Summary

The AI in drug discovery market is anticipated to grow from USD 5.09 billion in 2026 to USD 17.56 billion by 2031, at a CAGR of 28.1% during the forecast period. The market is driven by the increasing adoption of AI to improve R&D productivity, expanding use of multimodal biological datasets, and growing investments in precision medicine and computational drug discovery. According to a 2025 review published in Drug Discovery Today, declining pharmaceutical R&D productivity continues to reshape innovation strategies across the biopharmaceutical industry, prompting companies to increasingly adopt AI-driven platforms to improve research efficiency and accelerate drug discovery. However, challenges related to data quality, model validation, regulatory uncertainty, and integration with existing pharmaceutical R&D workflows continue to influence the pace of market adoption.

Machine learning to be the fastest-growing AI tool segment between 2026 and 2031
By AI tool, the machine learning segment is expected to register the fastest growth during the forecast period as pharmaceutical companies increasingly leverage predictive algorithms to improve decision-making across the drug discovery workflow. Machine learning enables rapid analysis of complex biological, chemical, and clinical datasets, significantly enhancing target identification, hit prioritization, molecular property prediction, and lead optimization. Continuous advancements in deep learning, graph neural networks, and generative AI have further expanded the application of machine learning across small molecule discovery, biologics development, and precision medicine research. Reflecting this trend, in March 2026, NVIDIA expanded its BioNeMo platform with next-generation foundation models and agentic AI capabilities to accelerate biomolecular research and molecular design. As pharmaceutical companies continue to prioritize faster drug development and improved R&D efficiency, machine learning is expected to remain the fastest-growing technology segment in the AI in drug discovery market.

Oncology segment accounted for the largest share of the AI in drug discovery market in 2025
By therapeutic area, the oncology segment accounted for the largest share of the AI in drug discovery market in 2025 due to the high global cancer burden, extensive oncology research pipelines, and increasing demand for precision therapeutics. According to the International Agency for Research on Cancer (IARC), global cancer incidence is projected to increase from 20.6 million new cases in 2024 to 34.4 million by 2050, highlighting the growing need for innovative technologies that can accelerate oncology drug discovery. AI is widely adopted to identify novel therapeutic targets, predict biomarkers, optimize patient stratification, and accelerate the discovery of targeted therapies and immuno-oncology drugs. The availability of large genomic, transcriptomic, proteomic, and clinical datasets has made oncology one of the most data-rich therapeutic areas, enabling AI models to generate more accurate and clinically relevant insights. Pharmaceutical companies continue to prioritize oncology within their R&D portfolios due to its significant commercial potential and the growing demand for personalized cancer therapies. Increasing collaborations between AI companies and oncology-focused biopharmaceutical organizations are further accelerating innovation and reinforcing oncology’s leading position in the AI in drug discovery market.

Europe to exhibit the second-highest CAGR during the forecast period
Europe is expected to register the second-highest growth rate during the forecast period, driven by increasing investments in pharmaceutical innovation, expanding adoption of AI across biomedical research, and a strong regulatory framework supporting trustworthy AI. The region is home to leading pharmaceutical companies, research institutions, and AI-native biotechnology firms that are accelerating the integration of AI into target discovery, molecular design, and precision medicine. The implementation of the European Health Data Space (EHDS) and the EU AI Act is expected to facilitate secure cross-border access to health data while establishing harmonized governance for AI applications in life sciences. In parallel, the proposed Cloud and AI Development Act (CADA) aims to strengthen Europe’s cloud and AI infrastructure by expanding sovereign computing capacity, improving access to high-performance computing resources, and supporting the development of AI innovation across strategic sectors, including healthcare and life sciences. In addition, collaborative programs such as the Innovative Health Initiative (IHI) continue to fund AI-enabled drug discovery projects, including LIGAND-AI, to accelerate therapeutic research through high-quality biological datasets and advanced AI models. Collectively, these initiatives are expected to reinforce its position as the second-fastest-growing regional market for AI in drug discovery.

The breakdown of primary participants is as mentioned below:
・ By Company Type - Tier 1: 32%, Tier 2: 44%, and Tier 3: 24%
・ By Designation - Directors: 30%, Managers: 34%, and Others: 36%
・ By Region - North America: 40%, Europe: 28%, Asia Pacific: 20%, Latin America: 7%, and Middle East & Africa: 5%
Key Players
The key players operating in the AI in drug discovery market include NVIDIA Corporation (US), Schrödinger, Inc. (US), Recursion (US), Insilico Medicine (US), Google (US), Microsoft Corporation (US), Tempus AI, Inc. (US), Illumina, Inc. (US), XtalPi Inc. (China), and Iktos (France). These companies have adopted strategies such as strategic partnerships, collaborations, product launches, platform enhancements, investments in foundation models and generative AI, mergers and acquisitions, and geographic expansion to strengthen their market presence in the market.
Research Coverage
The report analyzes the AI in drug discovery market. It aims to estimate the market size and future growth potential of various market segments based on process, use case, therapeutic area, player type, AI tool, deployment model, end user, and region. The report also analyzes factors such as drivers, restraints, opportunities, and challenges influencing market growth. It evaluates opportunities across the AI-driven drug discovery ecosystem and assesses the competitive landscape for key stakeholders. The report further analyzes micro markets with respect to their growth trends, prospects, and contributions to the overall AI in drug discovery market. It forecasts market revenue across major regions and provides a comprehensive competitive analysis of leading market participants, including their company profiles, product portfolios, recent developments, and key growth strategies.
Reasons to Buy the Report
This report will enrich established firms as well as new entrants/smaller firms to gauge the pulse of the market, which, in turn, would help them garner a greater share of the market. Firms purchasing the report could use one or a combination of the following strategies to strengthen their positions in the market.
This report provides insights on:
・ Analysis of key drivers (Rising need to reduce time and cost of drug discovery and development, Growing utilization of AI to predict drug-target interactions for cancer therapy), restraints (Shortage of AI workforce and regulatory frameworks for AI-enabled drug discovery, Increasing AI compute infrastructure costs amid global HBM/DRAM/NAND shortage), opportunities (Accelerating biotech drug discovery, AI-driven single-cell analysis for biomarker and disease-subtype identification), and challenges (Limited availability of high-quality training datasets, Limited real-world clinical validation of AI-derived drug candidates) are factors contributing the growth of the AI in drug discovery market
・ Product Development/Innovation: Detailed insights on upcoming trends, research & development activities, and software launches in the AI in drug discovery market
・ Market Development: Comprehensive information on high-growth market segments across process, use case, therapeutic area, player type, AI tool, deployment model, end user, and region
・ Market Diversification: Exhaustive information on product portfolios, technology advancements, expanding geographic presence, strategic collaborations, investments, and recent developments in the AI in drug discovery market
・ Competitive Assessment: In-depth assessment of market shares, growth strategies, product offerings, company evaluation quadrant, technology capabilities, and competitive strengths of leading players in the global AI in drug discovery market, including NVIDIA Corporation (US), Schrödinger, Inc. (US), Recursion (US), Insilico Medicine (US), Google (US), Microsoft Corporation (US), Tempus AI, Inc. (US), Illumina, Inc. (US), XtalPi Inc. (China), and other major market participants

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Table of Contents

1 INTRODUCTION 49
1.1 STUDY OBJECTIVES 49
1.2 MARKET DEFINITION 49
1.3 MARKET SCOPE 50
1.3.1 MARKET SEGMENTATION 50
1.3.2 REGIONAL SCOPE 51
1.3.3 INCLUSIONS & EXCLUSIONS 51
1.3.4 YEARS CONSIDERED 53
1.4 CURRENCY CONSIDERED 54
1.5 LIMITATIONS 54
1.6 STAKEHOLDERS 55
1.7 SUMMARY OF CHANGES 56
2 EXECUTIVE SUMMARY 57
2.1 KEY INSIGHTS AND MARKET HIGHLIGHTS 57
2.2 KEY MARKET PARTICIPANTS: SHARE INSIGHTS AND STRATEGIC DEVELOPMENTS 59
2.3 DISRUPTIVE TRENDS SHAPING THE MARKET 60
2.4 HIGH-GROWTH SEGMENTS & EMERGING FRONTIERS 61
2.5 SNAPSHOT: GLOBAL MARKET SIZE, GROWTH RATE, AND FORECAST 62
3 PREMIUM INSIGHTS 64
3.1 AI IN DRUG DISCOVERY MARKET OVERVIEW 64
3.2 AI IN DRUG DISCOVERY MARKET, BY DEPLOYMENT & COUNTRY 65
3.3 AI IN DRUG DISCOVERY MARKET: GEOGRAPHIC SNAPSHOT 66
4 MARKET OVERVIEW 67
4.1 INTRODUCTION 67
4.2 MARKET DYNAMICS 68
4.2.1 DRIVERS 68
4.2.1.1 Increasing number of cross-industry collaborations and partnerships 68
4.2.1.2 Rising need to reduce time and cost of drug discovery and development 70
4.2.1.3 Patent expiry of drugs and need for effective new leads 71
4.2.1.4 Growing utilization of AI to predict drug-target interactions for
cancer therapy 71
4.2.1.5 Integration of AI-assisted multiomics in drug discovery 72
4.2.1.6 Growing focus on rare disease treatments for orphan
drug development 73
4.2.2 RESTRAINTS 73
4.2.2.1 Shortage of AI workforce and ambiguous regulatory guidelines for medical software 73
4.2.3 OPPORTUNITIES 74
4.2.3.1 Leveraging AI for accelerated biotech drug discovery 74
4.2.3.2 Increased focus on drug discovery in emerging economies 75
4.2.3.3 Focus on developing human-aware AI systems 76
4.2.3.4 Growing use of AI in single-cell analysis 76
4.2.3.5 Easy identification of biomarker and disease subtypes from
single-cell data 77
4.2.3.6 High demand for precision and personalized medicines 78
4.2.4 CHALLENGES 79
4.2.4.1 Limited availability of quality data sets 79
4.2.4.2 Lack of advanced AI tools and training data sets 79
4.2.4.3 Computational constraints of advanced AI models 80
4.2.4.4 Lack of high-quality data sets for model training 80
4.3 UNMET NEEDS AND WHITE SPACES 81
4.4 INTERCONNECTED MARKETS AND CROSS-SECTOR OPPORTUNITIES 82
4.5 STRATEGIC MOVES BY TIER-1/2/3 PLAYERS 83
5 INDUSTRY TRENDS 84
5.1 PORTER’S FIVE FORCES ANALYSIS 84
5.1.1 BARGAINING POWER OF SUPPLIERS 85
5.1.2 BARGAINING POWER OF BUYERS 85
5.1.3 THREAT OF SUBSTITUTES 85
5.1.4 THREAT OF NEW ENTRANTS 85
5.1.5 INTENSITY OF COMPETITIVE RIVALRY 85
5.2 MACROECONOMIC INDICATORS 86
5.2.1 INTRODUCTION 86
5.2.2 GDP TRENDS AND FORECAST 86
5.2.3 GLOBAL PHARMACEUTICAL R&D EXPENDITURE AND PRODUCTIVITY TRENDS 87
5.3 VALUE CHAIN ANALYSIS 88
5.3.1 RESEARCH, DATA GENERATION, AND SCIENTIFIC INPUTS 89
5.3.2 DATA ENGINEERING & AI INFRASTRUCTURE 89
5.3.3 AI MODEL & PLATFORM DEVELOPMENT 90
5.3.4 AI WORKFLOW INTEGRATION & DEPLOYMENT 90
5.3.5 DRUG DISCOVERY SERVICES & EXPERIMENTAL EXECUTION 90
5.3.6 VALIDATION, LAB-IN-THE-LOOP, AND CONTINUOUS OPTIMIZATION 90
5.4 ECOSYSTEM ANALYSIS 91
5.5 PRICING ANALYSIS 92
5.5.1 INDICATIVE PRICE FOR AI IN DRUG DISCOVERY PLATFORMS, BY KEY PLAYERS (2025) 93
5.5.2 INDICATIVE PRICE FOR AI IN DRUG DISCOVERY SOFTWARE AND SERVICES, BY REGION (2025) 94
5.6 KEY CONFERENCES AND EVENTS, 2026–2027 96
5.7 TRENDS/DISRUPTIONS IMPACTING CUSTOMER BUSINESS 97
5.8 INVESTMENT AND FUNDING SCENARIO 98
5.9 CASE STUDY ANALYSIS 99
5.10 IMPACT OF 2025 US TARIFF – AI IN DRUG DISCOVERY MARKET 101
5.10.1 INTRODUCTION 101
5.10.2 KEY TARIFF RATES 101
5.10.3 PRICE IMPACT ANALYSIS 102
5.10.4 IMPACT ON COUNTRY/REGION 102
5.10.4.1 US 102
5.10.4.2 Europe 103
5.10.4.3 Asia-Pacific 103
5.10.5 IMPACT ON END-USE INDUSTRIES 103
5.10.5.1 Pharmaceutical companies 103
5.10.5.2 Biotechnology companies 103
5.10.5.3 CROs and CDMOs 104
5.10.5.4 Academic and research users 104
5.10.5.5 Other end users 104
6 STRATEGIC DISRUPTION THROUGH TECHNOLOGY, PATENTS, DIGITAL,
AND AI ADOPTION 105
6.1 KEY EMERGING TECHNOLOGIES 105
6.1.1 GENERATIVE AND AGENTIC AI FOR DRUG DISCOVERY 105
6.1.2 MULTIMODAL AI AND FOUNDATION MODELS 105
6.1.3 AI-ENABLED AUTONOMOUS LABORATORIES 106
6.2 COMPLEMENTARY TECHNOLOGIES 106
6.2.1 CLOUD COMPUTING AND HIGH-PERFORMANCE COMPUTING 106
6.2.2 HIGH-THROUGHPUT SCREENING AND LABORATORY AUTOMATION 106
6.3 ADJACENT TECHNOLOGIES 106
6.3.1 MULTIOMICS AND SINGLE-CELL TECHNOLOGIES 107
6.3.2 DIGITAL TWINS AND IN-SILICO CLINICAL TECHNOLOGIES 107
6.4 TECHNOLOGY/PRODUCT ROADMAP 107
6.5 PATENT ANALYSIS 108
6.5.1 PATENT PUBLICATION TRENDS FOR AI IN DRUG DISCOVERY MARKET 108
6.5.2 INSIGHTS: JURISDICTION AND TOP APPLICANT ANALYSIS 109
6.6 FUTURE APPLICATIONS 112
6.6.1 AUTONOMOUS END-TO-END DRUG DISCOVERY 112
6.6.2 AI-DRIVEN PRECISION DRUG DISCOVERY AND PATIENT-SPECIFIC THERAPEUTICS 113
6.6.3 AI-ENABLED DIGITAL AND VIRTUAL DRUG DEVELOPMENT 113
7 REGULATORY LANDSCAPE 114
7.1 REGIONAL REGULATIONS AND COMPLIANCE 114
7.1.1 REGULATORY BODIES, GOVERNMENT AGENCIES, & OTHER ORGANIZATIONS 115
7.1.2 REGULATORY FRAMEWORK 121
7.1.2.1 North America 121
7.1.2.2 Europe 121
7.1.2.3 Asia Pacific 123
7.1.2.4 Latin America 125
7.1.2.5 Middle East & Africa 126
7.1.3 INDUSTRY STANDARDS 128
8 CUSTOMER LANDSCAPE & BUYER BEHAVIOR 129
8.1 INTRODUCTION 129
8.2 DECISION-MAKING PROCESS 129
8.3 BUYER STAKEHOLDERS AND BUYING EVALUATION CRITERIA 130
8.3.1 KEY STAKEHOLDERS IN BUYING PROCESS 130
8.3.2 BUYING CRITERIA 131
8.4 ADOPTION BARRIERS & INTERNAL CHALLENGES 132
8.5 UNMET NEEDS FROM VARIOUS END USERS 133
8.5.1 UNMET NEEDS 133
8.5.2 END USER EXPECTATIONS 134
8.6 MARKET PROFITABILITY 135
9 AI IN DRUG DISCOVERY MARKET, BY PROCESS 136
9.1 INTRODUCTION 137
9.2 TARGET IDENTIFICATION & SELECTION 137
9.2.1 INCREASED DEMAND FOR PERSONALIZED MEDICINES AND HIGH INVESTMENT IN PHARMACEUTICAL R&D TO FUEL MARKET GROWTH 137
9.3 TARGET VALIDATION 139
9.3.1 RISING EMPHASIS ON AVOIDING LATE-STAGE FAILURE IN DRUG DISCOVERY TO BOOST MARKET GROWTH 139
9.4 HIT IDENTIFICATION & PRIORITIZATION 140
9.4.1 NEED FOR LARGE-SCALE DATA ANALYSIS TO DRIVE ADOPTION 140
9.5 HIT-TO-LEAD IDENTIFICATION/LEAD GENERATION 141
9.5.1 HIT-TO-LEAD IDENTIFICATION/LEAD GENERATION TO IMPROVE NEW DRUG POTENCY WITHOUT INCREASING LIPOPHILICITY 141
9.6 LEAD OPTIMIZATION 142
9.6.1 NEED FOR TRANSPARENT PRESENTATION AND ANALYSIS TO BOOST
MARKET GROWTH 142
9.7 CANDIDATE SELECTION & VALIDATION 144
9.7.1 HIGH POSSIBILITY OF CLINICAL DRUG FAILURE TO SPUR ADOPTION OF CANDIDATE VALIDATION SERVICES 144
10 AI IN DRUG DISCOVERY MARKET, BY AI TOOL 146
10.1 INTRODUCTION 147
10.2 MACHINE LEARNING 148
10.2.1 INCREASING AVAILABILITY OF COMPLEX BIOLOGICAL AND CHEMICAL DATASETS DRIVES ADOPTION 148
10.2.2 DEEP LEARNING 150
10.2.2.1 Ability to capture complex nonlinear relationships across multimodal biological and molecular data – key driver 150
10.2.2.2 Transformer-based architectures 152
10.2.2.2.1 Growing volumes of sequential, multimodal, and unstructured scientific data drives market 152
10.2.2.3 Graph neural networks (GNN) 153
10.2.2.3.1 Need to understand molecular structure and complex biological relationships supports GNN adoption 153
10.2.2.4 Convolutional neural networks (CNN) 154
10.2.2.4.1 Expansion of image-based and 3D structural analysis boosts adoption 154
10.2.2.5 Diffusion and flow-based models 155
10.2.2.5.1 Increasing demand for controlled generation of novel molecules and proteins accelerates segment growth 155
10.2.2.6 Generative adversarial networks (GAN) & variational autoencoders (VAE) 156
10.2.2.6.1 Growing demand for computational exploration of chemical space supports growth 156
10.2.2.7 Recurrent & Sequence Models (RNN, LSTM) 157
10.2.2.7.1 Continued need to model sequential chemical and biological information sustains demand 157
10.2.2.8 Other deep learning technologies 158
10.2.2.8.1 Emergence of specialized neural architectures expands applications across complex discovery workflows 158
10.2.3 SUPERVISED LEARNING 159
10.2.3.1 Growing availability of experimentally validated datasets supports segment 159
10.2.4 SELF-SUPERVISED & REPRESENTATION LEARNING 160
10.2.4.1 Shortage of labeled biological data and growing availability of unlabeled datasets drive adoption 160
10.2.5 REINFORCEMENT LEARNING 161
10.2.5.1 Need to optimize molecules and experimental decisions across multiple objectives drives adoption 161
10.2.6 UNSUPERVISED LEARNING 162
10.2.6.1 Increasing complexity of biological datasets to boost segment 162
10.2.7 OTHER MACHINE LEARNING TECHNOLOGIES 163
10.2.7.1 Need to extract value from partially labeled and heterogeneous datasets supports segment 163
10.3 GENERATIVE AI 164
10.3.1 ABILITY TO DESIGN NOVEL MOLECULES AND BIOLOGICAL STRUCTURES ACCELERATES ADOPTION 164
10.3.2 MOLECULAR GENERATIVE MODELS 165
10.3.2.1 Need to explore larger chemical spaces and simultaneously optimize multiple molecular properties – segment driver 165
10.3.3 PROTEIN & BIOLOGICS GENERATIVE MODELS 166
10.3.3.1 Growing demand for engineered proteins, antibodies, and other biologics expands applications 166
10.3.4 LARGE LANGUAGE MODELS (LLMS) 167
10.3.4.1 Rapid growth of scientific literature and unstructured research data increases demand 167
10.4 FOUNDATION MODELS 168
10.4.1 NEED FOR REUSABLE AI MODELS TO LEARN FROM LARGE-SCALE, MULTIMODAL BIOLOGICAL DATASETS DRIVES ADOPTION 168
10.4.2 CHEMISTRY FOUNDATION MODELS 169
10.4.2.1 Increasing need for reusable molecular representation and scalable chemical intelligence drives segment 169
10.4.3 PROTEIN LANGUAGE MODELS 170
10.4.3.1 Growing demand for protein engineering and functional prediction accelerates adoption 170
10.4.4 BIOLOGY AND MULTIOMICS FOUNDATION MODELS 171
10.4.4.1 Increasing integration of genomic, transcriptomic, proteomic, and cellular data – key driver 171
10.5 AGENTIC AI & AI CO-SCIENTISTS 172
10.5.1 GROWTH DRIVEN BY DEMAND FOR AUTONOMOUS RESEARCH WORKFLOWS AND IMPROVED SCIENTIST PRODUCTIVITY 172
10.5.2 AUTONOMOUS RESEARCH AGENTS & WORKFLOW ORCHESTRATION 173
10.5.2.1 Need to automate complex multi-step research processes drives adoption 173
10.5.3 MULTI-AGENT REASONING SYSTEMS 174
10.5.3.1 Increasing complexity of scientific problems creates demand 174
10.5.4 LAB-IN-THE-LOOP & CLOSED-LOOP EXPERIMENTATION 175
10.5.4.1 Integration of AI with automated laboratories enables continuous design–build–test–learn workflows 175
10.6 KNOWLEDGE GRAPHS AND SEMANTIC REASONING 176
10.6.1 NEED TO CONNECT FRAGMENTED SCIENTIFIC INFORMATION AND IDENTIFY HIDDEN RELATIONSHIPS DRIVES SEGMENT 176
10.7 NATURAL LANGUAGE PROCESSING (NLP) 177
10.7.1 EXPLOSION OF SCIENTIFIC LITERATURE, PATENTS, AND UNSTRUCTURED R&D INFORMATION DRIVES NLP ADOPTION 177
10.8 COMPUTER VISION & IMAGE ANALYSIS 178
10.8.1 INCREASING USE OF HIGH-CONTENT SCREENING, MICROSCOPY, AND PHENOTYPIC ASSAYS EXPANDS APPLICATIONS 178
10.9 PHYSICS-BASED & HYBRID AI METHODS 179
10.9.1 NEED FOR MECHANISTIC UNDERSTANDING AND IMPROVED ACCURACY IN MOLECULAR MODELING DRIVES SEGMENT 179
11 AI IN DRUG DISCOVERY MARKET, BY END USER 182
11.1 INTRODUCTION 183
11.2 PHARMACEUTICAL & BIOTECHNOLOGY COMPANIES 183
11.2.1 GROWING PRESSURE TO ACCELERATE R&D PRODUCTIVITY AND REDUCE DRUG DISCOVERY COSTS DRIVES SEGMENT 183
11.2.2 LARGE PHARMACEUTICAL COMPANIES 185
11.2.2.1 High R&D expenditure and increasing need to improve pipeline productivity accelerate AI adoption 185
11.2.3 SMALL & MID-SIZED BIOTECHNOLOGY COMPANIES 186
11.2.3.1 Limited internal resources and need for differentiated pipelines increase reliance on AI-enabled discovery 186
11.3 CONTRACT RESEARCH ORGANIZATIONS (CROS) & CDMOS 187
11.3.1 INCREASING OUTSOURCING OF DRUG DISCOVERY ACTIVITIES DRIVES GROWTH 187
11.4 RESEARCH CENTERS, ACADEMIC INSTITUTES, AND GOVERNMENT ORGANIZATIONS 188
11.4.1 GROWING AVAILABILITY OF RESEARCH FUNDING AND ADVANCED AI CAPABILITIES EXPANDS GROWTH 188
12 AI IN DRUG DISCOVERY MARKET, BY USE CASE 190
12.1 INTRODUCTION 191
12.2 UNDERSTANDING DISEASE BIOLOGY 192
12.2.1 INCREASED FOCUS ON UNDERSTANDING DISEASES TO IMPROVE RESEARCH DATA QUALITY AND QUANTITY 192
12.2.2 EVIDENCE SYNTHESIS AND SCIENTIFIC LITERATURE INTELLIGENCE 194
12.2.2.1 Rapid data analysis – key demand driver 194
12.2.3 MULTIOMICS INTEGRATION & TARGET-DISEASE ASSOCIATION 195
12.2.3.1 Growing integration of genomic, transcriptomic, proteomic, metabolomic, and other biological datasets to drive market 195
12.2.4 EXPERIMENT DESIGN & REAGENT/MODEL SELECTION 196
12.2.4.1 Growing complexity of disease biology and experiment design boosts demand 196
12.3 PROTEIN STRUCTURE & INTERACTION PREDICTION 197
12.3.1 ADVANCES IN AI-POWERED PROTEIN INTERACTION PREDICTION ACCELERATE STRUCTURE-BASED DRUG DISCOVERY 197
12.4 DRUG REPURPOSING 198
12.4.1 INCREASING ADOPTION OF AI PLATFORMS FOR SYSTEMATIC DRUG REPURPOSING 198
12.5 DE NOVO DRUG DESIGN 199
12.5.1 SMALL MOLECULE DESIGN 200
12.5.1.1 Increasing use of virtual screening and simulation techniques to
drive growth 200
12.5.2 VACCINE DESIGN 201
12.5.2.1 Availability of well-validated AI tools to boost market growth 201
12.5.3 ANTIBODY & OTHER BIOLOGICS DESIGN 202
12.5.3.1 Advancements in protein modeling to propel segment growth 202
12.5.4 PROTEIN & ENZYME DESIGN 203
12.5.4.1 Protein designing to propel segment growth 203
12.6 DRUG OPTIMIZATION 204
12.6.1 SMALL MOLECULE OPTIMIZATION 205
12.6.1.1 Generative models for potential modifications in molecular structures to aid market growth 205
12.6.2 VACCINE OPTIMIZATION 206
12.6.2.1 Effective prediction of vaccine formulations and adjustment of delivery vectors to drive growth 206
12.6.3 ANTIBODY & OTHER BIOLOGICS OPTIMIZATION 207
12.6.3.1 Increasing adoption of machine learning to predict protein structures to augment segment growth 207
12.7 SAFETY & TOXICITY 209
12.7.1 FOCUS ON ADVANCED OFF-TARGET EFFECT PREDICTION, PK/PD SIMULATION, AND QSP MODELING TO DRIVE MARKET 209
13 AI IN DRUG DISCOVERY MARKET, BY DEPLOYMENT 211
13.1 INTRODUCTION 212
13.2 ON-PREMISE SOLUTIONS 212
13.2.1 GROWING DEMAND FOR DATA SOVEREIGNTY, IP PROTECTION, AND CONTROL OVER PROPRIETARY R&D DATA SUPPORTS GROWTH DEPLOYMENT 212
13.3 CLOUD-BASED SOLUTIONS 213
13.3.1 NEED FOR SCALABLE COMPUTING, RAPID AI DEPLOYMENT, AND COST-EFFICIENT ACCESS TO ADVANCED INFRASTRUCTURE - KEY DRIVERS 213
13.3.2 PUBLIC CLOUD 214
13.3.2.1 Elastic computing capacity and access to advanced AI infrastructure drive adoption 214
13.3.3 PRIVATE CLOUD/VPC/SOVEREIGN DEPLOYMENT 215
13.3.3.1 Increasing data-security, IP-protection, and data-residency requirements strengthen demand 215
13.4 HYBRID SOLUTIONS 216
13.4.1 NEED TO BALANCE COMPUTATIONAL SCALABILITY WITH CONTROL OVER SENSITIVE R&D DATA ACCELERATES ADOPTION 216
14 AI IN DRUG DISCOVERY MARKET, BY THERAPEUTIC AREA 218
14.1 INTRODUCTION 219
14.2 ONCOLOGY 219
14.2.1 HIGH PREVALENCE OF ONCOLOGY AND SHORTAGE OF EFFECTIVE ONCOLOGY DRUGS TO DRIVE MARKET GROWTH 219
14.3 INFECTIOUS DISEASES 220
14.3.1 RISING ANTIMICROBIAL RESISTANCE AND NEED FOR NOVEL ANTI-INFECTIVE THERAPIES TO DRIVE GROWTH 220
14.4 NEUROLOGY 221
14.4.1 HIGH DISEASE COMPLEXITY AND LIMITED TREATMENT OPTIONS DRIVE DEMAND FOR AI-ENABLED DISCOVERY 221
14.5 CARDIOVASCULAR DISEASES 223
14.5.1 GROWING CARDIOVASCULAR DISEASE BURDEN AND NEED FOR NOVEL THERAPEUTIC TARGETS BOOST GROWTH 223
14.6 METABOLIC DISEASES 224
14.6.1 RISING PREVALENCE OF OBESITY AND METABOLIC DISORDERS ACCELERATES DEMAND FOR INNOVATIVE THERAPIES 224
14.7 IMMUNOLOGY 225
14.7.1 COMPLEX IMMUNE MECHANISMS AND GROWING DEMAND FOR TARGETED THERAPIES DRIVE AI ADOPTION 225
14.8 RARE & GENETIC DISORDERS 226
14.8.1 LIMITED TREATMENT OPTIONS AND FRAGMENTED DISEASE DATA DRIVE
AI-ENABLED DRUG DISCOVERY 226
14.9 MENTAL HEALTH DISORDERS 227
14.9.1 HIGH UNMET NEED AND LIMITED UNDERSTANDING OF DISEASE MECHANISMS DRIVE SEGMENT GROWTH 227
14.10 OTHER THERAPEUTIC AREAS 228
14.10.1 EXPANDING APPLICATION OF AI ACROSS UNDEREXPLORED DISEASE AREAS DRIVES MARKET GROWTH 228
15 AI IN DRUG DISCOVERY MARKET, BY PLAYER TYPE 230
15.1 INTRODUCTION 231
15.2 END-TO-END SOLUTION PROVIDERS 231
15.2.1 INCREASING ADOPTION OF INTEGRATED AI PLATFORMS ACROSS DRUG DISCOVERY WORKFLOW DRIVES GROWTH 231
15.3 NICHE/POINT SOLUTION PROVIDERS 232
15.3.1 GROWING DEMAND FOR SPECIALIZED AI CAPABILITIES TARGETING COMPLEX DISCOVERY CHALLENGES TO DRIVE GROWTH 232
15.4 AI TECHNOLOGY PROVIDERS 233
15.4.1 RAPID ADVANCES IN GENERATIVE AI, FOUNDATION MODELS, AND AGENTIC AI ACCELERATE DEMAND 233
15.5 COMPUTE & INFRASTRUCTURE PROVIDERS 234
15.5.1 GROWING COMPUTATIONAL REQUIREMENTS OF ADVANCED AI MODELS DRIVE DEMAND 234
15.6 BUSINESS PROCESS SERVICE PROVIDERS 235
15.6.1 INCREASING OUTSOURCING OF SPECIALIZED AI-ENABLED DISCOVERY ACTIVITIES DRIVES GROWTH 235
16 AI IN DRUG DISCOVERY MARKET, BY REGION 237
16.1 INTRODUCTION 238
16.2 NORTH AMERICA 238
16.2.1 MACROECONOMIC OUTLOOK FOR NORTH AMERICA 239
16.2.2 US 248
16.2.2.1 Strong pharma–AI ecosystem and high R&D investment
drives demand 248
16.2.3 CANADA 257
16.2.3.1 Strong AI research base and growing biopharma innovation
– key drivers 257
16.3 EUROPE 265
16.3.1 MACROECONOMIC OUTLOOK FOR EUROPE 265
16.3.2 GERMANY 274
16.3.2.1 Availability of advanced computing and research infrastructure
– key market driver 274
16.3.3 UK 282
16.3.3.1 Increasing investment in AI-based molecular design drives demand 282
16.3.4 SWITZERLAND 290
16.3.4.1 Strong pharmaceutical and biotechnology ecosystem to boost market 290
16.3.5 FRANCE 298
16.3.5.1 Large-scale AI investment by pharmaceutical companies – key driver 298
16.3.6 ITALY 306
16.3.6.1 Market driven by country’s strong pharmaceutical and life
sciences ecosystem 306
16.3.7 SPAIN 314
16.3.7.1 Expansion of AI-enabled biotechnology research drives demand 314
16.3.8 REST OF EUROPE 322
16.3.8.1 Growing pharmaceutical R&D and public-sector AI adoption to
drive market 322
16.4 ASIA PACIFIC 330
16.4.1 MACROECONOMIC OUTLOOK FOR ASIA PACIFIC 331
16.4.2 JAPAN 340
16.4.2.1 Increasing pharmaceutical investment in AI and robotics
drives demand 340
16.4.3 CHINA 348
16.4.3.1 Growth of AI-native biotech companies boosts demand 348
16.4.4 INDIA 357
16.4.4.1 Large pharmaceutical and biotechnology ecosystem to propel market 357
16.4.5 SOUTH KOREA 365
16.4.5.1 Government support for AI-based drug discovery to boost market 365
16.4.6 AUSTRALIA 374
16.4.6.1 Market driven by strong government support for AI and
medical research 374
16.4.7 REST OF ASIA PACIFIC 382
16.4.7.1 Growth of regional pharmaceutical and biotechnology capabilities to boost market 382
16.5 LATIN AMERICA 391
16.5.1 MACROECONOMIC OUTLOOK FOR LATIN AMERICA 392
16.5.2 BRAZIL 400
16.5.2.1 Expanding pharmaceutical R&D and emerging AI-biotech ecosystem act as major drivers 400
16.5.3 MEXICO 408
16.5.3.1 Multinational pharmaceutical activity and government-backed research to drive market 408
16.5.4 REST OF LATIN AMERICA 416
16.5.4.1 Growing research base for AI to drive market 416
16.6 MIDDLE EAST & AFRICA 425
16.6.1 MACROECONOMIC OUTLOOK FOR MIDDLE EAST & AFRICA 425
16.6.2 GCC COUNTRIES 434
16.6.2.1 National AI strategies and growing technology partnerships act as major drivers 434
16.6.3 SAUDI ARABIA 442
16.6.3.1 Government investment in biotechnology and life sciences propels market 442
16.6.4 UAE 450
16.6.4.1 Government-led AI and biotechnology investment boosts market 450
16.6.5 REST OF GCC 459
16.6.5.1 International AI-drug discovery partnerships drive demand 459
16.6.6 SOUTH AFRICA 467
16.6.6.1 Strong domestic drug-discovery research base drives market 467
16.6.7 REST OF MIDDLE EAST & AFRICA 475
16.6.7.1 Expansion of local pharmaceutical and biomanufacturing capabilities drives demand 475
17 COMPETITIVE LANDSCAPE 484
17.1 OVERVIEW 484
17.2 KEY PLAYER STRATEGIES/RIGHT TO WIN 484
17.2.1 OVERVIEW OF STRATEGIES ADOPTED BY KEY PLAYERS IN AI IN DRUG DISCOVERY MARKET 485
17.3 REVENUE SHARE ANALYSIS OF TOP MARKET PLAYERS 488
17.4 MARKET SHARE ANALYSIS, 2025 489
17.5 BRAND COMPARISON 491
17.6 VALUATION & FINANCIAL METRICS 492
17.6.1 FINANCIAL METRICS 492
17.6.2 COMPANY VALUATION 492
17.7 COMPANY EVALUATION MATRIX 493
17.7.1 STARS 493
17.7.2 EMERGING LEADERS 493
17.7.3 PERVASIVE PLAYERS 493
17.7.4 PARTICIPANTS 494
17.7.5 COMPANY FOOTPRINT: KEY PLAYERS, 2025 495
17.7.5.1 Company footprint 495
17.7.5.2 Region footprint 496
17.8 COMPANY EVALUATION MATRIX: STARTUPS/SMES, 2025 502
17.8.1 PROGRESSIVE COMPANIES 502
17.8.2 RESPONSIVE COMPANIES 502
17.8.3 DYNAMIC COMPANIES 502
17.8.4 STARTING BLOCKS 502
17.8.5 COMPETITIVE BENCHMARKING: STARTUPS/SMES, 2025 504
17.8.5.1 Detailed list of key startups/SMEs 504
17.8.5.2 Competitive benchmarking of startups/SMEs 505
17.9 COMPETITIVE SCENARIO 505
17.9.1 PRODUCT/SERVICE LAUNCHES 505
17.9.2 DEALS 506
17.9.3 EXPANSIONS 507
17.9.4 OTHER DEVELOPMENTS 507
18 COMPANY PROFILES 508
18.1 KEY PLAYERS 508
18.1.1 NVIDIA CORPORATION 508
18.1.1.1 Business overview 508
18.1.1.2 Products/Services offered 510
18.1.1.3 Recent developments 511
18.1.1.3.1 Product/Service launches & approvals 511
18.1.1.3.2 Deals 512
18.1.1.3.3 Other developments 515
18.1.1.4 MnM view 515
18.1.1.4.1 Right to win 515
18.1.1.4.2 Strategic choices 516
18.1.1.4.3 Weaknesses & competitive threats 516
18.1.2 ALPHABET INC. 517
18.1.2.1 Business overview 517
18.1.2.2 Products/Services offered 518
18.1.2.3 Recent developments 519
18.1.2.3.1 Product launches & approvals 519
18.1.2.3.2 Deals 520
18.1.2.3.3 Other developments 521
18.1.2.4 MnM view 521
18.1.2.4.1 Right to win 521
18.1.2.4.2 Strategic choices 521
18.1.2.4.3 Weaknesses & competitive threats 521
18.1.3 RECURSION 522
18.1.3.1 Business overview 522
18.1.3.2 Products/Services offered 523
18.1.3.3 Recent developments 524
18.1.3.3.1 Product/Service launches 524
18.1.3.3.2 Deals 524
18.1.3.3.3 Expansions 526
18.1.3.4 MnM view 527
18.1.3.4.1 Right to win 527
18.1.3.4.2 Strategic choices 527
18.1.3.4.3 Weaknesses & competitive threats 527
18.1.4 INSILICO MEDICINE 528
18.1.4.1 Business overview 528
18.1.4.2 Products/Services offered 529
18.1.4.3 Recent developments 530
18.1.4.3.1 Product/Service launches 530
18.1.4.3.2 Deals 531
18.1.4.3.3 Other developments 534
18.1.4.3.4 expansions 534
18.1.4.4 MnM view 534
18.1.4.4.1 Right to win 534
18.1.4.4.2 Strategic choices 535
18.1.4.4.3 Weaknesses & competitive threats 535
18.1.5 SCHRÖDINGER, INC. 536
18.1.5.1 Business overview 536
18.1.5.2 Products/Services offered 537
18.1.5.3 Recent developments 538
18.1.5.3.1 Deals 538
18.1.5.3.2 Other developments 539
18.1.5.4 MnM view 540
18.1.5.4.1 Right to win 540
18.1.5.4.2 Strategic choices 540
18.1.5.4.3 Weaknesses & competitive threats 540
18.1.6 BENEVOLENTAI 541
18.1.6.1 Business overview 541
18.1.6.2 Products/Services offered 542
18.1.6.3 Recent developments 542
18.1.6.3.1 Deals 542
18.1.7 MICROSOFT CORPORATION 544
18.1.7.1 Business overview 544
18.1.7.2 Products /Services offered 545
18.1.7.3 Recent developments 546
18.1.7.3.1 Product/Service launches & approvals 546
18.1.7.3.2 Deals 546
18.1.8 NUMERION LABS 548
18.1.8.1 Business overview 548
18.1.8.2 Products/Services offered 549
18.1.9 ILLUMINA, INC. 550
18.1.9.1 Business overview 550
18.1.9.2 Products/Services offered 551
18.1.9.3 Recent developments 553
18.1.9.3.1 Product/Service launches 553
18.1.9.3.2 Deals 554
18.1.10 XTALPI INC. 556
18.1.10.1 Business overview 556
18.1.10.2 Products/Services offered 557
18.1.10.3 Recent developments 558
18.1.10.3.1 Deals 558
18.1.11 IKTOS 560
18.1.11.1 Business overview 560
18.1.11.2 Products/Services offered 561
18.1.11.3 Recent developments 562
18.1.11.3.1 Deals 562
18.1.11.3.2 Other developments 563
18.1.12 TEMPUS AI, INC. 564
18.1.12.1 Business overview 564
18.1.12.2 Products/Services offered 565
18.1.12.3 Recent developments 566
18.1.12.3.1 Product/Service launches 566
18.1.12.3.2 Deals 567
18.1.13 DEEP GENOMICS, INC. 570
18.1.13.1 Business overview 570
18.1.13.2 Products/Services offered 570
18.1.13.3 Recent developments 571
18.1.13.3.1 Product/Service launches & approvals 571
18.1.14 VERGE LABS 572
18.1.14.1 Business overview 572
18.1.14.2 Products /Services offered 573
18.1.14.3 Recent developments 573
18.1.14.3.1 Deals 573
18.1.15 BENCHSCI 575
18.1.15.1 Business overview 575
18.1.15.2 Products/Services offered 575
18.1.15.3 Recent developments 576
18.1.15.3.1 Product/Service launches & approvals 576
18.1.15.3.2 Deals 576
18.1.15.3.3 Other developments 577
18.1.16 INSITRO 578
18.1.16.1 Business overview 578
18.1.16.2 Products/Services offered 578
18.1.16.3 Recent developments 579
18.1.16.3.1 Deals 579
18.1.16.3.2 Other developments 579
18.1.17 VALO HEALTH 580
18.1.17.1 Business overview 580
18.1.17.2 Products/Services offered 580
18.1.17.3 Recent developments 581
18.1.17.3.1 Deals 581
18.1.17.3.2 Other developments 582
18.1.18 BPGBIO, INC. 583
18.1.18.1 Business overview 583
18.1.18.2 Products/Services offered 583
18.1.18.3 Recent developments 584
18.1.18.3.1 Deals 584
18.1.19 GENERATE:BIOMEDICINES 585
18.1.19.1 Business overview 585
18.1.19.2 Products/Services offered 585
18.1.19.3 Recent developments 586
18.1.19.3.1 Product/Service launches 586
18.1.19.3.2 Deals 587
18.1.19.3.3 Expansions 588
18.1.20 CERTARA, INC. 589
18.1.20.1 Business overview 589
18.1.20.2 Products/Services offered 590
18.1.20.3 Recent developments 591
18.1.20.3.1 Product/Service launches & approvals 591
18.1.20.3.2 Deals 592
18.2 OTHER EMERGING PLAYERS 594
18.2.1 XAIRA THERAPEUTICS 594
18.2.2 IAMBIC THERAPEUTICS, INC. 595
18.2.3 GENESIS MOLECULAR AI 596
18.2.4 CRADLE BIO 597
18.2.5 ISOMORPHIC LABS 598
19 RESEARCH METHODOLOGY 599
19.1 RESEARCH APPROACH 599
19.1.1 SECONDARY RESEARCH 600
19.1.1.1 Key data from secondary sources 601
19.1.2 PRIMARY RESEARCH 601
19.1.2.1 Primary sources 602
19.1.2.2 Key data from primary sources 603
19.1.2.3 Breakdown of primaries 603
19.1.2.4 Insights from primary experts 604
19.2 RESEARCH METHODOLOGY DESIGN 604
19.3 MARKET SIZE ESTIMATION 606
19.4 MARKET BREAKDOWN DATA TRIANGULATION 612
19.5 MARKET SHARE ESTIMATION 612
19.6 STUDY ASSUMPTIONS 613
19.7 RESEARCH LIMITATIONS 613
19.7.1 METHODOLOGY-RELATED LIMITATIONS 613
19.8 RISK ASSESSMENT 614
20 APPENDIX 615
20.1 DISCUSSION GUIDE 615
20.2 KNOWLEDGESTORE: MARKETSANDMARKETS’ SUBSCRIPTION PORTAL 626
20.3 CUSTOMIZATION OPTIONS 628
20.4 RELATED REPORTS 628
20.5 AUTHOR DETAILS 629

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List of Tables/Graphs

TABLE 1 USD EXCHANGE RATES 54.
TABLE 2 AI IN DRUG DISCOVERY: COLLABORATIONS AND PARTNERSHIPS, 2024–2026 69.
TABLE 3 INDICATIVE LIST OF DRUGS LOSING PATENTS IN 2025 AND 2026 71.
TABLE 4 AI IN DRUG DISCOVERY MARKET: ROLE IN ECOSYSTEM 92.
TABLE 5 INDICATIVE PRICE FOR AI IN DRUG DISCOVERY PLATFORMS, BY KEY PLAYERS, 2025 93.
TABLE 6 INDICATIVE PRICE FOR AI IN DRUG DISCOVERY MARKET, BY REGION (2025) 95.
TABLE 7 KEY CONFERENCES & EVENTS IN AI IN DRUG DISCOVERY MARKET, JULY 2026-JUNE 2027 96.
TABLE 8 CASE 1: TERRAY THERAPEUTICS’ USE OF NVIDIA TO ACCELERATE GENERATIVE AI-ENABLED SMALL-MOLECULE DRUG DISCOVERY 99.
TABLE 9 CASE 2: ASTELLAS PHARMA’S USE OF NVIDIA AI TO ACCELERATE BIOMOLECULAR DISCOVERY AND COMPOUND SCREENING 100.
TABLE 10 CASE 3: AMGEN–NVIDIA COLLABORATION ACCELERATES BIOLOGICS DISCOVERY THROUGH GENERATIVE AI 100.
TABLE 11 US ADJUSTED RECIPROCAL TARIFF RATES 101.
TABLE 12 JURISDICTION ANALYSIS OF TOP APPLICANT COUNTRIES FOR AI IN DRUG DISCOVERY 109.
TABLE 13 AI IN DRUG DISCOVERY MARKET: KEY PATENTS/PATENT APPLICATIONS 111.
TABLE 14 NORTH AMERICA: REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS 115.
TABLE 15 EUROPE: REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS 116.
TABLE 16 ASIA PACIFIC: REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS 117.
TABLE 17 LATIN AMERICA: REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS 118.
TABLE 18 MIDDLE EAST & AFRICA: REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS 119.
TABLE 19 REGULATORY SCENARIO OF NORTH AMERICA 121.
TABLE 20 REGULATORY SCENARIO OF EUROPE 121.
TABLE 21 REGULATORY SCENARIO OF ASIA PACIFIC 123.
TABLE 22 REGULATORY SCENARIO OF LATIN AMERICA 125.
TABLE 23 REGULATORY SCENARIO OF MIDDLE EAST & AFRICA 126.
TABLE 24 INFLUENCE OF STAKEHOLDERS ON BUYING PROCESS OF TOP THREE END USERS (%) 131.
TABLE 25 KEY BUYING CRITERIA FOR TOP THREE END USERS 132.
TABLE 26 AI IN DRUG DISCOVERY MARKET: UNMET NEEDS 133.
TABLE 27 DRUG DISCOVERY MARKET: END USER EXPECTATIONS 134.
TABLE 28 AI IN DRUG DISCOVERY MARKET, BY PROCESS, 2024–2031 (USD MILLION) 137.
TABLE 29 AI IN DRUG DISCOVERY MARKET FOR TARGET IDENTIFICATION & SELECTION, BY REGION, 2024–2031 (USD MILLION) 138.
TABLE 30 AI IN DRUG DISCOVERY MARKET FOR TARGET VALIDATION, BY REGION, 2024–2031 (USD MILLION) 140.
TABLE 31 AI IN DRUG DISCOVERY MARKET FOR HIT IDENTIFICATION & PRIORITIZATION, BY REGION, 2024–2031 (USD MILLION) 141.
TABLE 32 AI IN DRUG DISCOVERY MARKET FOR HIT TO LEAD IDENTIFICATION/LEAD GENERATION, BY REGION, 2024–2031 (USD MILLION) 142.
TABLE 33 AI IN DRUG DISCOVERY MARKET FOR LEAD OPTIMIZATION, BY REGION, 2024–2031 (USD MILLION) 143.
TABLE 34 AI IN DRUG DISCOVERY MARKET FOR CANDIDATE SELECTION & VALIDATION, BY REGION, 2024–2031 (USD MILLION) 145.
TABLE 35 AI IN DRUG DISCOVERY MARKET, BY AI TOOL, 2024–2031 (USD MILLION) 147.
TABLE 36 MACHINE LEARNING: AI IN DRUG DISCOVERY MARKET, BY TYPE, 2024–2031 (USD MILLION) 149.
TABLE 37 MACHINE LEARNING: AI IN DRUG DISCOVERY MARKET, BY REGION, 2024–2031 (USD MILLION) 149.
TABLE 38 DEEP LEARNING: AI IN DRUG DISCOVERY MARKET, BY TYPE, 2024–2031 (USD MILLION) 151.
TABLE 39 DEEP LEARNING: AI IN DRUG DISCOVERY MARKET, BY REGION, 2024–2031 (USD MILLION) 151.
TABLE 40 TRANSFORMER-BASED ARCHITECTURE: AI IN DRUG DISCOVERY MARKET, BY REGION, 2024–2031 (USD MILLION) 152.
TABLE 41 GRAPH NEURAL NETWORKS: AI IN DRUG DISCOVERY MARKET, BY REGION, 2024–2031 (USD MILLION) 153.
TABLE 42 CONVOLUTIONAL NEURAL NETWORKS: AI IN DRUG DISCOVERY MARKET, BY REGION, 2024–2031 (USD MILLION) 154.
TABLE 43 DIFFUSION AND FLOW-BASED MODELS: AI IN DRUG DISCOVERY MARKET, BY REGION, 2024–2031 (USD MILLION) 155.
TABLE 44 GAN & VAE: AI IN DRUG DISCOVERY MARKET, BY REGION, 2024–2031 (USD MILLION) 156.
TABLE 45 RECURRENT & SEQUENCE MODELS: AI IN DRUG DISCOVERY MARKET, BY REGION, 2024–2031 (USD MILLION) 157.
TABLE 46 OTHER DEEP LEARNING TECHNOLOGIES: AI IN DRUG DISCOVERY MARKET, BY REGION, 2024–2031 (USD MILLION) 158.
TABLE 47 SUPERVISED LEARNING: AI IN DRUG DISCOVERY MARKET, BY REGION, 2024–2031 (USD MILLION) 159.
TABLE 48 SELF-SUPERVISED & REPRESENTATION LEARNING: AI IN DRUG DISCOVERY MARKET, BY REGION, 2024–2031 (USD MILLION) 160.
TABLE 49 REINFORCEMENT LEARNING: AI IN DRUG DISCOVERY MARKET, BY REGION, 2024–2031 (USD MILLION) 161.
TABLE 50 UNSUPERVISED LEARNING: AI IN DRUG DISCOVERY MARKET, BY REGION, 2024–2031 (USD MILLION) 162.
TABLE 51 OTHER MACHINE LEARNING TECHNOLOGIES: AI IN DRUG DISCOVERY MARKET, BY REGION, 2024–2031 (USD MILLION) 163.
TABLE 52 GENERATIVE AI: AI IN DRUG DISCOVERY MARKET, BY TYPE, 2024–2031 (USD MILLION) 165.
TABLE 53 GENERATIVE AI: AI IN DRUG DISCOVERY, BY REGION, 2024–2031 (USD MILLION) 165.
TABLE 54 MOLECULAR GENERATIVE MODELS: AI IN DRUG DISCOVERY MARKET, BY REGION, 2024–2031 (USD MILLION) 166.
TABLE 55 PROTEIN & BIOLOGICS GENERATIVE MODELS: AI IN DRUG DISCOVERY MARKET, BY REGION, 2024–2031 (USD MILLION) 167.
TABLE 56 LARGE LANGUAGE MODELS: AI IN DRUG DISCOVERY MARKET, BY REGION, 2024–2031 (USD MILLION) 168.
TABLE 57 FOUNDATION MODELS: AI IN DRUG DISCOVERY MARKET, BY TYPE, 2024–2031 (USD MILLION) 169.
TABLE 58 FOUNDATION MODELS: AI IN DRUG DISCOVERY MARKET, BY REGION, 2024–2031 (USD MILLION) 169.
TABLE 59 CHEMISTRY FOUNDATION MODELS: AI IN DRUG DISCOVERY MARKET, BY REGION, 2024–2031 (USD MILLION) 170.
TABLE 60 PROTEIN LANGUAGE MODELS: AI IN DRUG DISCOVERY MARKET, BY REGION, 2024–2031 (USD MILLION) 171.
TABLE 61 BIOLOGY AND MULTIOMICS FOUNDATION MODELS: AI IN DRUG DISCOVERY MARKET, BY REGION, 2024–2031 (USD MILLION) 172.
TABLE 62 AGENTIC AI & CO-SCIENTISTS: AI IN DRUG DISCOVERY MARKET, BY TYPE, 2024–2031 (USD MILLION) 173.
TABLE 63 AGENTIC AI & CO-SCIENTISTS: AI IN DRUG DISCOVERY MARKET, BY REGION, 2024–2031 (USD MILLION) 173.
TABLE 64 AUTONOMOUS RESEARCH AGENTS & WORKFLOW ORCHESTRATION: AI IN DRUG DISCOVERY MARKET, BY REGION, 2024–2031 (USD MILLION) 174.
TABLE 65 MULTI-AGENT REASONING SYSTEMS: AI IN DRUG DISCOVERY MARKET, BY REGION, 2024–2031 (USD MILLION) 175.
TABLE 66 LAB-IN-THE-LOOP & CLOSED-LOOP EXPERIMENTATION: AI IN DRUG DISCOVERY MARKET, BY REGION, 2024–2031 (USD MILLION) 176.
TABLE 67 KNOWLEDGE GRAPHS AND SEMANTIC REASONING: AI IN DRUG DISCOVERY MARKET, BY REGION, 2024–2031 (USD MILLION) 177.
TABLE 68 NATURAL LANGUAGE PROCESSING: AI IN DRUG DISCOVERY MARKET, BY REGION, 2024–2031 (USD MILLION) 178.
TABLE 69 COMPUTER VISION & IMAGE ANALYSIS: AI IN DRUG DISCOVERY MARKET, BY REGION, 2024–2031 (USD MILLION) 179.
TABLE 70 PHYSICS-BASED & HYBRID AI MODELS: AI IN DRUG DISCOVERY MARKET, BY REGION, 2024–2031 (USD MILLION) 181.
TABLE 71 AI IN DRUG DISCOVERY MARKET, BY END USER, 2024–2031 (USD MILLION) 183.
TABLE 72 PHARMACEUTICAL & BIOTECHNOLOGY COMPANIES: AI IN DRUG DISCOVERY MARKET, BY TYPE, 2024–2031 (USD MILLION) 184.
TABLE 73 PHARMACEUTICAL & BIOTECHNOLOGY COMPANIES: AI IN DRUG DISCOVERY MARKET, BY REGION, 2024–2031 (USD MILLION) 184.
TABLE 74 LARGE PHARMACEUTICAL COMPANIES: AI IN DRUG DISCOVERY MARKET, BY REGION, 2024–2031 (USD MILLION) 185.
TABLE 75 SMALL & MID-SIZED BIOTECHNOLOGY COMPANIES: AI IN DRUG DISCOVERY MARKET, BY REGION, 2024–2031 (USD MILLION) 186.
TABLE 76 CROS & CDMOS: AI IN DRUG DISCOVERY MARKET, BY REGION, 2024–2031 (USD MILLION) 188.
TABLE 77 RESEARCH CENTERS, ACADEMIC INSTITUTES, AND GOVERNMENT ORGANIZATIONS: AI IN DRUG DISCOVERY MARKET, BY REGION, 2024–2031 (USD MILLION) 189.
TABLE 78 AI IN DRUG DISCOVERY MARKET, BY USE CASE, 2024–2031 (USD MILLION) 191.
TABLE 79 UNDERSTANDING DISEASE BIOLOGY: AI IN DRUG DISCOVERY MARKET, BY TYPE, 2024–2031 (USD MILLION) 193.
TABLE 80 UNDERSTANDING DISEASE BIOLOGY: AI IN DRUG DISCOVERY MARKET, BY REGION, 2024–2031 (USD MILLION) 194.
TABLE 81 EVIDENCE SYNTHESIS AND SCIENTIFIC LITERATURE INTELLIGENCE: AI IN DRUG DISCOVERY MARKET, BY REGION, 2024–2031 (USD MILLION) 195.
TABLE 82 MULTIOMICS INTEGRATION & TARGET DISEASE ASSOCIATION: AI IN DRUG DISCOVERY MARKET, BY REGION, 2024–2031 (USD MILLION) 196.
TABLE 83 EXPERIMENT DESIGN & REAGENT/MODEL SELECTION: AI IN DRUG DISCOVERY MARKET, BY REGION, 2024–2031 (USD MILLION) 197.
TABLE 84 PROTEIN STRUCTURE & INTERACTION PREDICTION: AI IN DRUG DISCOVERY MARKET, BY REGION, 2024–2031 (USD MILLION) 198.
TABLE 85 DRUG REPURPOSING: AI IN DRUG DISCOVERY MARKET, BY REGION, 2024–2031 (USD MILLION) 199.
TABLE 86 DE NOVO DRUG DESIGN: AI IN DRUG DISCOVERY MARKET, BY TYPE, 2024–2031 (USD MILLION) 200.
TABLE 87 DE NOVO DRUG DESIGN: AI IN DRUG DISCOVERY MARKET, BY REGION, 2024–2031 (USD MILLION) 200.
TABLE 88 SMALL MOLECULE DESIGN: AI IN DRUG DISCOVERY MARKET, BY REGION, 2024–2031 (USD MILLION) 201.
TABLE 89 VACCINE DESIGN: AI IN DRUG DISCOVERY MARKET, BY REGION, 2024–2031 (USD MILLION) 202.
TABLE 90 ANTIBODY & OTHER BIOLOGICS DESIGN: AI IN DRUG DISCOVERY MARKET, BY REGION, 2024–2031 (USD MILLION) 203.
TABLE 91 PROTEIN & ENZYME DESIGN: AI IN DRUG DISCOVERY MARKET, BY REGION, 2024–2031 (USD MILLION) 204.
TABLE 92 DRUG OPTIMIZATION: AI IN DRUG DISCOVERY MARKET, BY TYPE, 2024–2031 (USD MILLION) 205.
TABLE 93 DRUG OPTIMIZATION: AI IN DRUG DISCOVERY MARKET, BY REGION, 2024–2031 (USD MILLION) 205.
TABLE 94 SMALL MOLECULE OPTIMIZATION: AI IN DRUG DISCOVERY MARKET, BY REGION, 2024–2031 (USD MILLION) 206.
TABLE 95 VACCINE OPTIMIZATION: AI IN DRUG DISCOVERY MARKET, BY REGION, 2024–2031 (USD MILLION) 207.
TABLE 96 ANTIBODY & OTHER BIOLOGICS OPTIMIZATION: AI IN DRUG DISCOVERY MARKET, BY REGION, 2024–2031 (USD MILLION) 208.
TABLE 97 SAFETY & TOXICITY: AI IN DRUG DISCOVERY MARKET, BY REGION, 2024–2031 (USD MILLION) 210.
TABLE 98 AI IN DRUG DISCOVERY MARKET, BY DEPLOYMENT, 2024–2031 (USD MILLION) 212.
TABLE 99 ON-PREMISE SOLUTIONS: AI IN DRUG DISCOVERY MARKET, BY REGION, 2024–2031 (USD MILLION) 213.
TABLE 100 CLOUD-BASED SOLUTIONS: AI IN DRUG DISCOVERY MARKET, BY TYPE, 2024–2031 (USD MILLION) 214.
TABLE 101 CLOUD-BASED SOLUTIONS: AI IN DRUG DISCOVERY MARKET, BY REGION, 2024–2031 (USD MILLION) 214.
TABLE 102 PUBLIC DEPLOYMENT: AI IN DRUG DISCOVERY MARKET, BY REGION, 2024–2031 (USD MILLION) 215.
TABLE 103 PRIVATE CLOUD/VPC/SOVEREIGN DEPLOYMENT: AI IN DRUG DISCOVERY MARKET, BY REGION, 2024–2031 (USD MILLION) 216.
TABLE 104 HYBRID SOLUTIONS: AI IN DRUG DISCOVERY MARKET, BY REGION, 2024–2031 (USD MILLION) 217.
TABLE 105 AI IN DRUG DISCOVERY MARKET, BY THERAPEUTIC AREA, 2024–2031 (USD MILLION) 219.
TABLE 106 ONCOLOGY: AI IN DRUG DISCOVERY MARKET, BY REGION, 2024–2031 (USD MILLION) 220.
TABLE 107 INFECTIOUS DISEASES: AI IN DRUG DISCOVERY MARKET, BY REGION, 2024–2031 (USD MILLION) 221.
TABLE 108 NEUROLOGY: AI IN DRUG DISCOVERY MARKET, BY REGION, 2024–2031 (USD MILLION) 222.
TABLE 109 CARDIOVASCULAR DISEASES: AI IN DRUG DISCOVERY MARKET, BY REGION, 2024–2031 (USD MILLION) 224.
TABLE 110 METABOLIC DISEASES: AI IN DRUG DISCOVERY MARKET, BY REGION, 2024–2031 (USD MILLION) 225.
TABLE 111 IMMUNOLOGY: AI IN DRUG DISCOVERY MARKET, BY REGION, 2024–2031 (USD MILLION) 226.
TABLE 112 RARE & GENETIC DISORDERS: AI IN DRUG DISCOVERY MARKET, BY REGION, 2024–2031 (USD MILLION) 227.
TABLE 113 MENTAL DISORDERS: AI IN DRUG DISCOVERY MARKET, BY REGION, 2024–2031 (USD MILLION) 228.
TABLE 114 OTHER THERAPEUTIC AREAS: AI IN DRUG DISCOVERY MARKET, BY REGION, 2024–2031 (USD MILLION) 229.
TABLE 115 AI IN DRUG DISCOVERY MARKET, BY PLAYER TYPE, 2024–2031 (USD MILLION) 231.
TABLE 116 END-TO-END SOLUTION PROVIDERS: AI IN DRUG DISCOVERY MARKET, BY REGION, 2024–2031 (USD MILLION) 232.
TABLE 117 NICHE/POINT SOLUTION PROVIDERS: AI IN DRUG DISCOVERY MARKET, BY REGION, 2024–2031 (USD MILLION) 233.
TABLE 118 AI TECHNOLOGY PROVIDERS: AI IN DRUG DISCOVERY MARKET, BY REGION, 2024–2031 (USD MILLION) 234.
TABLE 119 COMPUTE & INFRASTRUCTURE PROVIDERS: AI IN DRUG DISCOVERY MARKET, BY REGION, 2024–2031 (USD MILLION) 235.
TABLE 120 BUSINESS PROCESS SERVICE PROVIDERS: AI IN DRUG DISCOVERY MARKET, BY REGION, 2024–2031 (USD MILLION) 236.
TABLE 121 AI IN DRUG DISCOVERY MARKET, BY REGION, 2024–2031 (USD MILLION) 238.
TABLE 122 NORTH AMERICA: AI IN DRUG DISCOVERY MARKET, BY COUNTRY, 2024–2031 (USD MILLION) 240.
TABLE 123 NORTH AMERICA: AI IN DRUG DISCOVERY MARKET, BY PROCESS, 2024–2031 (USD MILLION) 240.
TABLE 124 NORTH AMERICA: AI IN DRUG DISCOVERY MARKET, BY USE CASE, 2024–2031 (USD MILLION) 241.
TABLE 125 NORTH AMERICA: AI IN DRUG DISCOVERY MARKET FOR UNDERSTANDING DISEASES, BY TYPE, 2024–2031 (USD MILLION) 241.
TABLE 126 NORTH AMERICA: AI IN DRUG DISCOVERY MARKET FOR DE NOVO DRUG DESIGN, BY TYPE, 2024–2031 (USD MILLION) 242.
TABLE 127 NORTH AMERICA: AI IN DRUG DISCOVERY MARKET FOR DRUG OPTIMIZATION, BY TYPE, 2024–2031 (USD MILLION) 242.
TABLE 128 NORTH AMERICA: AI IN DRUG DISCOVERY MARKET, BY THERAPEUTIC AREA, 2024–2031 (USD MILLION) 243.
TABLE 129 NORTH AMERICA: AI IN DRUG DISCOVERY MARKET, BY PLAYER TYPE, 2024–2031 (USD MILLION) 243.
TABLE 130 NORTH AMERICA: AI IN DRUG DISCOVERY MARKET, BY AI TOOL, 2024–2031 (USD MILLION) 244.
TABLE 131 NORTH AMERICA: MACHINE LEARNING IN AI IN DRUG DISCOVERY MARKET, BY TYPE, 2024–2031 (USD MILLION) 244.
TABLE 132 NORTH AMERICA: DEEP LEARNING IN AI IN DRUG DISCOVERY MARKET, BY TYPE, 2024–2031 (USD MILLION) 245.
TABLE 133 NORTH AMERICA: GENERATIVE AI IN AI IN DRUG DISCOVERY MARKET, BY TYPE, 2024–2031 (USD MILLION) 245.
TABLE 134 NORTH AMERICA: FOUNDATION MODELS IN AI IN DRUG DISCOVERY MARKET, BY TYPE, 2024–2031 (USD MILLION) 246.
TABLE 135 NORTH AMERICA: AGENTIC AI & CO-SCIENTISTS IN AI IN DRUG DISCOVERY MARKET, BY TYPE, 2024–2031 (USD MILLION) 246.
TABLE 136 NORTH AMERICA: AI IN DRUG DISCOVERY MARKET, BY DEPLOYMENT, 2024–2031 (USD MILLION) 247.
TABLE 137 NORTH AMERICA: CLOUD-BASED SOLUTIONS IN AI IN DRUG DISCOVERY MARKET, BY TYPE, 2024–2031 (USD MILLION) 247.
TABLE 138 NORTH AMERICA: AI IN DRUG DISCOVERY MARKET, BY END USER, 2024–2031 (USD MILLION) 247.
TABLE 139 NORTH AMERICA: PHARMACEUTICAL & BIOTECHNOLOGY COMPANIES IN AI IN DRUG DISCOVERY MARKET, BY TYPE, 2024–2031 (USD MILLION) 248.
TABLE 140 US: AI IN DRUG DISCOVERY MARKET, BY PROCESS, 2024–2031 (USD MILLION) 249.
TABLE 141 US: AI IN DRUG DISCOVERY MARKET, BY USE CASE, 2024–2031 (USD MILLION) 250.
TABLE 142 US: AI IN DRUG DISCOVERY MARKET FOR UNDERSTANDING DISEASES, BY TYPE, 2024–2031 (USD MILLION) 250.
TABLE 143 US: AI IN DRUG DISCOVERY MARKET FOR DE NOVO DRUG DESIGN, BY TYPE, 2024–2031 (USD MILLION) 251.
TABLE 144 US: AI IN DRUG DISCOVERY MARKET FOR DRUG OPTIMIZATION, BY TYPE, 2024–2031 (USD MILLION) 251.
TABLE 145 US: AI IN DRUG DISCOVERY MARKET, BY THERAPEUTIC AREA, 2024–2031 (USD MILLION) 252.
TABLE 146 US: AI IN DRUG DISCOVERY MARKET, BY PLAYER TYPE, 2024–2031 (USD MILLION) 252.
TABLE 147 US: AI IN DRUG DISCOVERY MARKET, BY AI TOOL, 2024–2031 (USD MILLION) 253.
TABLE 148 US: MACHINE LEARNING IN AI IN DRUG DISCOVERY MARKET, BY TYPE, 2024–2031 (USD MILLION) 253.
TABLE 149 US: DEEP LEARNING IN AI IN DRUG DISCOVERY MARKET, BY TYPE, 2024–2031 (USD MILLION) 254.
TABLE 150 US: GENERATIVE AI IN AI IN DRUG DISCOVERY MARKET, BY TYPE, 2024–2031 (USD MILLION) 254.
TABLE 151 US: FOUNDATION MODELS IN AI IN DRUG DISCOVERY MARKET, BY TYPE, 2024–2031 (USD MILLION) 255.
TABLE 152 US: AGENTIC AI & CO-SCIENTISTS IN AI IN DRUG DISCOVERY MARKET, BY TYPE, 2024–2031 (USD MILLION) 255.
TABLE 153 US: AI IN DRUG DISCOVERY MARKET, BY DEPLOYMENT, 2024–2031 (USD MILLION) 255.
TABLE 154 US: CLOUD-BASED SOLUTIONS IN AI IN DRUG DISCOVERY MARKET, BY TYPE, 2024–2031 (USD MILLION) 256.
TABLE 155 US: AI IN DRUG DISCOVERY MARKET, BY END USER, 2024–2031 (USD MILLION) 256.
TABLE 156 US: PHARMACEUTICAL & BIOTECHNOLOGY COMPANIES IN AI IN DRUG DISCOVERY MARKET, BY TYPE, 2024–2031 (USD MILLION) 256.
TABLE 157 CANADA: AI IN DRUG DISCOVERY MARKET, BY PROCESS, 2024–2031 (USD MILLION) 257.
TABLE 158 CANADA: AI IN DRUG DISCOVERY MARKET, BY USE CASE, 2024–2031 (USD MILLION) 258.
TABLE 159 CANADA: AI IN DRUG DISCOVERY MARKET FOR UNDERSTANDING DISEASES, BY TYPE, 2024–2031 (USD MILLION) 258.
TABLE 160 CANADA: AI IN DRUG DISCOVERY MARKET FOR DE NOVO DRUG DESIGN, BY TYPE, 2024–2031 (USD MILLION) 259.
TABLE 161 CANADA: AI IN DRUG DISCOVERY MARKET FOR DRUG OPTIMIZATION, BY TYPE, 2024–2031 (USD MILLION) 259.
TABLE 162 CANADA: AI IN DRUG DISCOVERY MARKET, BY THERAPEUTIC AREA, 2024–2031 (USD MILLION) 260.
TABLE 163 CANADA: AI IN DRUG DISCOVERY MARKET, BY PLAYER TYPE, 2024–2031 (USD MILLION) 260.
TABLE 164 CANADA: AI IN DRUG DISCOVERY MARKET, BY AI TOOL, 2024–2031 (USD MILLION) 261.
TABLE 165 CANADA: MACHINE LEARNING IN AI IN DRUG DISCOVERY MARKET, BY TYPE, 2024–2031 (USD MILLION) 261.
TABLE 166 CANADA: DEEP LEARNING IN AI IN DRUG DISCOVERY MARKET, BY TYPE, 2024–2031 (USD MILLION) 262.
TABLE 167 CANADA: GENERATIVE AI IN AI IN DRUG DISCOVERY MARKET, BY TYPE, 2024–2031 (USD MILLION) 262.
TABLE 168 CANADA: FOUNDATION MODELS IN AI IN DRUG DISCOVERY MARKET, BY TYPE, 2024–2031 (USD MILLION) 263.
TABLE 169 CANADA: AGENTIC AI & CO-SCIENTISTS IN AI IN DRUG DISCOVERY MARKET, BY TYPE, 2024–2031 (USD MILLION) 263.
TABLE 170 CANADA: AI IN DRUG DISCOVERY MARKET, BY DEPLOYMENT, 2024–2031 (USD MILLION) 263.
TABLE 171 CANADA: CLOUD-BASED SOLUTIONS IN AI IN DRUG DISCOVERY MARKET, BY TYPE, 2024–2031 (USD MILLION) 264.
TABLE 172 CANADA: AI IN DRUG DISCOVERY MARKET, BY END USER, 2024–2031 (USD MILLION) 264.
TABLE 173 CANADA: PHARMACEUTICAL & BIOTECHNOLOGY COMPANIES IN AI IN DRUG DISCOVERY MARKET, BY TYPE, 2024–2031 (USD MILLION) 264.
TABLE 174 EUROPE: AI IN DRUG DISCOVERY MARKET, BY COUNTRY, 2024–2031 (USD MILLION) 266.
TABLE 175 EUROPE: AI IN DRUG DISCOVERY MARKET, BY PROCESS, 2024–2031 (USD MILLION) 267.
TABLE 176 EUROPE: AI IN DRUG DISCOVERY MARKET, BY USE CASE, 2024–2031 (USD MILLION) 267.
TABLE 177 EUROPE: AI IN DRUG DISCOVERY MARKET FOR UNDERSTANDING DISEASES, BY TYPE, 2024–2031 (USD MILLION) 268.
TABLE 178 EUROPE: AI IN DRUG DISCOVERY MARKET FOR DE NOVO DRUG DESIGN, BY TYPE, 2024–2031 (USD MILLION) 268.
TABLE 179 EUROPE: AI IN DRUG DISCOVERY MARKET FOR DRUG OPTIMIZATION, BY TYPE, 2024–2031 (USD MILLION) 269.
TABLE 180 EUROPE: AI IN DRUG DISCOVERY MARKET, BY THERAPEUTIC AREA, 2024–2031 (USD MILLION) 269.
TABLE 181 EUROPE: AI IN DRUG DISCOVERY MARKET, BY PLAYER TYPE, 2024–2031 (USD MILLION) 270.
TABLE 182 EUROPE: AI IN DRUG DISCOVERY MARKET, BY AI TOOL, 2024–2031 (USD MILLION) 270.
TABLE 183 EUROPE: MACHINE LEARNING IN AI IN DRUG DISCOVERY MARKET, BY TYPE, 2024–2031 (USD MILLION) 271.
TABLE 184 EUROPE: DEEP LEARNING IN AI IN DRUG DISCOVERY MARKET, BY TYPE, 2024–2031 (USD MILLION) 271.
TABLE 185 EUROPE: GENERATIVE AI IN AI IN DRUG DISCOVERY MARKET, BY TYPE, 2024–2031 (USD MILLION) 272.
TABLE 186 EUROPE: FOUNDATION MODELS IN AI IN DRUG DISCOVERY MARKET, BY TYPE, 2024–2031 (USD MILLION) 272.
TABLE 187 EUROPE: AGENTIC AI & CO-SCIENTISTS MARKET, BY TYPE, 2024–2031 (USD MILLION) 272.
TABLE 188 EUROPE: AI IN DRUG DISCOVERY MARKET, BY DEPLOYMENT, 2024–2031 (USD MILLION) 273.
TABLE 189 EUROPE: CLOUD-BASED SOLUTIONS IN AI IN DRUG DISCOVERY MARKET, BY TYPE, 2024–2031 (USD MILLION) 273.
TABLE 190 EUROPE: AI IN DRUG DISCOVERY MARKET, BY END USER, 2024–2031 (USD MILLION) 273.
TABLE 191 EUROPE: PHARMACEUTICAL & BIOTECHNOLOGY COMPANIES IN AI IN DRUG DISCOVERY MARKET, BY TYPE, 2024–2031 (USD MILLION) 274.
TABLE 192 GERMANY: AI IN DRUG DISCOVERY MARKET, BY PROCESS, 2024–2031 (USD MILLION) 275.
TABLE 193 GERMANY: AI IN DRUG DISCOVERY MARKET, BY USE CASE, 2024–2031 (USD MILLION) 275.
TABLE 194 GERMANY: AI IN DRUG DISCOVERY MARKET FOR UNDERSTANDING DISEASES, BY TYPE, 2024–2031 (USD MILLION) 276.
TABLE 195 GERMANY: AI IN DRUG DISCOVERY MARKET FOR DE NOVO DRUG DESIGN, BY TYPE, 2024–2031 (USD MILLION) 276.
TABLE 196 GERMANY: AI IN DRUG DISCOVERY MARKET FOR DRUG OPTIMIZATION, BY TYPE, 2024–2031 (USD MILLION) 277.
TABLE 197 GERMANY: AI IN DRUG DISCOVERY MARKET, BY THERAPEUTIC AREA, 2024–2031 (USD MILLION) 277.
TABLE 198 GERMANY: AI IN DRUG DISCOVERY MARKET, BY PLAYER TYPE, 2024–2031 (USD MILLION) 278.
TABLE 199 GERMANY: AI IN DRUG DISCOVERY MARKET, BY AI TOOL, 2024–2031 (USD MILLION) 278.
TABLE 200 GERMANY: MACHINE LEARNING IN AI IN DRUG DISCOVERY MARKET, BY TYPE, 2024–2031 (USD MILLION) 279.
TABLE 201 GERMANY: DEEP LEARNING IN AI IN DRUG DISCOVERY MARKET, BY TYPE, 2024–2031 (USD MILLION) 279.
TABLE 202 GERMANY: GENERATIVE AI IN AI IN DRUG DISCOVERY MARKET, BY TYPE, 2024–2031 (USD MILLION) 280.
TABLE 203 GERMANY: FOUNDATION MODELS IN AI IN DRUG DISCOVERY MARKET, BY TYPE, 2024–2031 (USD MILLION) 280.
TABLE 204 GERMANY: AGENTIC AI & CO-SCIENTISTS MARKET, BY TYPE, 2024–2031 (USD MILLION) 280.
TABLE 205 GERMANY: AI IN DRUG DISCOVERY MARKET, BY DEPLOYMENT, 2024–2031 (USD MILLION) 281.
TABLE 206 GERMANY: CLOUD-BASED SOLUTIONS IN AI IN DRUG DISCOVERY MARKET, BY TYPE, 2024–2031 (USD MILLION) 281.
TABLE 207 GERMANY: AI IN DRUG DISCOVERY MARKET, BY END USER, 2024–2031 (USD MILLION) 281.
TABLE 208 GERMANY: PHARMACEUTICAL & BIOTECHNOLOGY COMPANIES IN AI IN DRUG DISCOVERY MARKET, BY TYPE, 2024–2031 (USD MILLION) 282.
TABLE 209 UK: AI IN DRUG DISCOVERY MARKET, BY PROCESS, 2024–2031 (USD MILLION) 283.
TABLE 210 UK: AI IN DRUG DISCOVERY MARKET, BY USE CASE, 2024–2031 (USD MILLION) 283.
TABLE 211 UK: AI IN DRUG DISCOVERY MARKET FOR UNDERSTANDING DISEASES, BY TYPE, 2024–2031 (USD MILLION) 284.
TABLE 212 UK: AI IN DRUG DISCOVERY MARKET FOR DE NOVO DRUG DESIGN, BY TYPE, 2024–2031 (USD MILLION) 284.
TABLE 213 UK: AI IN DRUG DISCOVERY MARKET FOR DRUG OPTIMIZATION, BY TYPE, 2024–2031 (USD MILLION) 285.
TABLE 214 UK: AI IN DRUG DISCOVERY MARKET, BY THERAPEUTIC AREA, 2024–2031 (USD MILLION) 285.
TABLE 215 UK: AI IN DRUG DISCOVERY MARKET, BY PLAYER TYPE, 2024–2031 (USD MILLION) 286.
TABLE 216 UK: AI IN DRUG DISCOVERY MARKET, BY AI TOOL, 2024–2031 (USD MILLION) 286.
TABLE 217 UK: MACHINE LEARNING IN AI IN DRUG DISCOVERY MARKET, BY TYPE, 2024–2031 (USD MILLION) 287.
TABLE 218 UK: DEEP LEARNING IN AI IN DRUG DISCOVERY MARKET, BY TYPE, 2024–2031 (USD MILLION) 287.
TABLE 219 UK: GENERATIVE AI IN AI IN DRUG DISCOVERY MARKET, BY TYPE, 2024–2031 (USD MILLION) 288.
TABLE 220 UK: FOUNDATION MODELS IN AI IN DRUG DISCOVERY MARKET, BY TYPE, 2024–2031 (USD MILLION) 288.
TABLE 221 UK: AGENTIC AI & CO-SCIENTISTS MARKET, BY TYPE, 2024–2031 (USD MILLION) 288.
TABLE 222 UK: AI IN DRUG DISCOVERY MARKET, BY DEPLOYMENT, 2024–2031 (USD MILLION) 289.
TABLE 223 UK: CLOUD-BASED SOLUTIONS IN AI IN DRUG DISCOVERY MARKET, BY TYPE, 2024–2031 (USD MILLION) 289.
TABLE 224 UK: AI IN DRUG DISCOVERY MARKET, BY END USER, 2024–2031 (USD MILLION) 289.
TABLE 225 UK: PHARMACEUTICAL & BIOTECHNOLOGY COMPANIES IN AI IN DRUG DISCOVERY MARKET, BY TYPE, 2024–2031 (USD MILLION) 290.
TABLE 226 SWITZERLAND: AI IN DRUG DISCOVERY MARKET, BY PROCESS, 2024–2031 (USD MILLION) 291.
TABLE 227 SWITZERLAND: AI IN DRUG DISCOVERY MARKET, BY USE CASE, 2024–2031 (USD MILLION) 291.
TABLE 228 SWITZERLAND: AI IN DRUG DISCOVERY MARKET FOR UNDERSTANDING DISEASES, BY TYPE, 2024–2031 (USD MILLION) 292.
TABLE 229 SWITZERLAND: AI IN DRUG DISCOVERY MARKET FOR DE NOVO DRUG DESIGN, BY TYPE, 2024–2031 (USD MILLION) 292.
TABLE 230 SWITZERLAND: AI IN DRUG DISCOVERY MARKET FOR DRUG OPTIMIZATION, BY TYPE, 2024–2031 (USD MILLION) 293.
TABLE 231 SWITZERLAND: AI IN DRUG DISCOVERY MARKET, BY THERAPEUTIC AREA, 2024–2031 (USD MILLION) 293.
TABLE 232 SWITZERLAND: AI IN DRUG DISCOVERY MARKET, BY PLAYER TYPE, 2024–2031 (USD MILLION) 294.
TABLE 233 SWITZERLAND: AI IN DRUG DISCOVERY MARKET, BY AI TOOL, 2024–2031 (USD MILLION) 294.
TABLE 234 SWITZERLAND: MACHINE LEARNING IN AI IN DRUG DISCOVERY MARKET, BY TYPE, 2024–2031 (USD MILLION) 295.
TABLE 235 SWITZERLAND: DEEP LEARNING IN AI IN DRUG DISCOVERY MARKET, BY TYPE, 2024–2031 (USD MILLION) 295.
TABLE 236 SWITZERLAND: GENERATIVE AI IN AI IN DRUG DISCOVERY MARKET, BY TYPE, 2024–2031 (USD MILLION) 296.
TABLE 237 SWITZERLAND: FOUNDATION MODELS IN AI IN DRUG DISCOVERY MARKET, BY TYPE, 2024–2031 (USD MILLION) 296.
TABLE 238 SWITZERLAND: AGENTIC AI & CO-SCIENTISTS MARKET, BY TYPE, 2024–2031 (USD MILLION) 296.
TABLE 239 SWITZERLAND: AI IN DRUG DISCOVERY MARKET, BY DEPLOYMENT, 2024–2031 (USD MILLION) 297.
TABLE 240 SWITZERLAND: CLOUD-BASED SOLUTIONS IN AI IN DRUG DISCOVERY MARKET, BY TYPE, 2024–2031 (USD MILLION) 297.
TABLE 241 SWITZERLAND: AI IN DRUG DISCOVERY MARKET, BY END USER, 2024–2031 (USD MILLION) 297.
TABLE 242 SWITZERLAND: PHARMACEUTICAL & BIOTECHNOLOGY COMPANIES IN AI IN DRUG DISCOVERY MARKET, BY TYPE, 2024–2031 (USD MILLION) 298.
TABLE 243 FRANCE: AI IN DRUG DISCOVERY MARKET, BY PROCESS, 2024–2031 (USD MILLION) 299.
TABLE 244 FRANCE: AI IN DRUG DISCOVERY MARKET, BY USE CASE, 2024–2031 (USD MILLION) 299.
TABLE 245 FRANCE: AI IN DRUG DISCOVERY MARKET FOR UNDERSTANDING DISEASES, BY TYPE, 2024–2031 (USD MILLION) 300.
TABLE 246 FRANCE: AI IN DRUG DISCOVERY MARKET FOR DE NOVO DRUG DESIGN, BY TYPE, 2024–2031 (USD MILLION) 300.
TABLE 247 FRANCE: AI IN DRUG DISCOVERY MARKET FOR DRUG OPTIMIZATION, BY TYPE, 2024–2031 (USD MILLION) 301.
TABLE 248 FRANCE: AI IN DRUG DISCOVERY MARKET, BY THERAPEUTIC AREA, 2024–2031 (USD MILLION) 301.
TABLE 249 FRANCE: AI IN DRUG DISCOVERY MARKET, BY PLAYER TYPE, 2024–2031 (USD MILLION) 302.
TABLE 250 FRANCE: AI IN DRUG DISCOVERY MARKET, BY AI TOOL, 2024–2031 (USD MILLION) 302.
TABLE 251 FRANCE: MACHINE LEARNING IN AI IN DRUG DISCOVERY MARKET, BY TYPE, 2024–2031 (USD MILLION) 303.
TABLE 252 FRANCE: DEEP LEARNING IN AI IN DRUG DISCOVERY MARKET, BY TYPE, 2024–2031 (USD MILLION) 303.
TABLE 253 FRANCE: GENERATIVE AI IN AI IN DRUG DISCOVERY MARKET, BY TYPE, 2024–2031 (USD MILLION) 304.
TABLE 254 FRANCE: FOUNDATION MODELS IN AI IN DRUG DISCOVERY MARKET, BY TYPE, 2024–2031 (USD MILLION) 304.
TABLE 255 FRANCE: AGENTIC AI & CO-SCIENTISTS MARKET, BY TYPE, 2024–2031 (USD MILLION) 304.
TABLE 256 FRANCE: AI IN DRUG DISCOVERY MARKET, BY DEPLOYMENT, 2024–2031 (USD MILLION) 305.
TABLE 257 FRANCE: CLOUD-BASED SOLUTIONS IN AI IN DRUG DISCOVERY MARKET, BY TYPE, 2024–2031 (USD MILLION) 305.
TABLE 258 FRANCE: AI IN DRUG DISCOVERY MARKET, BY END USER, 2024–2031 (USD MILLION) 305.
TABLE 259 FRANCE: PHARMACEUTICAL & BIOTECHNOLOGY COMPANIES IN AI IN DRUG DISCOVERY MARKET, BY TYPE, 2024–2031 (USD MILLION) 306.
TABLE 260 ITALY: AI IN DRUG DISCOVERY MARKET, BY PROCESS, 2024–2031 (USD MILLION) 307.
TABLE 261 ITALY: AI IN DRUG DISCOVERY MARKET, BY USE CASE, 2024–2031 (USD MILLION) 307.
TABLE 262 ITALY: AI IN DRUG DISCOVERY MARKET FOR UNDERSTANDING DISEASES, BY TYPE, 2024–2031 (USD MILLION) 308.
TABLE 263 ITALY: AI IN DRUG DISCOVERY MARKET FOR DE NOVO DRUG DESIGN, BY TYPE, 2024–2031 (USD MILLION) 308.
TABLE 264 ITALY: AI IN DRUG DISCOVERY MARKET FOR DRUG OPTIMIZATION, BY TYPE, 2024–2031 (USD MILLION) 309.
TABLE 265 ITALY: AI IN DRUG DISCOVERY MARKET, BY THERAPEUTIC AREA, 2024–2031 (USD MILLION) 309.
TABLE 266 ITALY: AI IN DRUG DISCOVERY MARKET, BY PLAYER TYPE, 2024–2031 (USD MILLION) 310.
TABLE 267 ITALY: AI IN DRUG DISCOVERY MARKET, BY AI TOOL, 2024–2031 (USD MILLION) 310.
TABLE 268 ITALY: MACHINE LEARNING IN AI IN DRUG DISCOVERY MARKET, BY TYPE, 2024–2031 (USD MILLION) 311.
TABLE 269 ITALY: DEEP LEARNING IN AI IN DRUG DISCOVERY MARKET, BY TYPE, 2024–2031 (USD MILLION) 311.
TABLE 270 ITALY: GENERATIVE AI IN AI IN DRUG DISCOVERY MARKET, BY TYPE, 2024–2031 (USD MILLION) 312.
TABLE 271 ITALY: FOUNDATION MODELS IN AI IN DRUG DISCOVERY MARKET, BY TYPE, 2024–2031 (USD MILLION) 312.
TABLE 272 ITALY: AGENTIC AI & CO-SCIENTISTS MARKET, BY TYPE, 2024–2031 (USD MILLION) 312.
TABLE 273 ITALY: AI IN DRUG DISCOVERY MARKET, BY DEPLOYMENT, 2024–2031 (USD MILLION) 313.
TABLE 274 ITALY: CLOUD-BASED SOLUTIONS IN AI IN DRUG DISCOVERY MARKET, BY TYPE, 2024–2031 (USD MILLION) 313.
TABLE 275 ITALY: AI IN DRUG DISCOVERY MARKET, BY END USER, 2024–2031 (USD MILLION) 313.
TABLE 276 ITALY: PHARMACEUTICAL & BIOTECHNOLOGY COMPANIES IN AI IN DRUG DISCOVERY MARKET, BY TYPE, 2024–2031 (USD MILLION) 314.
TABLE 277 SPAIN: AI IN DRUG DISCOVERY MARKET, BY PROCESS, 2024–2031 (USD MILLION) 315.
TABLE 278 SPAIN: AI IN DRUG DISCOVERY MARKET, BY USE CASE, 2024–2031 (USD MILLION) 315.
TABLE 279 SPAIN: AI IN DRUG DISCOVERY MARKET FOR UNDERSTANDING DISEASES, BY TYPE, 2024–2031 (USD MILLION) 316.
TABLE 280 SPAIN: AI IN DRUG DISCOVERY MARKET FOR DE NOVO DRUG DESIGN, BY TYPE, 2024–2031 (USD MILLION) 316.
TABLE 281 SPAIN: AI IN DRUG DISCOVERY MARKET FOR DRUG OPTIMIZATION, BY TYPE, 2024–2031 (USD MILLION) 317.
TABLE 282 SPAIN: AI IN DRUG DISCOVERY MARKET, BY THERAPEUTIC AREA, 2024–2031 (USD MILLION) 317.
TABLE 283 SPAIN: AI IN DRUG DISCOVERY MARKET, BY PLAYER TYPE, 2024–2031 (USD MILLION) 318.
TABLE 284 SPAIN: AI IN DRUG DISCOVERY MARKET, BY AI TOOL, 2024–2031 (USD MILLION) 318.
TABLE 285 SPAIN: MACHINE LEARNING IN AI IN DRUG DISCOVERY MARKET, BY TYPE, 2024–2031 (USD MILLION) 319.
TABLE 286 SPAIN: DEEP LEARNING IN AI IN DRUG DISCOVERY MARKET, BY TYPE, 2024–2031 (USD MILLION) 319.
TABLE 287 SPAIN: GENERATIVE AI IN AI IN DRUG DISCOVERY MARKET, BY TYPE, 2024–2031 (USD MILLION) 320.
TABLE 288 SPAIN: FOUNDATION MODELS IN AI IN DRUG DISCOVERY MARKET, BY TYPE, 2024–2031 (USD MILLION) 320.
TABLE 289 SPAIN: AGENTIC AI & CO-SCIENTISTS MARKET, BY TYPE, 2024–2031 (USD MILLION) 320.
TABLE 290 SPAIN: AI IN DRUG DISCOVERY MARKET, BY DEPLOYMENT, 2024–2031 (USD MILLION) 321.
TABLE 291 SPAIN: CLOUD-BASED SOLUTIONS IN AI IN DRUG DISCOVERY MARKET, BY TYPE, 2024–2031 (USD MILLION) 321.
TABLE 292 SPAIN: AI IN DRUG DISCOVERY MARKET, BY END USER, 2024–2031 (USD MILLION) 321.
TABLE 293 SPAIN: PHARMACEUTICAL & BIOTECHNOLOGY COMPANIES IN AI IN DRUG DISCOVERY MARKET, BY TYPE, 2024–2031 (USD MILLION) 322.
TABLE 294 REST OF EUROPE: AI IN DRUG DISCOVERY MARKET, BY PROCESS, 2024–2031 (USD MILLION) 323.
TABLE 295 REST OF EUROPE: AI IN DRUG DISCOVERY MARKET, BY USE CASE, 2024–2031 (USD MILLION) 323.
TABLE 296 REST OF EUROPE: AI IN DRUG DISCOVERY MARKET FOR UNDERSTANDING DISEASES, BY TYPE, 2024–2031 (USD MILLION) 324.
TABLE 297 REST OF EUROPE: AI IN DRUG DISCOVERY MARKET FOR DE NOVO DRUG DESIGN, BY TYPE, 2024–2031 (USD MILLION) 324.
TABLE 298 REST OF EUROPE: AI IN DRUG DISCOVERY MARKET FOR DRUG OPTIMIZATION, BY TYPE, 2024–2031 (USD MILLION) 325.
TABLE 299 REST OF EUROPE: AI IN DRUG DISCOVERY MARKET, BY THERAPEUTIC AREA, 2024–2031 (USD MILLION) 325.
TABLE 300 REST OF EUROPE: AI IN DRUG DISCOVERY MARKET, BY PLAYER TYPE, 2024–2031 (USD MILLION) 326.
TABLE 301 REST OF EUROPE: AI IN DRUG DISCOVERY MARKET, BY AI TOOL, 2024–2031 (USD MILLION) 326.
TABLE 302 REST OF EUROPE: MACHINE LEARNING IN AI IN DRUG DISCOVERY MARKET, BY TYPE, 2024–2031 (USD MILLION) 327.
TABLE 303 REST OF EUROPE: DEEP LEARNING IN AI IN DRUG DISCOVERY MARKET, BY TYPE, 2024–2031 (USD MILLION) 327.
TABLE 304 REST OF EUROPE: GENERATIVE AI IN AI IN DRUG DISCOVERY MARKET, BY TYPE, 2024–2031 (USD MILLION) 328.
TABLE 305 REST OF EUROPE: FOUNDATION MODELS IN AI IN DRUG DISCOVERY MARKET, BY TYPE, 2024–2031 (USD MILLION) 328.
TABLE 306 REST OF EUROPE: AGENTIC AI & CO-SCIENTISTS MARKET, BY TYPE, 2024–2031 (USD MILLION) 328.
TABLE 307 REST OF EUROPE: AI IN DRUG DISCOVERY MARKET, BY DEPLOYMENT, 2024–2031 (USD MILLION) 329.
TABLE 308 REST OF EUROPE: CLOUD-BASED SOLUTIONS IN AI IN DRUG DISCOVERY MARKET, BY TYPE, 2024–2031 (USD MILLION) 329.
TABLE 309 REST OF EUROPE: AI IN DRUG DISCOVERY MARKET, BY END USER, 2024–2031 (USD MILLION) 329.
TABLE 310 REST OF EUROPE: PHARMACEUTICAL & BIOTECHNOLOGY COMPANIES IN AI IN DRUG DISCOVERY MARKET, BY TYPE, 2024–2031 (USD MILLION) 330.
TABLE 311 ASIA PACIFIC: AI IN DRUG DISCOVERY MARKET, BY COUNTRY, 2024–2031 (USD MILLION) 332.
TABLE 312 ASIA PACIFIC: AI IN DRUG DISCOVERY MARKET, BY PROCESS, 2024–2031 (USD MILLION) 333.
TABLE 313 ASIA PACIFIC: AI IN DRUG DISCOVERY MARKET, BY USE CASE, 2024–2031 (USD MILLION) 333.
TABLE 314 ASIA PACIFIC: AI IN DRUG DISCOVERY MARKET FOR UNDERSTANDING DISEASES, BY TYPE, 2024–2031 (USD MILLION) 334.
TABLE 315 ASIA PACIFIC: AI IN DRUG DISCOVERY MARKET FOR DE NOVO DRUG DESIGN, BY TYPE, 2024–2031 (USD MILLION) 334.
TABLE 316 ASIA PACIFIC: AI IN DRUG DISCOVERY MARKET FOR DRUG OPTIMIZATION, BY TYPE, 2024–2031 (USD MILLION) 335.
TABLE 317 ASIA PACIFIC: AI IN DRUG DISCOVERY MARKET, BY THERAPEUTIC AREA, 2024–2031 (USD MILLION) 335.
TABLE 318 ASIA PACIFIC: AI IN DRUG DISCOVERY MARKET, BY PLAYER TYPE, 2024–2031 (USD MILLION) 336.
TABLE 319 ASIA PACIFIC: AI IN DRUG DISCOVERY MARKET, BY AI TOOL, 2024–2031 (USD MILLION) 336.
TABLE 32