Summary

The global AI in protein engineering market is projected to reach USD 3.82 billion by 2031 from USD 1.44 billion in 2026, at a CAGR of 21.6% from 2026 to 2031. Growth in the AI in protein engineering market is driven by rising pharmaceutical R&D expenditure, increasing drug development costs, and the need to improve the productivity of protein discovery and design. The 25 selected drugmakers analyzed by IntuitionLabs reported approximately USD 185 billion in combined R&D spending in 2025, with Merck & Co. spending USD 15.8 billion, Johnson & Johnson USD 14.7 billion, and Eli Lilly USD 13.3 billion. Improving returns from these investments is especially important, as the average R&D cost per approved drug asset rose from USD 2.23 billion in 2024 to USD 2.67 billion in 2025. AI is increasingly viewed as a lever to address these costs and improve the efficiency of drug discovery and development. However, adoption remains constrained by implementation complexity and uncertain ROI; 71% of life sciences executives reported AI deployment progress, but only 45% reported measurable performance gains, while 61% identified external partnerships as important for accessing AI capabilities.

In 2025, antibodies held the largest share of the market, by protein type
By protein type, antibodies represented the largest share of the AI in protein engineering market in 2025. This leadership stems from the growing development of antibody-based therapeutics and the increasing need to improve the efficiency of antibody discovery and optimization. Pharmaceutical and biotechnology companies extensively utilize AI-powered protein engineering tools for antibody sequence generation, affinity optimization, specificity prediction, developability assessment, and stability optimization. The rising focus on innovative antibody modalities, including bispecific antibodies, antibody-drug conjugates, and other next-generation biologics, has further increased demand for AI-enabled antibody engineering. Moreover, generative AI and protein language models can explore large sequence spaces, prioritize promising candidates, and reduce experimental iterations, encouraging greater adoption of AI-based antibody engineering platforms.

Protein optimization to register highest CAGR in the market, by process
By process, protein optimization is expected to be the fastest-growing segment in the AI in protein engineering market, driven by the need to improve protein activity, stability, specificity, affinity, and developability while reducing experimental iterations. AI-enabled optimization is demonstrating measurable improvements; an AI-guided closed-loop platform achieved a 57-fold increase in enzyme activity within five engineering cycles and up to 104-fold improvement for another enzyme. AI-based computational filtering has also improved experimental success rates by 50–150%, enabling faster prioritization of high-performing protein variants. These advances are expected to accelerate adoption of protein language models, generative AI, and machine-learning-based optimization across pharmaceutical, biotechnology, and industrial protein-engineering workflows.

Asia Pacific to witness the highest growth rate during the forecast period
The Asia Pacific region is projected to register the highest growth rate in the AI in protein engineering market during the forecast period, supported by the rapid development of AI-enabled protein design capabilities, expanding computational biology infrastructure, and increasing integration of AI with high-throughput experimentation. In China, researchers at Shanghai Jiao Tong University developed the Venus-Pod protein dataset, which contains more than 9 billion protein sequences, including 2.43 billion antibody sequences and 500 million functionally annotated sequences, providing a strong foundation for AI-driven protein design and optimization. The region is also advancing AI-enabled experimental workflows; an automated platform developed in China can perform more than 100 protein expression, purification, and testing tasks within 24 hours, nearly 10 times as efficiently as manual workflows. In Japan, RevolKa raised JPY 210 million (approximately USD 1.4 million) in May 2025 to advance its AI-powered aiProtein technology and therapeutic programs. Furthermore, Singapore-based research at the National University of Singapore is integrating machine learning with ultra-high-throughput sorting and next-generation sequencing to generate large-scale sequence-function datasets for AI-driven protein engineering. These developments, alongside the growing ecosystem of AI-protein engineering startups, research institutes, and automated biofoundries, are expected to accelerate adoption of generative AI, protein language models, and machine learning across protein discovery, optimization, antibody engineering, and de novo protein design in APAC.

The breakdown of primary participants is as mentioned below:
- By Company Type - Tier 1: 34%, Tier 2: 46%, and Tier 3: 20%
- By Designation - C-level: 35%, Director-level: 25%, and Others: 40%
- By Region - North America: 30%, Europe: 45%, Asia Pacific: 20%, Middle East & Africa: 3%, Latin America: 2%

Key Players in the AI in Protein Engineering Market
The key players functioning in the AI in protein engineering market include Schrödinger, Inc. (US), XtalPi (China), Dassault Systèmes (France), NVIDIA Corporation (US), Generate:Biomedicines (US), Absci Corp. (US), Insilico Medicine (US), Isomorphic Labs (UK), among others.

Research Coverage:
This research report categorizes the AI in protein engineering market by offering (software/platforms, services), by AI tool (machine learning & deep learning, protein language models, generative AI, structure-based AI, other tools), by application (next-generation biologics, molecular glues, data generation, antibody discovery and optimization, enzyme engineering, de novo protein design, protein stability and developability optimization, other applications), by protein type (antibodies, enzymes, cytokines & growth factors, peptides, fusion proteins, miniproteins, other proteins), by protein engineering process (protein discovery, protein design, protein optimization, protein characterization, experimental validation), by end user (pharmaceutical & biotechnology companies, academic & research institutes, contract research organizations, industrial biotechnology companies, other end users), and by region (North America, Europe, Asia Pacific, Latin America, and Middle East & Africa). The report covers detailed information on major factors, such as drivers, restraints, challenges, and opportunities, influencing the growth of the AI in protein engineering market. A detailed analysis of key industry players provides insights into their business overview, solutions, and services; key strategies; and recent developments associated with the AI in protein engineering market. This report covers the competitive analysis of startups in the AI in protein engineering market ecosystem.

Reasons to Buy the Report
This report will help established firms and new entrants/smaller firms gauge the market's pulse, which, in turn, can help them gain a greater share of the market. Firms purchasing the report can use one or more of the strategies below to strengthen their market position.

This report provides insights on:
- Analysis of key drivers (increasing adoption of generative ai and protein foundation models, rising demand for next-generation biologics and engineered proteins, increasing availability of protein sequence, structure, and experimental datasets), restraints (limited availability of high-quality experimentally validated protein data, high cost and complexity of experimental validation), opportunities (expansion of AI-designed de novo proteins, growth of AI-enabled antibody discovery and optimization, increasing demand for proprietary protein-engineering datasets), and challenges (biosecurity and biosafety concerns, lack of standardized benchmarking across ai protein-engineering platforms) influencing the growth of the AI in protein engineering market.
- Product Development/Innovation: Detailed insights on upcoming technologies, research & development activities, and new product launches in the AI in protein engineering market.
- Market Development: Comprehensive information on lucrative emerging markets, offerings, AI tools, applications, protein types, protein engineering processes, end users, and regions.
- Market Diversification: Exhaustive information about the product portfolios, growing geographies, recent developments, and investments in the AI in protein engineering market.
- Competitive Assessment: In-depth assessment of market shares, growth strategies, product offerings, and capabilities of the leading players in the AI in protein engineering market like Schrödinger, Inc. (US), XtalPi (China), Dassault Systèmes (France), NVIDIA Corporation (US), Generate:Biomedicines (US), Absci Corp. (US), Insilico Medicine (US), Isomorphic Labs (UK), among others.

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Table of Contents

1 INTRODUCTION 37
1.1 STUDY OBJECTIVES 37
1.2 MARKET DEFINITION 37
1.3 MARKET SCOPE 38
1.3.1 MARKET SEGMENTATION & REGIONAL SCOPE 38
1.3.2 INCLUSIONS & EXCLUSIONS 39
1.3.3 YEARS CONSIDERED 40
1.4 CURRENCY CONSIDERED 40
1.5 LIMITATIONS 41
1.6 STAKEHOLDERS 42

2 EXECUTIVE SUMMARY 43
2.1 KEY INSIGHTS AND MARKET HIGHLIGHTS 43
2.2 KEY MARKET PARTICIPANTS: SHARE INSIGHTS AND STRATEGIC DEVELOPMENTS 45
2.3 DISRUPTIVE TRENDS SHAPING THE MARKET 46
2.4 HIGH-GROWTH SEGMENTS & EMERGING FRONTIERS 47
2.5 SNAPSHOT: GLOBAL MARKET SIZE, GROWTH RATE, AND FORECAST 48

3 PREMIUM INSIGHTS 50
3.1 AI IN PROTEIN ENGINEERING MARKET OVERVIEW 50
3.2 AI IN PROTEIN ENGINEERING MARKET, BY APPLICATION & COUNTRY 51
3.3 AI IN PROTEIN ENGINEERING MARKET: GEOGRAPHIC SNAPSHOT 52

4 MARKET OVERVIEW 53
4.1 INTRODUCTION 53
4.2 MARKET DYNAMICS 54
4.2.1 DRIVERS 54
4.2.1.1 Increasing adoption of generative AI and protein foundation models 54
4.2.1.2 Rising demand for next-generation biologics and engineered proteins 55
4.2.1.3 Increasing availability of protein sequence, structure, and experimental datasets 56
4.2.2 RESTRAINTS 56
4.2.2.1 Limited availability of high-quality experimentally
validated protein data 56
4.2.2.2 High cost and complexity of experimental validation 57
4.2.3 OPPORTUNITIES 57
4.2.3.1 Expansion of AI-designed de novo proteins 57
4.2.3.2 Growth of AI-enabled antibody discovery and optimization 57
4.2.3.3 Increasing demand for proprietary protein-engineering datasets 58
4.2.4 CHALLENGES 58
4.2.4.1 Biosecurity and biosafety concerns 58
4.2.4.2 Lack of standardized benchmarking across AI protein-engineering platforms 59
4.3 UNMET NEEDS AND WHITE SPACES 59
4.4 INTERCONNECTED MARKETS AND CROSS-SECTOR OPPORTUNITIES 60
4.5 STRATEGIC MOVES BY TIER-1/2/3 PLAYERS 60

5 INDUSTRY TRENDS 62
5.1 INDUSTRY TRENDS IN GLOBAL AI IN PROTEIN ENGINEERING MARKET 62
5.2 PORTER’S FIVE FORCES ANALYSIS 62
5.2.1 BARGAINING POWER OF SUPPLIERS 63
5.2.2 BARGAINING POWER OF BUYERS 64
5.2.3 THREAT OF SUBSTITUTES 64
5.2.4 THREAT OF NEW ENTRANTS 64
5.2.5 INTENSITY OF COMPETITIVE RIVALRY 64
5.3 MACROECONOMIC INDICATORS 64
5.3.1 INTRODUCTION 64
5.3.2 GDP TRENDS AND FORECAST 65
5.3.3 TRENDS IN GLOBAL HEALTHCARE IT INDUSTRY 65
5.4 VALUE CHAIN ANALYSIS 65
5.4.1 RESEARCH & PRODUCT DEVELOPMENT 66
5.4.2 DATA INPUTS & COMPUTATIONAL INFRASTRUCTURE 66
5.4.3 AI MODEL & PLATFORM DEVELOPMENT 67
5.4.4 PLATFORM DEPLOYMENT & INTEGRATION 67
5.4.5 MARKETING AND SALES 67
5.4.6 POST-SALE SERVICES 67
5.5 ECOSYSTEM ANALYSIS 67
5.6 PRICING ANALYSIS 70
5.6.1 INDICATIVE PRICE FOR AI IN PROTEIN ENGINEERING MARKET,
BY OFFERING (2025) 70
5.6.2 INDICATIVE PRICE FOR AI IN PROTEIN ENGINEERING MARKET,
BY REGION (2025) 71
5.7 KEY CONFERENCES AND EVENTS, 2026–2027 71
5.8 TRENDS/DISRUPTIONS IMPACTING CUSTOMER BUSINESS 72
5.9 INVESTMENT AND FUNDING SCENARIO 73
5.10 CASE STUDY ANALYSIS 74
5.11 IMPACT OF 2025 US TARIFF – AI IN PROTEIN ENGINEERING MARKET 76
5.11.1 INTRODUCTION 76
5.11.2 KEY TARIFF RATES 76
5.11.3 PRICE IMPACT ANALYSIS 77
5.11.4 IMPACT ON COUNTRY/REGION 78
5.11.4.1 US 78
5.11.4.2 Europe 78
5.11.4.3 Asia Pacific 78
5.11.5 IMPACT ON END USERS 78
5.11.5.1 Pharmaceutical & biotechnology companies 78
5.11.5.2 Academic & research institutes 79
5.11.5.3 Contract research organizations 79
5.11.5.4 Industrial biotechnology companies 79
5.11.5.5 Other end users 79

6 STRATEGIC DISRUPTION THROUGH TECHNOLOGY, PATENTS, DIGITAL,
AND AI ADOPTION 80
6.1 KEY EMERGING TECHNOLOGIES 80
6.1.1 GENERATIVE AI FOR PROTEIN DESIGN 80
6.1.2 PROTEIN LANGUAGE MODELS (PLMS) 80
6.1.3 STRUCTURE-BASED AI FOR PROTEIN ENGINEERING 81
6.2 COMPLEMENTARY TECHNOLOGIES 81
6.2.1 HIGH-PERFORMANCE COMPUTING (HPC) AND CLOUD COMPUTING 81
6.2.2 LABORATORY AUTOMATION AND HIGH-THROUGHPUT SCREENING 81
6.3 ADJACENT TECHNOLOGIES 82
6.3.1 COMPUTATIONAL CHEMISTRY AND MOLECULAR SIMULATION 82
6.3.2 BIOINFORMATICS AND BIOLOGICAL DATA ANALYTICS 82
6.4 TECHNOLOGY/PRODUCT ROADMAP 82
6.5 PATENT ANALYSIS 83
6.5.1 PATENT PUBLICATION TRENDS FOR AI IN PROTEIN ENGINEERING MARKET 83
6.5.2 INSIGHTS: JURISDICTION AND TOP APPLICANT ANALYSIS 84
6.6 FUTURE APPLICATIONS 86
6.6.1 AI-ENABLED INTELLIGENT PROTEIN DESIGN AND PREDICTION 87
6.6.2 AI-DRIVEN AUTOMATED PROTEIN ENGINEERING AND DESIGN-BUILD-
TEST-LEARN 87
6.6.3 AI-ENABLED PERSONALIZED AND FUNCTION-SPECIFIC PROTEIN ENGINEERING 87

7 REGULATORY LANDSCAPE 88
7.1 REGIONAL REGULATIONS AND COMPLIANCE 88
7.1.1 REGULATORY BODIES, GOVERNMENT AGENCIES, & OTHER ORGANIZATIONS 88
7.1.2 REGULATORY FRAMEWORK 92
7.1.2.1 North America 92
7.1.2.2 Europe 93
7.1.2.3 ASIA PACIFIC 94
7.1.2.4 LATIN AMERICA 96
7.1.2.5 Middle East & Africa 97
7.1.3 INDUSTRY STANDARDS 97

8 CUSTOMER LANDSCAPE & BUYER BEHAVIOR 99
8.1 INTRODUCTION 99
8.2 DECISION-MAKING PROCESS 99
8.3 BUYER STAKEHOLDERS AND BUYING EVALUATION CRITERIA 99
8.3.1 KEY STAKEHOLDERS IN BUYING PROCESS 100
8.3.2 BUYING CRITERIA 100
8.4 ADOPTION BARRIERS & INTERNAL CHALLENGES 102
8.5 UNMET NEEDS FROM VARIOUS END-USE INDUSTRIES 102
8.5.1 UNMET NEEDS 103
8.5.2 END USER EXPECTATIONS 104
8.6 MARKET PROFITABILITY 105

9 AI IN PROTEIN ENGINEERING MARKET, BY OFFERING 106
9.1 INTRODUCTION 107
9.2 SOFTWARE/PLATFORMS 107
9.2.1 NICHE POINT SOLUTIONS 109
9.2.1.1 Specialized AI platforms expand protein engineering beyond
end-to-end workflows 109
9.2.2 END-TO-END SOLUTIONS 110
9.2.2.1 Integrated AI platforms enable multi-stage protein engineering and accelerate candidate development 110
9.3 SERVICES 111
9.3.1 CONSULTING & ADVISORY SERVICES 112
9.3.1.1 Increasing complexity of AI adoption creates demand for protein engineering strategy and technical expertise 112
9.3.2 IMPLEMENTATION & INTEGRATION SERVICES 113
9.3.2.1 Integration complexity and data compatibility shape adoption of
AI protein engineering solutions 113
9.3.3 TRAINING & SUPPORT SERVICES 114
9.3.3.1 Specialized skills gaps and evolving AI technologies sustain demand for training & support 114

10 AI IN PROTEIN ENGINEERING MARKET, BY AI TOOL 116
10.1 INTRODUCTION 117
10.2 MACHINE LEARNING & DEEP LEARNING 117
10.2.1 FOUNDATIONAL NEURAL ARCHITECTURES UNDERPIN MODERN PROTEIN ENGINEERING WORKFLOWS 117
10.3 PROTEIN LANGUAGE MODELS 118
10.3.1 EVOLUTION-SCALE SEQUENCE MODELS ENABLE PREDICTION AND GENERATION WITHOUT STRUCTURAL INPUTS 118
10.4 GENERATIVE AI 119
10.4.1 GENERATIVE MODELS MOVE ANTIBODY AND BINDER DESIGN FROM SCREENING TO PROGRAMMABLE DESIGN 119
10.5 STRUCTURE-BASED AI 120
10.5.1 ACCURATE COMPLEX PREDICTION SUPPORTS EPITOPE-SPECIFIC DESIGN AND AFFINITY ESTIMATION 120
10.6 OTHER TOOLS 121
10.6.1 ACTIVE LEARNING, BAYESIAN OPTIMIZATION, AND LAB-IN-THE-LOOP PLATFORMS COMPLEMENT CORE MODEL CLASSES 121

11 AI IN PROTEIN ENGINEERING MARKET, BY APPLICATION 123
11.1 INTRODUCTION 124
11.2 NEXT-GENERATION BIOLOGICS 124
11.2.1 THERAPEUTIC PROTEIN ENGINEERING 126
11.2.1.1 AI-optimized antibodies and engineered proteins move into late-stage development 126
11.2.2 MULTISPECIFIC & BISPECIFIC PROTEIN ENGINEERING 127
11.2.2.1 Dual-targeting formats attract record licensing investment as engineering platforms mature 127
11.2.3 CYTOKINE & GROWTH FACTOR ENGINEERING 128
11.2.3.1 Redesigned cytokines aim to separate therapeutic benefit from systemic toxicity 128
11.2.4 PROTEIN BINDER ENGINEERING 129
11.2.4.1 De novo binder design reaches double-digit to near-complete experimental hit rates 129
11.2.5 OTHER NEXT-GENERATION BIOLOGICS 130
11.2.5.1 Antibody-drug conjugates, scaffold fusions, and novel formats broaden engineering toolkits 130
11.3 MOLECULAR GLUES 131
11.4 DATA GENERATION 132
11.5 ANTIBODY DISCOVERY & OPTIMIZATION 133
11.5.1 ANTIBODY DISCOVERY 134
11.5.1.1 Generative design reduces dependence on immunization and library screening 134
11.5.2 ANTIBODY AFFINITY OPTIMIZATION 135
11.5.2.1 Computational lead optimization improves potency and dosing convenience 135
11.5.3 ANTIBODY SPECIFICITY & CROSS-REACTIVITY OPTIMIZATION 136
11.5.3.1 Atomic-level design enables selective binding and controlled species cross-reactivity 136
11.5.4 ANTIBODY DEVELOPABILITY OPTIMIZATION 137
11.5.4.1 Early developability screening reduces late-stage attrition risk 137
11.5.5 BISPECIFIC & MULTISPECIFIC ANTIBODY ENGINEERING 138
11.5.5.1 Maturing formats and design platforms extend beyond oncology T-Cell engagers 138
11.5.6 OTHER ANTIBODY ENGINEERING 139
11.5.6.1 Fc modification, half-life extension, and delivery formats broaden antibody differentiation 139
11.6 ENZYME ENGINEERING 140
11.7 DE NOVO PROTEIN DESIGN 141
11.8 PROTEIN STABILITY & DEVELOPABILITY OPTIMIZATION 142
11.9 OTHER APPLICATIONS 143

12 AI IN PROTEIN ENGINEERING MARKET, BY PROTEIN TYPE 144
12.1 INTRODUCTION 145
12.2 ANTIBODIES 145
12.2.1 AI-DRIVEN ANTIBODY DESIGN AND OPTIMIZATION ACCELERATE NEXT-GENERATION BIOLOGICS DEVELOPMENT 145
12.3 ENZYMES 147
12.3.1 AI-POWERED ENZYME ENGINEERING EXPANDS APPLICATIONS ACROSS INDUSTRIAL BIOCATALYSIS 147
12.4 CYTOKINES & GROWTH FACTORS 148
12.4.1 ADVANCING PRECISION ENGINEERING OF CYTOKINES AND GROWTH FACTORS 148
12.5 PEPTIDES 149
12.5.1 AI ADDRESSES COMPLEXITY IN PEPTIDE SEQUENCE DESIGN AND FUNCTIONAL OPTIMIZATION 149
12.6 FUSION PROTEINS 149
12.6.1 AI IMPROVES MULTI-DOMAIN DESIGN OF FUSION PROTEINS 149
12.7 MINIPROTEIN 150
12.7.1 DE NOVO MINIPROTEIN DESIGN OPENS NEW OPPORTUNITIES FOR PRECISION BIOLOGICS 150
12.8 OTHER PROTEINS 151
12.8.1 EMERGING PROTEIN MODALITIES CREATE NEW OPPORTUNITIES FOR AI-ENABLED ENGINEERING 151

13 AI IN PROTEIN ENGINEERING MARKET, BY PROTEIN ENGINEERING PROCESS 153
13.1 INTRODUCTION 154
13.2 PROTEIN DISCOVERY 154
13.2.1 EXPANDING SEQUENCE AND STRUCTURE DATABASES ACCELERATE TARGET AND STARTING-POINT IDENTIFICATION 154
13.3 PROTEIN DESIGN 155
13.3.1 OPEN GENERATIVE MODELS MOVE DE NOVO DESIGN FROM PROOF OF CONCEPT TO BROAD EXPERIMENTAL VALIDATION 155
13.4 PROTEIN OPTIMIZATION 156
13.4.1 MACHINE LEARNING-GUIDED OPTIMIZATION IMPROVES AFFINITY, STABILITY, AND MANUFACTURABILITY ACROSS ITERATIVE CYCLES 156
13.5 PROTEIN CHARACTERIZATION 157
13.5.1 HIGHER-RESOLUTION STRUCTURAL AND BIOPHYSICAL ANALYSIS ANCHORS COMPUTATIONAL PREDICTIONS IN EXPERIMENTAL REALITY 157
13.6 EXPERIMENTAL VALIDATION 158
13.6.1 CLOUD LABS, PUBLIC COMPETITIONS, AND LAB-IN-THE-LOOP PLATFORMS SCALE WET-LAB TESTING 158

14 AI IN PROTEIN ENGINEERING MARKET, BY END USER 160
14.1 INTRODUCTION 161
14.2 PHARMACEUTICAL & BIOTECHNOLOGY COMPANIES 161
14.2.1 HIGH R&D INVESTMENTS AND GROWING AI INTEGRATION ACCELERATE PROTEIN ENGINEERING ADOPTION 161
14.3 ACADEMIC & RESEARCH INSTITUTES 163
14.3.1 ADVANCING PROTEIN SCIENCE THROUGH AI-ENABLED RESEARCH
AND COMPUTATIONAL DESIGN 163
14.4 CONTRACT RESEARCH ORGANIZATIONS 164
14.4.1 AI HELPS CROS DIFFERENTIATE PROTEIN ENGINEERING SERVICES
AND EXPAND OUTSOURCED DISCOVERY CAPABILITIES 164
14.5 INDUSTRIAL BIOTECHNOLOGY COMPANIES 165
14.5.1 AI-DRIVEN BIOCATALYST DEVELOPMENT ACCELERATES
ADOPTION IN INDUSTRIAL BIOTECHNOLOGY 165
14.6 OTHER END USERS 166
14.6.1 EXPANSION OF AI-ENABLED PROTEIN ENGINEERING ACROSS DIVERSE APPLICATIONS TO BOOST SEGMENT 166

15 AI IN PROTEIN ENGINEERING MARKET, BY REGION 167
15.1 INTRODUCTION 168
15.2 NORTH AMERICA 168
15.2.1 MACROECONOMIC OUTLOOK FOR NORTH AMERICA 169
15.2.2 US 174
15.2.2.1 AI-driven protein design and strong biopharmaceutical
R&D support market growth 174
15.2.3 CANADA 179
15.2.3.1 Government support for AI innovation and biomanufacturing strengthens market growth 179
15.3 EUROPE 185
15.3.1 MACROECONOMIC OUTLOOK FOR EUROPE 185
15.3.2 GERMANY 191
15.3.2.1 Strong pharmaceutical research base and AI innovation
drive protein engineering adoption 191
15.3.3 FRANCE 196
15.3.3.1 Biopharma innovation and research commercialization support market expansion 196
15.3.4 UK 201
15.3.4.1 Regulatory innovation and AI-driven drug discovery accelerate adoption 201
15.3.5 ITALY 206
15.3.5.1 Pharmaceutical manufacturing strength and research modernization create opportunities 206
15.3.6 SPAIN 211
15.3.6.1 Strong pharmaceutical R&D and biopharma ecosystem support market growth 211
15.3.7 REST OF EUROPE 216
15.4 ASIA PACIFIC 221
15.4.1 MACROECONOMIC OUTLOOK FOR ASIA PACIFIC 221
15.4.2 CHINA 227
15.4.2.1 AI-driven protein engineering and biologics innovation reshape pharmaceutical development 227
15.4.3 JAPAN 233
15.4.3.1 Demographic pressures and AI innovation drive protein engineering adoption 233
15.4.4 INDIA 238
15.4.4.1 Cost-efficient innovation and biotechnology expansion support growth 238
15.4.5 AUSTRALIA 243
15.4.5.1 Translational research ecosystem supports AI-enabled protein engineering 243
15.4.6 SOUTH KOREA 248
15.4.6.1 Biotechnology Expansion and AI investments support
protein engineering adoption 248
15.4.7 REST OF ASIA PACIFIC 252
15.5 LATIN AMERICA 258
15.5.1 MACROECONOMIC OUTLOOK FOR LATIN AMERICA 258
15.5.2 BRAZIL 264
15.5.2.1 Leading regional pharmaceutical research activity supports
market growth 264
15.5.3 MEXICO 269
15.5.3.1 Pharmaceutical manufacturing base and growing R&D
activity support AI adoption 269
15.5.4 REST OF LATIN AMERICA 273
15.6 MIDDLE EAST & AFRICA 279
15.6.1 MACROECONOMIC OUTLOOK FOR MIDDLE EAST & AFRICA 279
15.6.2 GCC COUNTRIES 285
15.6.2.1 Healthcare transformation and biotechnology investments support market growth 285
15.6.2.2 Saudi Arabia 290
15.6.2.2.1 Vision 2030 investments accelerate biotechnology and AI-enabled protein engineering 290
15.6.2.3 UAE 295
15.6.2.3.1 Healthcare innovation and biotechnology initiatives support market growth 295
15.6.2.4 Other GCC countries 300
15.6.3 SOUTH AFRICA 305
15.6.3.1 Expanding biotechnology and research capabilities support market growth 305
15.6.4 REST OF MIDDLE EAST & AFRICA 310

16 COMPETITIVE LANDSCAPE 316
16.1 OVERVIEW 316
16.2 KEY PLAYER STRATEGIES/RIGHT TO WIN 316
16.2.1 OVERVIEW OF STRATEGIES ADOPTED BY KEY PLAYERS IN
AI IN PROTEIN ENGINEERING MARKET 317
16.3 REVENUE SHARE ANALYSIS OF TOP MARKET PLAYERS 319
16.4 MARKET SHARE ANALYSIS, 2025 320
16.5 BRAND COMPARISON 322
16.6 VALUATION & FINANCIAL METRICS 323
16.6.1 FINANCIAL METRICS 323
16.6.2 COMPANY VALUATION 323
16.7 COMPANY EVALUATION MATRIX, KEY PLAYERS (2025) 324
16.7.1 STARS 324
16.7.2 EMERGING LEADERS 324
16.7.3 PERVASIVE PLAYERS 324
16.7.4 PARTICIPANTS 325
16.7.5 COMPANY FOOTPRINT: KEY PLAYERS, 2025 326
16.7.5.1 Company footprint 326
16.7.5.2 Region footprint 327
16.7.5.3 Offering footprint 328
16.7.5.4 Application footprint 329
16.7.5.5 AI tool footprint 330
16.7.5.6 End user footprint 331
16.8 COMPANY EVALUATION MATRIX: STARTUPS/SMES, 2025 332
16.8.1 PROGRESSIVE COMPANIES 332
16.8.2 RESPONSIVE COMPANIES 332
16.8.3 DYNAMIC COMPANIES 332
16.8.4 STARTING BLOCKS 332
16.8.5 COMPETITIVE BENCHMARKING: STARTUPS/SMES, 2025 334
16.8.5.1 Detailed list of key startups/SMEs 334
16.8.5.2 Competitive benchmarking of startups/SMEs 335
16.9 COMPETITIVE SCENARIO 336
16.9.1 PRODUCT/SERVICE LAUNCHES & APPROVALS 336
16.9.2 DEALS 337

17 COMPANY PROFILES 338
17.1 KEY PLAYERS 338
17.1.1 SCHRÖDINGER, INC. 338
17.1.1.1 Business overview 338
17.1.1.2 Products offered 340
17.1.1.3 Recent developments 341
17.1.1.3.1 Product enhancements 341
17.1.1.3.2 Deals 341
17.1.1.4 MnM view 342
17.1.1.4.1 Key strengths 342
17.1.1.4.2 Strategic choices 342
17.1.1.4.3 Weaknesses and competitive threats 342
17.1.2 XTALPI 343
17.1.2.1 Business overview 343
17.1.2.2 Products offered 344
17.1.2.3 Recent developments 345
17.1.2.3.1 Deals 345
17.1.2.4 MnM view 346
17.1.2.4.1 Key strengths 346
17.1.2.4.2 Strategic choices 346
17.1.2.4.3 Weaknesses and competitive threats 346
17.1.3 DASSAULT SYSTÈMES 347
17.1.3.1 Business overview 347
17.1.3.2 Products Offered 348
17.1.3.3 Recent developments 349
17.1.3.3.1 Product launches/enhancements 349
17.1.3.3.2 Deals 349
17.1.3.4 MnM view 349
17.1.3.4.1 Key strengths 349
17.1.3.4.2 Strategic choices 349
17.1.3.4.3 Weaknesses and competitive threats 350
17.1.4 NVIDIA CORPORATION 351
17.1.4.1 Business overview 351
17.1.4.2 Products/Solutions offered 352
17.1.4.3 Recent developments 353
17.1.4.3.1 Product launches/enhancements 353
17.1.4.3.2 Deals 353
17.1.4.4 MnM view 353
17.1.4.4.1 Key strengths 353
17.1.4.4.2 Strategic choices 353
17.1.4.4.3 Weaknesses and competitive threats 354
17.1.5 GENERATE:BIOMEDICINES 355
17.1.5.1 Business overview 355
17.1.5.2 Products offered 355
17.1.5.3 Recent developments 356
17.1.5.3.1 Product enhancements 356
17.1.5.3.2 Deals 356
17.1.5.4 MnM view 357
17.1.5.4.1 Key strengths 357
17.1.5.4.2 Strategic choices 357
17.1.5.4.3 Weaknesses and competitive threats 357
17.1.6 ABSCI CORP. 358
17.1.6.1 Business overview 358
17.1.6.2 Products Offered 359
17.1.6.3 Recent developments 360
17.1.6.3.1 Deals 360
17.1.6.4 MnM view 360
17.1.6.4.1 Key strengths 360
17.1.6.4.2 Strategic choices 360
17.1.6.4.3 Weaknesses and competitive threats 361
17.1.7 INSILICO MEDICINE 362
17.1.7.1 Business overview 362
17.1.7.2 Products/Solutions offered 363
17.1.7.3 Recent developments 364
17.1.7.3.1 Product launches/enhancements 364
17.1.7.3.2 Deals 365
17.1.7.4 MnM view 365
17.1.7.4.1 Key strengths 365
17.1.7.4.2 Strategic choices 365
17.1.7.4.3 Weaknesses and competitive threats 365
17.1.8 CRADLE 366
17.1.8.1 Business overview 366
17.1.8.2 Products offered 367
17.1.8.3 Recent developments 368
17.1.8.3.1 Deals 368
17.1.8.3.2 Other developments 369
17.1.9 A-ALPHA BIO, INC. 370
17.1.9.1 Business overview 370
17.1.9.2 Products offered 371
17.1.9.3 Recent developments 371
17.1.9.3.1 Product launches 371
17.1.9.3.2 Deals 372
17.1.9.3.3 Other developments 373
17.1.10 ISOMORPHIC LABS 374
17.1.10.1 Business overview 374
17.1.10.2 Products offered 375
17.1.10.3 Recent developments 375
17.1.10.3.1 Deals 375
17.1.10.3.2 Other developments 376
17.1.11 CHAI DISCOVERY 377
17.1.11.1 Business overview 377
17.1.11.2 Products offered 378
17.1.11.3 Recent developments 378
17.1.11.3.1 Product launches and approvals 378
17.1.11.3.2 Deals 379
17.1.11.3.3 Other developments 379
17.1.12 EVOLUTIONARYSCALE (BIOHUB) 380
17.1.12.1 Business overview 380
17.1.12.2 Products offered 381
17.1.12.3 Recent developments 381
17.1.12.3.1 Product launches and approvals 381
17.1.12.3.2 Deals 382
17.1.12.3.3 Other developments 382
17.1.13 PROFLUENT 383
17.1.13.1 Business overview 383
17.1.13.2 Products offered 384
17.1.13.3 Recent developments 384
17.1.13.3.1 Deals 384
17.1.13.3.2 Other developments 385
17.1.14 BIGHAT BIO 386
17.1.14.1 Business overview 386
17.1.14.2 Products offered 387
17.1.14.3 Recent developments 387
17.1.14.3.1 Product launches 387
17.1.14.3.2 Deals 388
17.1.15 LATENT LABS 390
17.1.15.1 Business overview 390
17.1.15.2 Products offered 391
17.1.15.3 Recent developments 391
17.1.15.3.1 Product launches 391
17.1.15.3.2 Deals 392
17.1.15.3.3 Other developments 392
17.1.16 BASECAMP RESEARCH 393
17.1.16.1 Business overview 393
17.1.16.2 Products offered 393
17.1.16.3 Recent developments 394
17.1.16.3.1 Product launches 394
17.1.16.3.2 Deals 394
17.1.16.3.3 Other developments 395
17.1.17 NABLA BIO, INC. 396
17.1.17.1 Business overview 396
17.1.17.2 Products offered 397
17.1.17.3 Recent developments 397
17.1.17.3.1 Deals 397
17.1.17.3.2 Other developments 398
17.1.18 EVOZYNE 399
17.1.18.1 Business overview 399
17.1.18.2 Products offered 399
17.1.18.3 Recent developments 400
17.1.18.3.1 Deals 400
17.1.18.3.2 Other developments 400
17.1.19 LABGENIUS LIMITED 401
17.1.19.1 Business overview 401
17.1.19.2 Products offered 401
17.1.19.3 Recent developments 402
17.1.19.3.1 Deals 402
17.1.19.3.2 Other developments 402
17.2 OTHER PLAYERS 403
17.2.1 ARZEDA CORPORATION 403
17.2.2 MENTEN AI 404
17.2.3 PROTEINQURE 405
17.2.4 OUTPACE BIO 406
17.2.5 AI PROTEINS 407
17.2.6 MONODBIO 408
17.2.7 BIOMATTER INC. 409
17.2.8 DIFFUSE BIO 410

18 RESEARCH METHODOLOGY 411
18.1 RESEARCH APPROACH 411
18.1.1 SECONDARY RESEARCH 412
18.1.1.1 Key data from secondary sources 413
18.1.2 PRIMARY RESEARCH 413
18.1.2.1 Primary sources 414
18.1.2.2 Key data from primary sources 415
18.1.2.3 Breakdown of primaries 415
18.1.2.4 Insights from primary experts 416
18.2 RESEARCH METHODOLOGY DESIGN 416
18.3 MARKET SIZE ESTIMATION 418
18.4 MARKET BREAKDOWN DATA TRIANGULATION 423
18.5 MARKET SHARE ESTIMATION 423
18.6 STUDY ASSUMPTIONS 424
18.7 RESEARCH LIMITATIONS 424
18.7.1 METHODOLOGY-RELATED LIMITATIONS 424
18.8 RISK ASSESSMENT 425

19 APPENDIX 426
19.1 DISCUSSION GUIDE 426
19.2 KNOWLEDGESTORE: MARKETSANDMARKETS’ SUBSCRIPTION PORTAL 432
19.3 CUSTOMIZATION OPTIONS 434
19.4 RELATED REPORTS 434
19.5 AUTHOR DETAILS 435

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List of Tables/Graphs

FIGURE 1 AI IN PROTEIN ENGINEERING MARKET SEGMENTATION 38.
FIGURE 2 MARKET SCENARIO 44.
FIGURE 3 GLOBAL AI IN PROTEIN ENGINEERING MARKET, 2024–2031 44.
FIGURE 4 MAJOR STRATEGIES ADOPTED BY KEY PLAYERS IN AI IN PROTEIN ENGINEERING MARKET, 2023–2026 45.
FIGURE 5 DISRUPTIONS INFLUENCING GROWTH OF AI IN PROTEIN ENGINEERING MARKET 46.
FIGURE 6 HIGH-GROWTH SEGMENTS IN AI IN PROTEIN ENGINEERING MARKET, 2026–2031 47.
FIGURE 7 ASIA PACIFIC TO REGISTER HIGHEST CAGR IN AI IN PROTEIN ENGINEERING MARKET DURING FORECAST PERIOD 48.
FIGURE 8 INCREASING R&D INVESTMENTS IN PHARMACEUTICAL AND BIOTECHNOLOGY INDUSTRIES TO DRIVE GROWTH IN AI IN PROTEIN ENGINEERING MARKET 50.
FIGURE 9 SOFTWARE/PLATFORMS HELD MAJOR SHARE IN NORTH AMERICA IN 2025 51.
FIGURE 10 INDIA TO REGISTER HIGHEST GROWTH RATE DURING FORECAST PERIOD 52.
FIGURE 11 AI IN PROTEIN ENGINEERING MARKET: PORTER’S FIVE FORCES ANALYSIS 63.
FIGURE 12 AI IN PROTEIN ENGINEERING MARKET: VALUE CHAIN ANALYSIS 66.
FIGURE 13 AI IN PROTEIN ENGINEERING MARKET: ECOSYSTEM ANALYSIS 68.
FIGURE 14 TRENDS/DISRUPTIONS IMPACTING CUSTOMERS’ BUSINESSES 73.
FIGURE 16 PATENT PUBLICATION TRENDS IN AI IN PROTEIN ENGINEERING MARKET, 2015–2026 84.
FIGURE 17 JURISDICTION AND TOP APPLICANT ANALYSIS FOR AI IN PROTEIN ENGINEERING MARKET 84.
FIGURE 18 TOP APPLICANTS & OWNERS (COMPANIES/INSTITUTIONS) FOR AI IN PROTEIN ENGINEERING MARKET (JANUARY 2015 TO JUNE 2026) 85.
FIGURE 19 INFLUENCE OF STAKEHOLDERS ON BUYING PROCESS FOR END USERS 100.
FIGURE 20 KEY BUYING CRITERIA FOR TOP THREE END USERS 101.
FIGURE 21 NORTH AMERICA: AI IN PROTEIN ENGINEERING MARKET SNAPSHOT 169.
FIGURE 22 ASIA PACIFIC: AI IN PROTEIN ENGINEERING MARKET SNAPSHOT 222.
FIGURE 23 AI IN PROTEIN ENGINEERING MARKET: REVENUE ANALYSIS OF KEY PLAYERS 319.
FIGURE 24 AI IN PROTEIN ENGINEERING MARKET SHARE ANALYSIS OF KEY PLAYERS (2025) 320.
FIGURE 25 AI IN PROTEIN ENGINEERING MARKET: BRAND COMPARATIVE ANALYSIS 322.
FIGURE 26 EV/EBITDA OF KEY VENDORS 323.
FIGURE 27 YEAR-TO-DATE (YTD) PRICE TOTAL RETURN AND 5-YEAR STOCK BETA OF KEY VENDORS 323.
FIGURE 28 AI IN PROTEIN ENGINEERING MARKET: COMPANY EVALUATION MATRIX (2025) 325.
FIGURE 29 AI IN PROTEIN ENGINEERING MARKET: COMPANY FOOTPRINT 326.
FIGURE 30 AI IN PROTEIN ENGINEERING MARKET: COMPANY EVALUATION MATRIX (STARTUPS/SMES), 2025 333.
FIGURE 31 SCHRÖDINGER, INC.: COMPANY SNAPSHOT (2025) 339.
FIGURE 32 XTALPI: COMPANY SNAPSHOT (2025) 344.
FIGURE 33 DASSAULT SYSTÈMES: COMPANY SNAPSHOT (2025) 348.
FIGURE 34 NVIDIA CORPORATION: COMPANY SNAPSHOT (2025) 352.
FIGURE 35 ABSCI CORP.: COMPANY SNAPSHOT (2025) 359.
FIGURE 36 INSILICO MEDICINE: COMPANY SNAPSHOT (2025) 363.
FIGURE 37 RESEARCH DESIGN 411.
FIGURE 38 BREAKDOWN OF PRIMARY INTERVIEWS: BY COMPANY TYPE, DESIGNATION, AND REGION 415.
FIGURE 39 RESEARCH METHODOLOGY: HYPOTHESIS BUILDING 417.
FIGURE 40 BOTTOM-UP APPROACH 418.
FIGURE 41 TOP-DOWN APPROACH 419.
FIGURE 42 CAGR PROJECTIONS FROM ANALYSIS OF MARKET DRIVERS, RESTRAINTS, OPPORTUNITIES, AND CHALLENGES OF AI IN PROTEIN ENGINEERING INDUSTRY 420.
FIGURE 43 CAGR PROJECTIONS: SUPPLY-SIDE ANALYSIS 420.
FIGURE 44 DATA TRIANGULATION METHODOLOGY 423.
TABLE 1 USD EXCHANGE RATES 40.
TABLE 2 AI IN PROTEIN ENGINEERING MARKET: PORTER’S FIVE FORCES ANALYSIS 63.
TABLE 3 AI IN PROTEIN ENGINEERING MARKET: ROLE IN ECOSYSTEM 69.
TABLE 4 INDICATIVE PRICE FOR AI IN PROTEIN ENGINEERING MARKET, BY OFFERING (2025) 70.
TABLE 5 INDICATIVE PRICE FOR AI IN PROTEIN ENGINEERING MARKET, BY REGION (2025) 71.
TABLE 6 AI IN PROTEIN ENGINEERING MARKET: KEY CONFERENCES, 2026–2027 72.
TABLE 7 CASE 1: AI-GUIDED ENZYME OPTIMIZATION USING HISTORICAL EXPERIMENTAL DATA 74.
TABLE 8 CASE 2: AI-GENERATED PROTEIN DESIGN FOR PRECISION GENE EDITING 75.
TABLE 9 CASE 3: COMPUTATIONAL PROTEIN DESIGN FOR AI-DESIGNED PEPTIDE THERAPEUTIC 75.
TABLE 10 US ADJUSTED RECIPROCAL TARIFF RATES 76.
TABLE 11 JURISDICTION ANALYSIS OF TOP APPLICANT COUNTRIES FOR AI IN PROTEIN ENGINEERING MARKET 85.
TABLE 12 AI IN PROTEIN ENGINEERING MARKET: KEY PATENTS/PATENT APPLICATIONS 86.
TABLE 13 NORTH AMERICA: REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS 88.
TABLE 14 EUROPE: REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS 89.
TABLE 15 ASIA PACIFIC: REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS 90.
TABLE 16 LATIN AMERICA: REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS 91.
TABLE 17 MIDDLE EAST & AFRICA: REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS 92.
TABLE 18 REGULATORY SCENARIO OF NORTH AMERICA 92.
TABLE 19 REGULATORY SCENARIO OF EUROPE 93.
TABLE 20 REGULATORY SCENARIO OF ASIA PACIFIC 94.
TABLE 21 REGULATORY SCENARIO OF LATIN AMERICA 96.
TABLE 22 REGULATORY SCENARIO OF MIDDLE EAST & AFRICA 97.
TABLE 23 INFLUENCE OF STAKEHOLDERS ON BUYING PROCESS OF TOP THREE END USERS (%) 100.
TABLE 24 KEY BUYING CRITERIA FOR TOP THREE END USERS 101.
TABLE 25 UNMET NEEDS IN AI IN PROTEIN ENGINEERING MARKET 103.
TABLE 26 END USER EXPECTATIONS IN AI IN PROTEIN ENGINEERING MARKET 104.
TABLE 27 AI IN PROTEIN ENGINEERING MARKET, BY OFFERING, 2024–2031 (USD MILLION) 107.
TABLE 28 AI IN PROTEIN ENGINEERING MARKET, FOR SOFTWARE/PLATFORMS, BY TYPE, 2024–2031 (USD MILLION) 108.
TABLE 29 AI IN PROTEIN ENGINEERING MARKET, FOR SOFTWARE/PLATFORMS, BY REGION, 2024–2031 (USD MILLION) 108.
TABLE 30 AI IN PROTEIN ENGINEERING MARKET, FOR NICHE POINT SOLUTIONS, BY REGION, 2024–2031 (USD MILLION) 110.
TABLE 31 AI IN PROTEIN ENGINEERING MARKET, FOR END-TO-END SOLUTIONS, BY REGION, 2024–2031 (USD MILLION) 111.
TABLE 32 AI IN PROTEIN ENGINEERING MARKET, FOR SERVICES, BY TYPE, 2024–2031 (USD MILLION) 112.
TABLE 33 AI IN PROTEIN ENGINEERING MARKET, FOR SERVICES, BY REGION, 2024–2031 (USD MILLION) 112.
TABLE 34 AI IN PROTEIN ENGINEERING MARKET, FOR CONSULTING & ADVISORY SERVICES, BY REGION, 2024–2031 (USD MILLION) 113.
TABLE 35 AI IN PROTEIN ENGINEERING MARKET, FOR IMPLEMENTATION & INTEGRATION SERVICES, BY REGION, 2024–2031 (USD MILLION) 114.
TABLE 36 AI IN PROTEIN ENGINEERING MARKET, FOR TRAINING & SUPPORT SERVICES, BY REGION, 2024–2031 (USD MILLION) 115.
TABLE 37 AI IN PROTEIN ENGINEERING MARKET, BY AI TOOL, 2024–2031 (USD MILLION) 117.
TABLE 38 AI IN PROTEIN ENGINEERING MARKET FOR MACHINE LEARNING & DEEP LEARNING, BY REGION, 2024–2031 (USD MILLION) 118.
TABLE 39 AI IN PROTEIN ENGINEERING MARKET FOR PROTEIN LANGUAGE MODELS, BY REGION, 2024–2031 (USD MILLION) 119.
TABLE 40 AI IN PROTEIN ENGINEERING MARKET FOR GENERATIVE AI, BY REGION, 2024–2031 (USD MILLION) 120.
TABLE 41 AI IN PROTEIN ENGINEERING MARKET FOR STRUCTURE-BASED AI, BY REGION, 2024–2031 (USD MILLION) 121.
TABLE 42 AI IN PROTEIN ENGINEERING MARKET FOR OTHER TOOLS, BY REGION, 2024–2031 (USD MILLION) 122.
TABLE 43 AI IN PROTEIN ENGINEERING MARKET, BY APPLICATION, 2024–2031 (USD MILLION) 124.
TABLE 44 AI IN PROTEIN ENGINEERING MARKET FOR NEXT-GENERATION BIOLOGICS, BY TYPE, 2024–2031 (USD MILLION) 125.
TABLE 45 AI IN PROTEIN ENGINEERING MARKET FOR NEXT-GENERATION BIOLOGICS, BY REGION, 2024–2031 (USD MILLION) 126.
TABLE 46 AI IN PROTEIN ENGINEERING MARKET FOR THERAPEUTIC PROTEIN ENGINEERING, BY REGION, 2024–2031 (USD MILLION) 127.
TABLE 47 AI IN PROTEIN ENGINEERING MARKET FOR MULTISPECIFIC & BISPECIFIC PROTEIN ENGINEERING, BY REGION, 2024–2031 (USD MILLION) 128.
TABLE 48 AI IN PROTEIN ENGINEERING MARKET FOR CYTOKINE & GROWTH FACTOR ENGINEERING, BY REGION, 2024–2031 (USD MILLION) 129.
TABLE 49 AI IN PROTEIN ENGINEERING MARKET FOR PROTEIN BINDER ENGINEERING, BY REGION, 2024–2031 (USD MILLION) 130.
TABLE 50 AI IN PROTEIN ENGINEERING MARKET FOR OTHER NEXT-GENERATION BIOLOGICS, BY REGION, 2024–2031 (USD MILLION) 131.
TABLE 51 AI IN PROTEIN ENGINEERING MARKET FOR MOLECULAR GLUES, BY REGION, 2024–2031 (USD MILLION) 132.
TABLE 52 AI IN PROTEIN ENGINEERING MARKET FOR DATA GENERATION, BY REGION, 2024–2031 (USD MILLION) 132.
TABLE 53 AI IN PROTEIN ENGINEERING MARKET FOR ANTIBODY DISCOVERY & OPTIMIZATION, BY TYPE, 2024–2031 (USD MILLION) 133.
TABLE 54 AI IN PROTEIN ENGINEERING MARKET FOR ANTIBODY DISCOVERY & OPTIMIZATION, BY REGION, 2024–2031 (USD MILLION) 134.
TABLE 55 AI IN PROTEIN ENGINEERING MARKET FOR ANTIBODY DISCOVERY, BY REGION, 2024–2031 (USD MILLION) 135.
TABLE 56 AI IN PROTEIN ENGINEERING MARKET FOR ANTIBODY AFFINITY OPTIMIZATION, BY REGION, 2024–2031 (USD MILLION) 136.
TABLE 57 AI IN PROTEIN ENGINEERING MARKET FOR ANTIBODY SPECIFICITY & CROSS-REACTIVITY OPTIMIZATION, BY REGION, 2024–2031 (USD MILLION) 137.
TABLE 58 AI IN PROTEIN ENGINEERING MARKET FOR ANTIBODY DEVELOPABILITY OPTIMIZATION, BY REGION, 2024–2031 (USD MILLION) 138.
TABLE 59 AI IN PROTEIN ENGINEERING MARKET FOR BISPECIFIC & MULTISPECIFIC ANTIBODY ENGINEERING, BY REGION, 2024–2031 (USD MILLION) 139.
TABLE 60 AI IN PROTEIN ENGINEERING MARKET FOR OTHER ANTIBODY ENGINEERING, BY REGION, 2024–2031 (USD MILLION) 140.
TABLE 61 AI IN PROTEIN ENGINEERING MARKET FOR ENZYME ENGINEERING, BY REGION, 2024–2031 (USD MILLION) 141.
TABLE 62 AI IN PROTEIN ENGINEERING MARKET FOR DE NOVO PROTEIN DESIGN, BY REGION, 2024–2031 (USD MILLION) 142.
TABLE 63 AI IN PROTEIN ENGINEERING MARKET FOR PROTEIN STABILITY & DEVELOPABILITY OPTIMIZATION, BY REGION, 2024–2031 (USD MILLION) 142.
TABLE 64 AI IN PROTEIN ENGINEERING MARKET FOR OTHER APPLICATIONS, BY REGION, 2024–2031 (USD MILLION) 143.
TABLE 65 AI IN PROTEIN ENGINEERING MARKET, BY PROTEIN TYPE, 2024–2031 (USD MILLION) 145.
TABLE 66 AI IN PROTEIN ENGINEERING MARKET FOR ANTIBODIES, BY REGION, 2024–2031 (USD MILLION) 146.
TABLE 67 AI IN PROTEIN ENGINEERING MARKET FOR ENZYMES, BY REGION, 2024–2031 (USD MILLION) 147.
TABLE 68 AI IN PROTEIN ENGINEERING MARKET FOR CYTOKINES & GROWTH FACTORS, BY REGION, 2024–2031 (USD MILLION) 148.
TABLE 69 AI IN PROTEIN ENGINEERING MARKET FOR PEPTIDES, BY REGION, 2024–2031 (USD MILLION) 149.
TABLE 70 AI IN PROTEIN ENGINEERING MARKET FOR FUSION PROTEINS, BY REGION, 2024–2031 (USD MILLION) 150.
TABLE 71 AI IN PROTEIN ENGINEERING MARKET FOR MINIPROTEIN, BY REGION, 2024–2031 (USD MILLION) 151.
TABLE 72 AI IN PROTEIN ENGINEERING MARKET FOR OTHER PROTEINS, BY REGION, 2024–2031 (USD MILLION) 152.
TABLE 73 AI IN PROTEIN ENGINEERING MARKET, BY PROTEIN ENGINEERING PROCESS, 2024–2031 (USD MILLION) 154.
TABLE 74 AI IN PROTEIN ENGINEERING MARKET FOR PROTEIN DISCOVERY, BY REGION, 2024–2031 (USD MILLION) 155.
TABLE 75 AI IN PROTEIN ENGINEERING MARKET FOR PROTEIN DESIGN, BY REGION, 2024–2031 (USD MILLION) 156.
TABLE 76 AI IN PROTEIN ENGINEERING MARKET FOR PROTEIN OPTIMIZATION, BY REGION, 2024–2031 (USD MILLION) 157.
TABLE 77 AI IN PROTEIN ENGINEERING MARKET FOR PROTEIN CHARACTERIZATION, BY REGION, 2024–2031 (USD MILLION) 158.
TABLE 78 AI IN PROTEIN ENGINEERING MARKET FOR EXPERIMENTAL VALIDATION, BY REGION, 2024–2031 (USD MILLION) 159.
TABLE 79 AI IN PROTEIN ENGINEERING MARKET, BY END USER, 2024–2031 (USD MILLION) 161.
TABLE 80 AI IN PROTEIN ENGINEERING MARKET FOR PHARMACEUTICAL & BIOTECHNOLOGY COMPANIES, BY REGION, 2024–2031 (USD MILLION) 162.
TABLE 81 AI IN PROTEIN ENGINEERING MARKET FOR ACADEMIC & RESEARCH INSTITUTES, BY REGION, 2024–2031 (USD MILLION) 163.
TABLE 82 AI IN PROTEIN ENGINEERING MARKET FOR CONTRACT RESEARCH ORGANIZATIONS, BY REGION, 2024–2031 (USD MILLION) 164.
TABLE 83 AI IN PROTEIN ENGINEERING MARKET FOR INDUSTRIAL BIOTECHNOLOGY COMPANIES, BY REGION, 2024–2031 (USD MILLION) 165.
TABLE 84 AI IN PROTEIN ENGINEERING MARKET FOR OTHER END USERS, BY REGION, 2024–2031 (USD MILLION) 166.
TABLE 85 AI IN PROTEIN ENGINEERING MARKET, BY REGION, 2024–2031 (USD MILLION) 168.
TABLE 86 NORTH AMERICA AI IN PROTEIN ENGINEERING MARKET, BY COUNTRY, 2024–2031 (USD MILLION) 170.
TABLE 87 NORTH AMERICA: AI IN PROTEIN ENGINEERING MARKET, BY OFFERING, 2024–2031 (USD MILLION) 170.
TABLE 88 NORTH AMERICA: AI IN PROTEIN ENGINEERING MARKET FOR SOFTWARE/PLATFORMS, BY TYPE, 2024–2031 (USD MILLION) 170.
TABLE 89 NORTH AMERICA: AI IN PROTEIN ENGINEERING MARKET FOR SERVICES, BY TYPE, 2024–2031 (USD MILLION) 171.
TABLE 90 NORTH AMERICA: AI IN PROTEIN ENGINEERING MARKET, BY AI TOOL, 2024–2031 (USD MILLION) 171.
TABLE 91 NORTH AMERICA: AI IN PROTEIN ENGINEERING MARKET, BY APPLICATION, 2024–2031 (USD MILLION) 172.
TABLE 92 NORTH AMERICA: AI IN PROTEIN ENGINEERING MARKET FOR NEXT-GENERATION BIOLOGICS, BY TYPE, 2024–2031 (USD MILLION) 172.
TABLE 93 NORTH AMERICA: AI IN PROTEIN ENGINEERING MARKET FOR ANTIBODY DISCOVERY & OPTIMIZATION, BY TYPE, 2024–2031 (USD MILLION) 173.
TABLE 94 NORTH AMERICA: AI IN PROTEIN ENGINEERING MARKET, BY PROTEIN TYPE, 2024–2031 (USD MILLION) 173.
TABLE 95 NORTH AMERICA: AI IN PROTEIN ENGINEERING MARKET, BY PROTEIN ENGINEERING PROCESS, 2024–2031 (USD MILLION) 174.
TABLE 96 NORTH AMERICA: AI IN PROTEIN ENGINEERING MARKET, BY END USER, 2024–2031 (USD MILLION) 174.
TABLE 97 US: AI IN PROTEIN ENGINEERING MARKET, BY OFFERING, 2024–2031 (USD MILLION) 175.
TABLE 98 US: AI IN PROTEIN ENGINEERING MARKET FOR SOFTWARE/PLATFORMS, BY TYPE, 2024–2031 (USD MILLION) 176.
TABLE 99 US: AI IN PROTEIN ENGINEERING MARKET FOR SERVICES, BY TYPE, 2024–2031 (USD MILLION) 176.
TABLE 100 US: AI IN PROTEIN ENGINEERING MARKET, BY AI TOOL, 2024–2031 (USD MILLION) 176.
TABLE 101 US: AI IN PROTEIN ENGINEERING MARKET, BY APPLICATION, 2024–2031 (USD MILLION) 177.
TABLE 102 US: AI IN PROTEIN ENGINEERING MARKET FOR NEXT-GENERATION BIOLOGICS, BY TYPE, 2024–2031 (USD MILLION) 177.
TABLE 103 US: AI IN PROTEIN ENGINEERING MARKET FOR ANTIBODY DISCOVERY & OPTIMIZATION, BY TYPE, 2024–2031 (USD MILLION) 178.
TABLE 104 US: AI IN PROTEIN ENGINEERING MARKET, BY PROTEIN TYPE, 2024–2031 (USD MILLION) 178.
TABLE 105 US: AI IN PROTEIN ENGINEERING MARKET, BY PROTEIN ENGINEERING PROCESS, 2024–2031 (USD MILLION) 179.
TABLE 106 US: AI IN PROTEIN ENGINEERING MARKET, BY END USER, 2024–2031 (USD MILLION) 179.
TABLE 107 CANADA: AI IN PROTEIN ENGINEERING MARKET, BY OFFERING, 2024–2031 (USD MILLION) 180.
TABLE 108 CANADA: AI IN PROTEIN ENGINEERING MARKET FOR SOFTWARE/PLATFORMS, BY TYPE, 2024–2031 (USD MILLION) 181.
TABLE 109 CANADA: AI IN PROTEIN ENGINEERING MARKET FOR SERVICES, BY TYPE, 2024–2031 (USD MILLION) 181.
TABLE 110 CANADA: AI IN PROTEIN ENGINEERING MARKET, BY AI TOOL, 2024–2031 (USD MILLION) 181.
TABLE 111 CANADA: AI IN PROTEIN ENGINEERING MARKET, BY APPLICATION, 2024–2031 (USD MILLION) 182.
TABLE 112 CANADA: AI IN PROTEIN ENGINEERING MARKET FOR NEXT-GENERATION BIOLOGICS, BY TYPE, 2024–2031 (USD MILLION) 182.
TABLE 113 CANADA: AI IN PROTEIN ENGINEERING MARKET FOR ANTIBODY DISCOVERY & OPTIMIZATION, BY TYPE, 2024–2031 (USD MILLION) 183.
TABLE 114 CANADA: AI IN PROTEIN ENGINEERING MARKET, BY PROTEIN TYPE, 2024–2031 (USD MILLION) 183.
TABLE 115 CANADA: AI IN PROTEIN ENGINEERING MARKET, BY PROTEIN ENGINEERING PROCESS, 2024–2031 (USD MILLION) 184.
TABLE 116 CANADA: AI IN PROTEIN ENGINEERING MARKET, BY END USER, 2024–2031 (USD MILLION) 184.
TABLE 117 EUROPE: AI IN PROTEIN ENGINEERING MARKET, BY COUNTRY, 2024–2031 (USD MILLION) 186.
TABLE 118 EUROPE: AI IN PROTEIN ENGINEERING MARKET, BY OFFERING, 2024–2031 (USD MILLION) 186.
TABLE 119 EUROPE: AI IN PROTEIN ENGINEERING MARKET FOR SOFTWARE/PLATFORMS, BY TYPE, 2024–2031 (USD MILLION) 186.
TABLE 120 EUROPE: AI IN PROTEIN ENGINEERING MARKET FOR SERVICES, BY TYPE, 2024–2031 (USD MILLION) 187.
TABLE 121 EUROPE: AI IN PROTEIN ENGINEERING MARKET, BY AI TOOL, 2024–2031 (USD MILLION) 187.
TABLE 122 EUROPE: AI IN PROTEIN ENGINEERING MARKET, BY APPLICATION, 2024–2031 (USD MILLION) 188.
TABLE 123 EUROPE: AI IN PROTEIN ENGINEERING MARKET FOR NEXT-GENERATION BIOLOGICS, BY TYPE, 2024–2031 (USD MILLION) 188.
TABLE 124 EUROPE: AI IN PROTEIN ENGINEERING MARKET FOR ANTIBODY DISCOVERY & OPTIMIZATION, BY TYPE, 2024–2031 (USD MILLION) 189.
TABLE 125 EUROPE: AI IN PROTEIN ENGINEERING MARKET, BY PROTEIN TYPE, 2024–2031 (USD MILLION) 189.
TABLE 126 EUROPE: AI IN PROTEIN ENGINEERING MARKET, BY PROTEIN ENGINEERING PROCESS, 2024–2031 (USD MILLION) 190.
TABLE 127 EUROPE: AI IN PROTEIN ENGINEERING MARKET, BY END USER, 2024–2031 (USD MILLION) 190.
TABLE 128 GERMANY: AI IN PROTEIN ENGINEERING MARKET, BY OFFERING, 2024–2031 (USD MILLION) 191.
TABLE 129 GERMANY: AI IN PROTEIN ENGINEERING MARKET FOR SOFTWARE/PLATFORMS, BY TYPE, 2024–2031 (USD MILLION) 192.
TABLE 130 GERMANY: AI IN PROTEIN ENGINEERING MARKET FOR SERVICES, BY TYPE, 2024–2031 (USD MILLION) 192.
TABLE 131 GERMANY: AI IN PROTEIN ENGINEERING MARKET, BY AI TOOL, 2024–2031 (USD MILLION) 192.
TABLE 132 GERMANY: AI IN PROTEIN ENGINEERING MARKET, BY APPLICATION, 2024–2031 (USD MILLION) 193.
TABLE 133 GERMANY: AI IN PROTEIN ENGINEERING MARKET FOR NEXT-GENERATION BIOLOGICS, BY TYPE, 2024–2031 (USD MILLION) 193.
TABLE 134 GERMANY: AI IN PROTEIN ENGINEERING MARKET FOR ANTIBODY DISCOVERY & OPTIMIZATION, BY TYPE, 2024–2031 (USD MILLION) 194.
TABLE 135 GERMANY: AI IN PROTEIN ENGINEERING MARKET, BY PROTEIN TYPE, 2024–2031 (USD MILLION) 194.
TABLE 136 GERMANY: AI IN PROTEIN ENGINEERING MARKET, BY PROTEIN ENGINEERING PROCESS, 2024–2031 (USD MILLION) 195.
TABLE 137 GERMANY: AI IN PROTEIN ENGINEERING MARKET, BY END USER, 2024–2031 (USD MILLION) 195.
TABLE 138 FRANCE: AI IN PROTEIN ENGINEERING MARKET, BY OFFERING, 2024–2031 (USD MILLION) 196.
TABLE 139 FRANCE: AI IN PROTEIN ENGINEERING MARKET FOR SOFTWARE/PLATFORMS, BY TYPE, 2024–2031 (USD MILLION) 197.
TABLE 140 FRANCE: AI IN PROTEIN ENGINEERING MARKET FOR SERVICES, BY TYPE, 2024–2031 (USD MILLION) 197.
TABLE 141 FRANCE: AI IN PROTEIN ENGINEERING MARKET, BY AI TOOL, 2024–2031 (USD MILLION) 197.
TABLE 142 FRANCE: AI IN PROTEIN ENGINEERING MARKET, BY APPLICATION, 2024–2031 (USD MILLION) 198.
TABLE 143 FRANCE: AI IN PROTEIN ENGINEERING MARKET FOR NEXT-GENERATION BIOLOGICS, BY TYPE, 2024–2031 (USD MILLION) 198.
TABLE 144 FRANCE: AI IN PROTEIN ENGINEERING MARKET FOR ANTIBODY DISCOVERY & OPTIMIZATION, BY TYPE, 2024–2031 (USD MILLION) 199.
TABLE 145 FRANCE: AI IN PROTEIN ENGINEERING MARKET, BY PROTEIN TYPE, 2024–2031 (USD MILLION) 199.
TABLE 146 FRANCE: AI IN PROTEIN ENGINEERING MARKET, BY PROTEIN ENGINEERING PROCESS, 2024–2031 (USD MILLION) 200.
TABLE 147 FRANCE: AI IN PROTEIN ENGINEERING MARKET, BY END USER, 2024–2031 (USD MILLION) 200.
TABLE 148 UK: AI IN PROTEIN ENGINEERING MARKET, BY OFFERING, 2024–2031 (USD MILLION) 201.
TABLE 149 UK: AI IN PROTEIN ENGINEERING MARKET FOR SOFTWARE/PLATFORMS, BY TYPE, 2024–2031 (USD MILLION) 202.
TABLE 150 UK: AI IN PROTEIN ENGINEERING MARKET FOR SERVICES, BY TYPE, 2024–2031 (USD MILLION) 202.
TABLE 151 UK: AI IN PROTEIN ENGINEERING MARKET, BY AI TOOL, 2024–2031 (USD MILLION) 202.
TABLE 152 UK: AI IN PROTEIN ENGINEERING MARKET, BY APPLICATION, 2024–2031 (USD MILLION) 203.
TABLE 153 UK: AI IN PROTEIN ENGINEERING MARKET FOR NEXT-GENERATION BIOLOGICS, BY TYPE, 2024–2031 (USD MILLION) 203.
TABLE 154 UK: AI IN PROTEIN ENGINEERING MARKET FOR ANTIBODY DISCOVERY & OPTIMIZATION, BY TYPE, 2024–2031 (USD MILLION) 204.
TABLE 155 UK: AI IN PROTEIN ENGINEERING MARKET, BY PROTEIN TYPE, 2024–2031 (USD MILLION) 204.
TABLE 156 UK: AI IN PROTEIN ENGINEERING MARKET, BY PROTEIN ENGINEERING PROCESS, 2024–2031 (USD MILLION) 205.
TABLE 157 UK: AI IN PROTEIN ENGINEERING MARKET, BY END USER, 2024–2031 (USD MILLION) 205.
TABLE 158 ITALY: AI IN PROTEIN ENGINEERING MARKET, BY OFFERING, 2024–2031 (USD MILLION) 206.
TABLE 159 ITALY: AI IN PROTEIN ENGINEERING MARKET FOR SOFTWARE/PLATFORMS, BY TYPE, 2024–2031 (USD MILLION) 207.
TABLE 160 ITALY: AI IN PROTEIN ENGINEERING MARKET FOR SERVICES, BY TYPE, 2024–2031 (USD MILLION) 207.
TABLE 161 ITALY: AI IN PROTEIN ENGINEERING MARKET, BY AI TOOL, 2024–2031 (USD MILLION) 207.
TABLE 162 ITALY: AI IN PROTEIN ENGINEERING MARKET, BY APPLICATION, 2024–2031 (USD MILLION) 208.
TABLE 163 ITALY: AI IN PROTEIN ENGINEERING MARKET FOR NEXT-GENERATION BIOLOGICS, BY TYPE, 2024–2031 (USD MILLION) 208.
TABLE 164 ITALY: AI IN PROTEIN ENGINEERING MARKET FOR ANTIBODY DISCOVERY & OPTIMIZATION, BY TYPE, 2024–2031 (USD MILLION) 209.
TABLE 165 ITALY: AI IN PROTEIN ENGINEERING MARKET, BY PROTEIN TYPE, 2024–2031 (USD MILLION) 209.
TABLE 166 ITALY: AI IN PROTEIN ENGINEERING MARKET, BY PROTEIN ENGINEERING PROCESS, 2024–2031 (USD MILLION) 210.
TABLE 167 ITALY: AI IN PROTEIN ENGINEERING MARKET, BY END USER, 2024–2031 (USD MILLION) 210.
TABLE 168 SPAIN: AI IN PROTEIN ENGINEERING MARKET, BY OFFERING, 2024–2031 (USD MILLION) 211.
TABLE 169 SPAIN: AI IN PROTEIN ENGINEERING MARKET FOR SOFTWARE/PLATFORMS, BY TYPE, 2024–2031 (USD MILLION) 212.
TABLE 170 SPAIN: AI IN PROTEIN ENGINEERING MARKET FOR SERVICES, BY TYPE, 2024–2031 (USD MILLION) 212.
TABLE 171 SPAIN: AI IN PROTEIN ENGINEERING MARKET, BY AI TOOL, 2024–2031 (USD MILLION) 212.
TABLE 172 SPAIN: AI IN PROTEIN ENGINEERING MARKET, BY APPLICATION, 2024–2031 (USD MILLION) 213.
TABLE 173 SPAIN: AI IN PROTEIN ENGINEERING MARKET FOR NEXT-GENERATION BIOLOGICS, BY TYPE, 2024–2031 (USD MILLION) 213.
TABLE 174 SPAIN: AI IN PROTEIN ENGINEERING MARKET FOR ANTIBODY DISCOVERY & OPTIMIZATION, BY TYPE, 2024–2031 (USD MILLION) 214.
TABLE 175 SPAIN: AI IN PROTEIN ENGINEERING MARKET, BY PROTEIN TYPE, 2024–2031 (USD MILLION) 214.
TABLE 176 SPAIN: AI IN PROTEIN ENGINEERING MARKET, BY PROTEIN ENGINEERING PROCESS, 2024–2031 (USD MILLION) 215.
TABLE 177 SPAIN: AI IN PROTEIN ENGINEERING MARKET, BY END USER, 2024–2031 (USD MILLION) 215.
TABLE 178 REST OF EUROPE: AI IN PROTEIN ENGINEERING MARKET, BY OFFERING, 2024–2031 (USD MILLION) 216.
TABLE 179 REST OF EUROPE: AI IN PROTEIN ENGINEERING MARKET FOR SOFTWARE/PLATFORMS, BY TYPE, 2024–2031 (USD MILLION) 217.
TABLE 180 REST OF EUROPE: AI IN PROTEIN ENGINEERING MARKET FOR SERVICES, BY TYPE, 2024–2031 (USD MILLION) 217.
TABLE 181 REST OF EUROPE: AI IN PROTEIN ENGINEERING MARKET, BY AI TOOL, 2024–2031 (USD MILLION) 217.
TABLE 182 REST OF EUROPE: AI IN PROTEIN ENGINEERING MARKET, BY APPLICATION, 2024–2031 (USD MILLION) 218.
TABLE 183 REST OF EUROPE: AI IN PROTEIN ENGINEERING MARKET FOR NEXT-GENERATION BIOLOGICS, BY TYPE, 2024–2031 (USD MILLION) 218.
TABLE 184 REST OF EUROPE: AI IN PROTEIN ENGINEERING MARKET FOR ANTIBODY DISCOVERY & OPTIMIZATION, BY TYPE, 2024–2031 (USD MILLION) 219.
TABLE 185 REST OF EUROPE: AI IN PROTEIN ENGINEERING MARKET, BY PROTEIN TYPE, 2024–2031 (USD MILLION) 219.
TABLE 186 REST OF EUROPE: AI IN PROTEIN ENGINEERING MARKET, BY PROTEIN ENGINEERING PROCESS, 2024–2031 (USD MILLION) 220.
TABLE 187 REST OF EUROPE: AI IN PROTEIN ENGINEERING MARKET, BY END USER, 2024–2031 (USD MILLION) 220.
TABLE 188 ASIA PACIFIC: AI IN PROTEIN ENGINEERING MARKET, BY COUNTRY, 2024–2031 (USD MILLION) 222.
TABLE 189 ASIA PACIFIC: AI IN PROTEIN ENGINEERING MARKET, BY OFFERING, 2024–2031 (USD MILLION) 223.
TABLE 190 ASIA PACIFIC: AI IN PROTEIN ENGINEERING MARKET FOR SOFTWARE/PLATFORMS, BY TYPE, 2024–2031 (USD MILLION) 223.
TABLE 191 ASIA PACIFIC: AI IN PROTEIN ENGINEERING MARKET FOR SERVICES, BY TYPE, 2024–2031 (USD MILLION) 223.
TABLE 192 ASIA PACIFIC: AI IN PROTEIN ENGINEERING MARKET, BY AI TOOL, 2024–2031 (USD MILLION) 224.
TABLE 193 ASIA PACIFIC: AI IN PROTEIN ENGINEERING MARKET, BY APPLICATION, 2024–2031 (USD MILLION) 224.
TABLE 194 ASIA PACIFIC: AI IN PROTEIN ENGINEERING MARKET FOR NEXT-GENERATION BIOLOGICS, BY TYPE, 2024–2031 (USD MILLION) 225.
TABLE 195 ASIA PACIFIC: AI IN PROTEIN ENGINEERING MARKET FOR ANTIBODY DISCOVERY & OPTIMIZATION, BY TYPE, 2024–2031 (USD MILLION) 225.
TABLE 196 ASIA PACIFIC: AI IN PROTEIN ENGINEERING MARKET, BY PROTEIN TYPE, 2024–2031 (USD MILLION) 226.
TABLE 197 ASIA PACIFIC: AI IN PROTEIN ENGINEERING MARKET, BY PROTEIN ENGINEERING PROCESS, 2024–2031 (USD MILLION) 226.
TABLE 198 ASIA PACIFIC: AI IN PROTEIN ENGINEERING MARKET, BY END USER, 2024–2031 (USD MILLION) 227.
TABLE 199 CHINA: AI IN PROTEIN ENGINEERING MARKET, BY OFFERING, 2024–2031 (USD MILLION) 228.
TABLE 200 CHINA: AI IN PROTEIN ENGINEERING MARKET FOR SOFTWARE/PLATFORMS, BY TYPE, 2024–2031 (USD MILLION) 228.
TABLE 201 CHINA: AI IN PROTEIN ENGINEERING MARKET FOR SERVICES, BY TYPE, 2024–2031 (USD MILLION) 229.
TABLE 202 CHINA: AI IN PROTEIN ENGINEERING MARKET, BY AI TOOL, 2024–2031 (USD MILLION) 229.
TABLE 203 CHINA: AI IN PROTEIN ENGINEERING MARKET, BY APPLICATION, 2024–2031 (USD MILLION) 230.
TABLE 204 CHINA: AI IN PROTEIN ENGINEERING MARKET FOR NEXT-GENERATION BIOLOGICS, BY TYPE, 2024–2031 (USD MILLION) 230.
TABLE 205 CHINA: AI IN PROTEIN ENGINEERING MARKET FOR ANTIBODY DISCOVERY & OPTIMIZATION, BY TYPE, 2024–2031 (USD MILLION) 231.
TABLE 206 CHINA: AI IN PROTEIN ENGINEERING MARKET, BY PROTEIN TYPE, 2024–2031 (USD MILLION) 231.
TABLE 207 CHINA: AI IN PROTEIN ENGINEERING MARKET, BY PROTEIN ENGINEERING PROCESS, 2024–2031 (USD MILLION) 232.
TABLE 208 CHINA: AI IN PROTEIN ENGINEERING MARKET, BY END USER, 2024–2031 (USD MILLION) 232.
TABLE 209 JAPAN: AI IN PROTEIN ENGINEERING MARKET, BY OFFERING, 2024–2031 (USD MILLION) 233.
TABLE 210 JAPAN: AI IN PROTEIN ENGINEERING MARKET FOR SOFTWARE/PLATFORMS, BY TYPE, 2024–2031 (USD MILLION) 234.
TABLE 211 JAPAN: AI IN PROTEIN ENGINEERING MARKET FOR SERVICES, BY TYPE, 2024–2031 (USD MILLION) 234.
TABLE 212 JAPAN: AI IN PROTEIN ENGINEERING MARKET, BY AI TOOL, 2024–2031 (USD MILLION) 234.
TABLE 213 JAPAN: AI IN PROTEIN ENGINEERING MARKET, BY APPLICATION, 2024–2031 (USD MILLION) 235.
TABLE 214 JAPAN: AI IN PROTEIN ENGINEERING MARKET FOR NEXT-GENERATION BIOLOGICS, BY TYPE, 2024–2031 (USD MILLION) 235.
TABLE 215 JAPAN: AI IN PROTEIN ENGINEERING MARKET FOR ANTIBODY DISCOVERY & OPTIMIZATION, BY TYPE, 2024–2031 (USD MILLION) 236.
TABLE 216 JAPAN: AI IN PROTEIN ENGINEERING MARKET, BY PROTEIN TYPE, 2024–2031 (USD MILLION) 236.
TABLE 217 JAPAN: AI IN PROTEIN ENGINEERING MARKET, BY PROTEIN ENGINEERING PROCESS, 2024–2031 (USD MILLION) 237.
TABLE 218 JAPAN: AI IN PROTEIN ENGINEERING MARKET, BY END USER, 2024–2031 (USD MILLION) 237.
TABLE 219 INDIA: AI IN PROTEIN ENGINEERING MARKET, BY OFFERING, 2024–2031 (USD MILLION) 238.
TABLE 220 INDIA: AI IN PROTEIN ENGINEERING MARKET FOR SOFTWARE/PLATFORMS, BY TYPE, 2024–2031 (USD MILLION) 239.
TABLE 221 INDIA: AI IN PROTEIN ENGINEERING MARKET FOR SERVICES, BY TYPE, 2024–2031 (USD MILLION) 239.
TABLE 222 INDIA: AI IN PROTEIN ENGINEERING MARKET, BY AI TOOL, 2024–2031 (USD MILLION) 239.
TABLE 223 INDIA: AI IN PROTEIN ENGINEERING MARKET, BY APPLICATION, 2024–2031 (USD MILLION) 240.
TABLE 224 INDIA: AI IN PROTEIN ENGINEERING MARKET FOR NEXT-GENERATION BIOLOGICS, BY TYPE, 2024–2031 (USD MILLION) 240.
TABLE 225 INDIA: AI IN PROTEIN ENGINEERING MARKET FOR ANTIBODY DISCOVERY & OPTIMIZATION, BY TYPE, 2024–2031 (USD MILLION) 241.
TABLE 226 INDIA: AI IN PROTEIN ENGINEERING MARKET, BY PROTEIN TYPE, 2024–2031 (USD MILLION) 241.
TABLE 227 INDIA: AI IN PROTEIN ENGINEERING MARKET, BY PROTEIN ENGINEERING PROCESS, 2024–2031 (USD MILLION) 242.
TABLE 228 INDIA: AI IN PROTEIN ENGINEERING MARKET, BY END USER, 2024–2031 (USD MILLION) 242.
TABLE 229 AUSTRALIA: AI IN PROTEIN ENGINEERING MARKET, BY OFFERING, 2024–2031 (USD MILLION) 243.
TABLE 230 AUSTRALIA: AI IN PROTEIN ENGINEERING MARKET FOR SOFTWARE/PLATFORMS, BY TYPE, 2024–2031 (USD MILLION) 244.
TABLE 231 AUSTRALIA: AI IN PROTEIN ENGINEERING MARKET FOR SERVICES, BY TYPE, 2024–2031 (USD MILLION) 244.
TABLE 232 AUSTRALIA: AI IN PROTEIN ENGINEERING MARKET, BY AI TOOL, 2024–2031 (USD MILLION) 244.
TABLE 233 AUSTRALIA: AI IN PROTEIN ENGINEERING MARKET, BY APPLICATION, 2024–2031 (USD MILLION) 245.
TABLE 234 AUSTRALIA: AI IN PROTEIN ENGINEERING MARKET FOR NEXT-GENERATION BIOLOGICS, BY TYPE, 2024–2031 (USD MILLION) 245.
TABLE 235 AUSTRALIA: AI IN PROTEIN ENGINEERING MARKET FOR ANTIBODY DISCOVERY & OPTIMIZATION, BY TYPE, 2024–2031 (USD MILLION) 246.
TABLE 236 AUSTRALIA: AI IN PROTEIN ENGINEERING MARKET, BY PROTEIN TYPE, 2024–2031 (USD MILLION) 246.
TABLE 237 AUSTRALIA: AI IN PROTEIN ENGINEERING MARKET, BY PROTEIN ENGINEERING PROCESS, 2024–2031 (USD MILLION) 247.
TABLE 238 AUSTRALIA: AI IN PROTEIN ENGINEERING MARKET, BY END USER, 2024–2031 (USD MILLION) 247.
TABLE 239 SOUTH KOREA: AI IN PROTEIN ENGINEERING MARKET, BY OFFERING, 2024–2031 (USD MILLION) 248.
TABLE 240 SOUTH KOREA: AI IN PROTEIN ENGINEERING MARKET FOR SOFTWARE/PLATFORMS, BY TYPE, 2024–2031 (USD MILLION) 248.
TABLE 241 SOUTH KOREA: AI IN PROTEIN ENGINEERING MARKET FOR SERVICES, BY TYPE, 2024–2031 (USD MILLION) 249.
TABLE 242 SOUTH KOREA: AI IN PROTEIN ENGINEERING MARKET, BY AI TOOL, 2024–2031 (USD MILLION) 249.
TABLE 243 SOUTH KOREA: AI IN PROTEIN ENGINEERING MARKET, BY APPLICATION, 2024–2031 (USD MILLION) 250.
TABLE 244 SOUTH KOREA: AI IN PROTEIN ENGINEERING MARKET FOR NEXT-GENERATION BIOLOGICS, BY TYPE, 2024–2031 (USD MILLION) 250.
TABLE 245 SOUTH KOREA: AI IN PROTEIN ENGINEERING MARKET FOR ANTIBODY DISCOVERY & OPTIMIZATION, BY TYPE, 2024–2031 (USD MILLION) 251.
TABLE 246 SOUTH KOREA: AI IN PROTEIN ENGINEERING MARKET, BY PROTEIN TYPE, 2024–2031 (USD MILLION) 251.
TABLE 247 SOUTH KOREA: AI IN PROTEIN ENGINEERING MARKET, BY PROTEIN ENGINEERING PROCESS, 2024–2031 (USD MILLION) 252.
TABLE 248 SOUTH KOREA: AI IN PROTEIN ENGINEERING MARKET, BY END USER, 2024–2031 (USD MILLION) 252.
TABLE 249 REST OF ASIA PACIFIC: AI IN PROTEIN ENGINEERING MARKET, BY OFFERING, 2024–2031 (USD MILLION) 253.
TABLE 250 REST OF ASIA PACIFIC: AI IN PROTEIN ENGINEERING MARKET FOR SOFTWARE/PLATFORMS, BY TYPE, 2024–2031 (USD MILLION) 253.
TABLE 251 REST OF ASIA PACIFIC: AI IN PROTEIN ENGINEERING MARKET FOR SERVICES, BY TYPE, 2024–2031 (USD MILLION) 254.
TABLE 252 REST OF ASIA PACIFIC: AI IN PROTEIN ENGINEERING MARKET, BY AI TOOL, 2024–2031 (USD MILLION) 254.
TABLE 253 REST OF ASIA PACIFIC: AI IN PROTEIN ENGINEERING MARKET, BY APPLICATION, 2024–2031 (USD MILLION) 255.
TABLE 254 REST OF ASIA PACIFIC: AI IN PROTEIN ENGINEERING MARKET FOR NEXT-GENERATION BIOLOGICS, BY TYPE, 2024–2031 (USD MILLION) 255.
TABLE 255 REST OF ASIA PACIFIC: AI IN PROTEIN ENGINEERING MARKET FOR ANTIBODY DISCOVERY & OPTIMIZATION, BY TYPE, 2024–2031 (USD MILLION) 256.
TABLE 256 REST OF ASIA PACIFIC: AI IN PROTEIN ENGINEERING MARKET, BY PROTEIN TYPE, 2024–2031 (USD MILLION) 256.
TABLE 257 REST OF ASIA PACIFIC: AI IN PROTEIN ENGINEERING MARKET, BY PROTEIN ENGINEERING PROCESS, 2024–2031 (USD MILLION) 257.
TABLE 258 REST OF ASIA PACIFIC: AI IN PROTEIN ENGINEERING MARKET, BY END USER, 2024–2031 (USD MILLION) 257.
TABLE 259 LATIN AMERICA: AI IN PROTEIN ENGINEERING MARKET, BY COUNTRY, 2024–2031 (USD MILLION) 259.
TABLE 260 LATIN AMERICA: AI IN PROTEIN ENGINEERING MARKET, BY OFFERING, 2024–2031 (USD MILLION) 259.
TABLE 261 LATIN AMERICA: AI IN PROTEIN ENGINEERING MARKET FOR SOFTWARE/PLATFORMS, BY TYPE, 2024–2031 (USD MILLION) 259.
TABLE 262 LATIN AMERICA: AI IN PROTEIN ENGINEERING MARKET FOR SERVICES, BY TYPE, 2024–2031 (USD MILLION) 260.
TABLE 263 LATIN AMERICA: AI IN PROTEIN ENGINEERING MARKET, BY AI TOOL, 2024–2031 (USD MILLION) 260.
TABLE 264 LATIN AMERICA: AI IN PROTEIN ENGINEERING MARKET, BY APPLICATION, 2024–2031 (USD MILLION) 261.
TABLE 265 LATIN AMERICA: AI IN PROTEIN ENGINEERING MARKET FOR NEXT-GENERATION BIOLOGICS, BY TYPE, 2024–2031 (USD MILLION) 261.
TABLE 266 LATIN AMERICA: AI IN PROTEIN ENGINEERING MARKET FOR ANTIBODY DISCOVERY & OPTIMIZATION, BY TYPE, 2024–2031 (USD MILLION) 262.
TABLE 267 LATIN AMERICA: AI IN PROTEIN ENGINEERING MARKET, BY PROTEIN TYPE, 2024–2031 (USD MILLION) 262.
TABLE 268 LATIN AMERICA: AI IN PROTEIN ENGINEERING MARKET, BY PROTEIN ENGINEERING PROCESS, 2024–2031 (USD MILLION) 263.
TABLE 269 LATIN AMERICA: AI IN PROTEIN ENGINEERING MARKET, BY END USER, 2024–2031 (USD MILLION) 263.
TABLE 270 BRAZIL: AI IN PROTEIN ENGINEERING MARKET, BY OFFERING, 2024–2031 (USD MILLION) 264.
TABLE 271 BRAZIL: AI IN PROTEIN ENGINEERING MARKET FOR SOFTWARE/PLATFORMS, BY TYPE, 2024–2031 (USD MILLION) 264.
TABLE 272 BRAZIL: AI IN PROTEIN ENGINEERING MARKET FOR SERVICES, BY TYPE, 2024–2031 (USD MILLION) 265.
TABLE 273 BRAZIL: AI IN PROTEIN ENGINEERING MARKET, BY AI TOOL, 2024–2031 (USD MILLION) 265.
TABLE 274 BRAZIL: AI IN PROTEIN ENGINEERING MARKET, BY APPLICATION, 2024–2031 (USD MILLION) 266.
TABLE 275 BRAZIL: AI IN PROTEIN ENGINEERING MARKET FOR NEXT-GENERATION BIOLOGICS, BY TYPE, 2024–2031 (USD MILLION) 266.
TABLE 276 BRAZIL: AI IN PROTEIN ENGINEERING MARKET FOR ANTIBODY DISCOVERY & OPTIMIZATION, BY TYPE, 2024–2031 (USD MILLION) 267.
TABLE 277 BRAZIL: AI IN PROTEIN ENGINEERING MARKET, BY PROTEIN TYPE, 2024–2031 (USD MILLION) 267.