING 158
9.2.3 REINFORCEMENT MACHINE LEARNING 159
9.2.4 UNSUPERVISED MACHINE LEARNING 160
9.2.5 OTHER MACHINE LEARNING TOOLS 161
9.3 NATURAL LANGUAGE PROCESSING 162
9.3.1 ABUNDANCE OF UNSTRUCTURED DATA IN CLINICAL RESEARCH TO BE INTERPRETED 162
9.4 CONTEXT-AWARE PROCESSING & COMPUTING 163
9.4.1 TAILORING PATIENT CARE IN REAL TIME TO ENHANCE PRECISION MEDICINE 163
9.5 COMPUTER VISION 164
9.5.1 INCREASE IN USE OF IMAGING BIOMARKERS TO SUPPORT SURGICAL PRECISION 164
9.6 IMAGE ANALYSIS 165
9.6.1 HARNESSING MACHINE LEARNING TO AUTOMATE TECHNIQUES SUCH AS QUANTITATIVE IMAGING AND RADIOMICS 165
9.7 OTHER TOOLS 166
10 ARTIFICIAL INTELLIGENCE IN PRECISION MEDICINE MARKET,
BY DEPLOYMENT 168
10.1 INTRODUCTION 169
10.2 CLOUD-BASED MODEL 169
10.2.1 RESEARCH COLLABORATION AND COST-EFFICIENCY OF CLOUD DEPLOYMENT 169
10.3 ON-PREMISE MODEL 171
10.3.1 EASIER TO SECURE PATIENT DATA AND ENSURE COMPLIANCE IN ON-PREMISE AI-DRIVEN PRECISION MEDICINE 171
10.4 HYBRID MODEL 172
10.4.1 HYBRID MODELS TO ENHANCE FLEXIBILITY AND SECURITY 172
11 ARTIFICIAL INTELLIGENCE IN PRECISION MEDICINE MARKET, BY END USER 174
11.1 INTRODUCTION 175
11.2 HEALTHCARE PROVIDERS 175
11.2.1 REVOLUTIONIZING PATIENT CARE AND TREATMENT DELIVERY THROUGH ADVANCED TECHNOLOGIES 175
11.3 PHARMACEUTICAL & BIOTECHNOLOGY COMPANIES 176
11.3.1 DRIVING DRUG DEVELOPMENT EFFICIENCY TO DESIGN ADAPTIVE TRIAL PROTOCOLS AND OPTIMIZE TREATMENT 176
11.4 MEDICAL DEVICE & EQUIPMENT COMPANIES 177
11.4.1 INTEGRATION OF AI IN MEDICAL DEVICES TO ENHANCE PRECISION AND PERSONALIZED HEALTHCARE 177
11.5 RESEARCH CENTERS, ACADEMIC INSTITUTES, AND GOVERNMENT ORGANIZATIONS 178
11.5.1 AI IN ACADEMIC INSTITUTES AND PUBLIC SECTOR COLLABORATIONS TO ACCELERATE INNOVATION AND RESEARCH 178
11.6 OTHER END USERS 179
12 ARTIFICIAL INTELLIGENCE IN PRECISION MEDICINE MARKET, BY REGION 181
12.1 INTRODUCTION 182
12.2 NORTH AMERICA 182
12.2.1 NORTH AMERICA: MACROECONOMIC OUTLOOK 183
12.2.2 US 187
12.2.2.1 US to dominate North American market with advanced regulatory system 187
12.2.3 CANADA 190
12.2.3.1 Emergence of new AI-based startups and high health expenditure 190
12.3 EUROPE 194
12.3.1 EUROPE: MACROECONOMIC OUTLOOK 194
12.3.2 UK 198
12.3.2.1 Favorable government R&D investment and collaborations focused on drug discovery 198
12.3.3 GERMANY 201
12.3.3.1 Growing R&D investment by pharma and biotech companies 201
12.3.4 FRANCE 204
12.3.4.1 Strong government support through investments in initiatives 204
12.3.5 ITALY 208
12.3.5.1 Government Initiatives addressing local healthcare challenges through studies aimed at broader precision medicine strategies 208
12.3.6 SPAIN 211
12.3.6.1 High investments by pharmaceutical companies 211
12.3.7 REST OF EUROPE 214
12.4 ASIA PACIFIC 217
12.4.1 ASIA PACIFIC: MACROECONOMIC OUTLOOK 217
12.4.2 JAPAN 222
12.4.2.1 High investment in R&D and government initiatives focused on treatment outcomes 222
12.4.3 CHINA 226
12.4.3.1 Government funding to advance data analysis and international collaborations to develop targeted therapies 226
12.4.4 INDIA 229
12.4.4.1 High growth of pharmaceutical and medical device industries 229
12.4.5 REST OF ASIA PACIFIC 233
12.5 LATIN AMERICA 236
12.5.1 LATIN AMERICA: MACROECONOMIC OUTLOOK 236
12.5.2 BRAZIL 240
12.5.2.1 Increase in governmental support through initiatives such as Brazilian Artificial Intelligence Plan 240
12.5.3 MEXICO 243
12.5.3.1 High potential to become leader in terms of readiness in technology 243
12.5.4 REST OF LATIN AMERICA 246
12.6 MIDDLE EAST & AFRICA 249
12.6.1 MIDDLE EAST & AFRICA: MACROECONOMIC OUTLOOK 249
12.6.2 GCC COUNTRIES 253
12.6.2.1 Increasing emphasis on personalized medicines and developing healthcare infrastructure 253
12.6.3 REST OF MIDDLE EAST & AFRICA 257
13 COMPETITIVE LANDSCAPE 261
13.1 INTRODUCTION 261
13.2 KEY PLAYER STRATEGY/RIGHT TO WIN 261
13.3 REVENUE ANALYSIS, 2019–2023 264
13.4 MARKET SHARE ANALYSIS, 2023 265
13.4.1 RANKING OF KEY MARKET PLAYERS 267
13.5 COMPANY EVALUATION MATRIX: KEY PLAYERS, 2023 268
13.5.1 STARS 268
13.5.2 EMERGING LEADERS 268
13.5.3 PERVASIVE PLAYERS 268
13.5.4 PARTICIPANTS 268
13.5.5 COMPANY FOOTPRINT: KEY PLAYERS, 2023 270
13.5.5.1 Company footprint 270
13.5.5.2 Therapeutic area footprint 271
13.5.5.3 End user footprint 272
13.5.5.4 Component footprint 273
13.5.5.5 Deployment footprint 274
13.5.5.6 Region footprint 275
 
13.6 COMPANY EVALUATION MATRIX: STARTUPS/SMES, 2023 276
13.6.1 PROGRESSIVE COMPANIES 276
13.6.2 RESPONSIVE COMPANIES 276
13.6.3 DYNAMIC COMPANIES 276
13.6.4 STARTING BLOCKS 276
13.6.5 COMPETITIVE BENCHMARKING: STARTUPS/SMES, 2023 278
13.6.5.1 Detailed list of key startup/SME players 278
13.6.5.2 Competitive benchmarking of key emerging players/startups, by region 279
13.7 COMPANY VALUATION AND FINANCIAL METRICS 279
13.7.1 COMPANY VALUATION 279
13.7.2 FINANCIAL METRICS 280
13.8 BRAND/PRODUCT COMPARISON 281
13.9 COMPETITIVE SCENARIO 282
13.9.1 PRODUCT LAUNCHES 282
13.9.2 DEALS 283
13.9.3 EXPANSIONS 285
13.9.4 OTHER DEVELOPMENTS 286
14 COMPANY PROFILES 287
14.1 KEY PLAYERS 287
14.1.1 NVIDIA CORPORATION 287
14.1.1.1 Business overview 287
14.1.1.2 Products/Services/Solutions offered 289
14.1.1.3 Recent developments 289
14.1.1.3.1 Product launches 289
14.1.1.3.2 Deals 291
14.1.1.4 MnM view 295
14.1.1.4.1 Right to win 295
14.1.1.4.2 Strategic choices 295
14.1.1.4.3 Weaknesses & competitive threats 295
14.1.2 EXSCIENTIA 296
14.1.2.1 Business overview 296
14.1.2.2 Products/Services/Solutions offered 297
14.1.2.3 Recent developments 298
14.1.2.3.1 Product launches 298
14.1.2.3.2 Deals 298
14.1.2.3.3 Expansions 303
14.1.2.3.4 Other developments 304
14.1.2.4 MnM view 305
14.1.2.4.1 Right to win 305
14.1.2.4.2 Strategic choices 305
14.1.2.4.3 Weaknesses and competitive threats 306
14.1.3 GOOGLE 307
14.1.3.1 Business overview 307
14.1.3.2 Products/Services/Solutions offered 309
14.1.3.3 Recent developments 309
14.1.3.3.1 Product launches 309
14.1.3.3.2 Deals 310
14.1.3.3.3 Expansions 311
14.1.3.4 MnM view 311
14.1.3.4.1 Right to win 311
14.1.3.4.2 Strategic choices 311
14.1.3.4.3 Weaknesses and competitive threats 312
14.1.4 ILLUMINA, INC. 313
14.1.4.1 Business overview 313
14.1.4.2 Products/Services/Solutions offered 314
14.1.4.3 Recent developments 315
14.1.4.3.1 Product launches 315
14.1.4.3.2 Deals 316
14.1.4.4 MnM view 317
14.1.4.4.1 Right to win 317
14.1.4.4.2 Strategic choices 317
14.1.4.4.3 Weaknesses and competitive threats 317
14.1.5 TEMPUS AI, INC. 318
14.1.5.1 Business overview 318
14.1.5.2 Products/Services/Solutions offered 318
14.1.5.3 Recent developments 319
14.1.5.3.1 Product launches 319
14.1.5.3.2 Deals 320
14.1.5.3.3 Expansions 323
14.1.5.3.4 Other developments 324
14.1.5.4 MnM view 324
14.1.5.4.1 Right to win 324
14.1.5.4.2 Strategic choices 324
14.1.5.4.3 Weaknesses and competitive threats 324
14.1.6 BENEVOLENTAI 325
14.1.6.1 Business overview 325
14.1.6.2 Products/Services/Solutions offered 326
14.1.6.3 Recent developments 326
14.1.6.3.1 Deals 326
14.1.7 MICROSOFT CORPORATION 329
14.1.7.1 Business overview 329
14.1.7.2 Products/Services/Solutions offered 331
14.1.7.3 Recent developments 331
14.1.7.3.1 Deals 331
14.1.8 IBM 334
14.1.8.1 Business overview 334
14.1.8.2 Products/Services/Solutions offered 336
14.1.8.3 Recent developments 336
14.1.8.3.1 Deals 336
14.1.9 GE HEALTHCARE 337
14.1.9.1 Business overview 337
14.1.9.2 Products/Services/Solutions offered 338
14.1.9.3 Recent developments 339
14.1.9.3.1 Product launches 339
14.1.9.3.2 Deals 340
14.1.9.3.3 Other developments 341
14.1.10 DEEP GENOMICS 342
14.1.10.1 Business overview 342
14.1.10.2 Products/Services/Solutions offered 342
14.1.10.3 Recent developments 343
14.1.10.3.1 Product launches 343
14.1.10.3.2 Deals 343
14.1.10.3.3 Other developments 343
14.1.11 SIEMENS HEALTHINEERS AG 344
14.1.11.1 Business overview 344
14.1.11.2 Products/Solutions/Services offered 345
14.1.11.3 Recent developments 346
14.1.11.3.1 Deals 346
14.1.12 BIOXCEL THERAPEUTICS, INC. 347
14.1.12.1 Business overview 347
14.1.12.2 Products/Solutions/Services offered 347
14.1.12.3 Recent developments 348
14.1.12.3.1 Deals 348
14.1.12.3.2 Other developments 348
14.1.13 INSILICO MEDICINE 349
14.1.13.1 Business overview 349
14.1.13.2 Products/Services/Solutions offered 350
14.1.13.3 Recent developments 350
14.1.13.3.1 Product launches 350
14.1.13.3.2 Deals 352
14.1.13.3.3 Other developments 356
14.1.14 PATHAI, INC. 358
14.1.14.1 Business overview 358
14.1.14.2 Products/Services/Solutions offered 359
14.1.14.3 Recent developments 360
14.1.14.3.1 Product launches 360
14.1.14.3.2 Deals 362
14.1.14.3.3 Other developments 364
14.1.15 VERGE GENOMICS 365
14.1.15.1 Business overview 365
14.1.15.2 Products/Services/Solutions offered 365
14.1.15.3 Recent developments 366
14.1.15.3.1 Deals 366
14.1.16 GUARDANT HEALTH, INC. 367
14.1.16.1 Business overview 367
14.1.16.2 Products/Services/Solutions offered 368
14.1.16.3 Recent developments 369
14.1.16.3.1 Product launches 369
14.1.16.3.2 Deals 370
14.1.16.3.3 Other developments 372
14.1.17 GRAIL, INC. 374
14.1.17.1 Business overview 374
14.1.17.2 Products/Services/Solutions offered 374
14.1.17.3 Recent developments 375
14.1.17.3.1 Deals 375
14.1.18 FOUNDATION MEDICINE, INC. 377
14.1.18.1 Business overview 377
14.1.18.2 Products/Services/Solutions offered 377
14.1.18.3 Recent developments 378
14.1.18.3.1 Deals 378
14.1.18.3.2 Other developments 380
14.1.19 PROSCIA INC. 382
14.1.19.1 Business overview 382
14.1.19.2 Products/Services/Solutions offered 382
14.1.19.3 Recent developments 383
14.1.19.3.1 Product launches 383
14.1.19.3.2 Deals 383
14.1.19.3.3 Other developments 384
14.1.20 FLATIRON HEALTH 385
14.1.20.1 Business overview 385
14.1.20.2 Products/Services/Solutions offered 385
14.1.20.3 Recent developments 386
14.1.20.3.1 Deals 386
14.1.20.3.2 Other developments 387
 
14.2 OTHER PLAYERS 388
14.2.1 PREDICTIVE ONCOLOGY 388
14.2.2 PAIGE AI, INC. 389
14.2.3 DENSITAS INC. 390
14.2.4 ZEPHYR AI, INC. 391
14.2.5 NUCLEAI, INC. 392
15 APPENDIX 393
15.1 DISCUSSION GUIDE 393
15.2 KNOWLEDGESTORE: MARKETSANDMARKETS’ SUBSCRIPTION PORTAL 399
15.3 CUSTOMIZATION OPTIONS 401
15.4 RELATED REPORTS 401
15.5 AUTHOR DETAILS 402