- Published: April 2024
- Pages: 200
- Tables: 30
- Figures: 20
Generative biology is an emerging field that leverages computational techniques, such as deep learning and evolutionary algorithms, to model, simulate, and engineer biological systems. This includes the generation, optimization, and analysis of biological structures, functions, and behaviours. The global generative biology market has experienced significant growth in recent years, driven by advancements in various computational approaches and the increasing recognition of their potential to accelerate innovation and product development across multiple industries. This report provides a comprehensive analysis of the current state and future trajectory of this dynamic market, spanning key technologies, applications, end-user industries, and regional trends.
Generative biology, an interdisciplinary field that integrates computational modelling, data science, and biotechnology, has emerged as a game-changer across diverse industries. From accelerating drug discovery and materials design to revolutionizing software engineering and agricultural biotechnology, the versatile applications of generative biology are poised to reshape the global landscape of innovation. The report delves into the historical development of generative biology, outlining the core computational techniques that are powering this revolution, including generative models, design optimization algorithms, computational biology approaches, and data-driven methodologies. It analyzes the key market drivers, such as the increasing demand for efficient and cost-effective product development, the rise in investment and funding, and the convergence of generative biology with other emerging technologies.
Providing a detailed competitive landscape, the report examines the diverse ecosystem of technology companies, start-ups, and research institutions shaping the global generative biology market. It also presents a comprehensive segmentation of the market, highlighting the growth trajectories across various technologies, applications, end-user industries, and geographic regions. The wide-ranging applications of generative biology are explored, showcasing how these transformative techniques are being applied to accelerate drug discovery, design advanced materials, engineer synthetic biological systems, optimize software architectures, and address challenges in agriculture and environmental remediation.
The report presents a detailed market map, highlighting the diverse ecosystem of technology companies, start-ups, and research institutions that are shaping the competitive landscape. It analyzes the key market drivers, such as the advancements in computational techniques and the growing recognition of generative biology's potential across various industries. Segmentation of the global generative biology market is provided across multiple dimensions, including technology (e.g., deep learning, evolutionary algorithms, agent-based modeling), application (e.g., drug discovery, materials design, synthetic biology, software engineering), end-user industry (e.g., pharmaceuticals, chemicals, technology, agriculture), and geographic regions (North America, Europe, Asia-Pacific, Rest of the World).
The report also delves into the market challenges and limitations, addressing concerns related to data availability, computational resources, regulatory considerations, and ethical implications surrounding the development and deployment of generative biology technologies. The report explores the transformative applications of generative biology across a wide range of industries, providing in-depth analysis and case studies. In the pharmaceuticals and biotechnology sector, generative biology techniques are revolutionizing drug discovery and development, protein engineering, synthetic biology, and personalized medicine. The report examines how these computational approaches are accelerating the identification of novel drug candidates, optimizing therapeutic molecules, and enabling the engineering of advanced biotherapeutics and cellular systems. In the chemicals and materials industry, generative biology is driving the discovery of novel materials, the optimization of material properties, and the development of intelligent and adaptive materials systems. The report highlights the integration of generative models, high-throughput experimentation, and multi-objective optimization to streamline the design and commercialization of innovative materials. The application of generative biology in software engineering and design is explored, showcasing how these techniques are being leveraged to optimize software architectures, generate algorithms and code, and create adaptive and self-organizing software solutions. The report also delves into the transformative impact of generative biology in the agriculture and environmental sectors, including crop engineering, microbial engineering, bioremediation, and the development of advanced biosensing systems. Furthermore, the report examines the emerging applications of generative biology in other industries, such as aerospace, energy, consumer goods, intelligent systems, and finance, highlighting the cross-pollination of ideas and the potential for broader societal impact.
The report provides a comprehensive market forecast for the global generative biology market, projecting a compound annual growth rate (CAGR) of 25-30% from 2024 to 2035. This growth trajectory is driven by the continued advancements in computational techniques, the increasing adoption across diverse industries, and the convergence of generative biology with other emerging technologies. Detailed market size and forecast data are presented, segmented by technology, application, end-user industry, and geographic region. The report identifies the key growth opportunities and strategic recommendations for market players to capitalize on the expanding generative biology landscape.
The report profiles 97 companies and innovative start-ups shaping the global generative biology market, including technology giants, specialized software providers, and pioneering biotechnology firms. It analyzes the strategic initiatives, product offerings, and financial performance of these key market players, providing valuable insights into the competitive dynamics and growth strategies within the industry. Companies profiled include Absci, BigHat Biosciences, BioAge Labs, Bioptimus, Cradle, Deepcell, Evozyne, Generate:Biomedicines, Iambic Therapeutics, Insilico Medicine, Leash Biosciences, Model Medicines, Noetik, Profluent Bio, Terray Therapeutics, Xaira and Yoneda Labs (Full list in table of contents).
1 RESEARCH METHODOLOGY 12
2 INTRODUCTION 13
- 2.1 What is generative biology? 13
- 2.2 Historical development 15
- 2.3 Key techniques 15
- 2.3.1 Generative Models 16
- 2.3.1.1 Generative Adversarial Networks (GANs) 16
- 2.3.1.2 Variational Autoencoders (VAEs) 17
- 2.3.1.3 Normalizing Flows 17
- 2.3.1.4 Autoregressive Models 17
- 2.3.1.5 Evolutionary Generative Models 18
- 2.3.2 Design Optimization 18
- 2.3.2.1 Evolutionary Algorithms (e.g., Genetic Algorithms, Evolutionary Strategies) 18
- 2.3.2.2 Reinforcement Learning 19
- 2.3.2.3 Multi-Objective Optimization 19
- 2.3.2.4 Bayesian Optimization 20
- 2.3.3 Computational Biology 21
- 2.3.3.1 Molecular Dynamics Simulations 21
- 2.3.3.2 Quantum Mechanical Calculations 22
- 2.3.3.3 Systems Biology Modeling 22
- 2.3.3.4 Metabolic Engineering Modeling 23
- 2.3.4 Data-Driven Approaches 24
- 2.3.4.1 Machine Learning 24
- 2.3.4.2 Graph Neural Networks 25
- 2.3.4.3 Unsupervised Learning 25
- 2.3.4.4 Active Learning and Bayesian Optimization 25
- 2.3.5 Agent-Based Modeling 26
- 2.3.6 Hybrid Approaches 27
- 2.3.1 Generative Models 16
3 MARKET ANALYSIS 29
- 3.1 Market drivers 29
- 3.2 Market map and competitive landscape 30
- 3.3 Investment in generative biology 32
- 3.4 Industry collaborations 34
- 3.5 Market challenges 36
- 3.6 Application Areas 38
- 3.6.1 Drug discovery and development 38
- 3.6.1.1 Proteins 38
- 3.6.1.2 New therapeutic small molecules 40
- 3.6.1.3 RNA therapeutics 40
- 3.6.1.4 Protein degraders 41
- 3.6.1.5 Other Emerging Areas 41
- 3.6.2 Materials design and optimization 42
- 3.6.2.1 Novel Materials Discovery 42
- 3.6.2.2 Materials Optimization 43
- 3.6.2.3 Materials Simulation and Modeling 43
- 3.6.2.4 High-Throughput Screening and Experimentation 44
- 3.6.2.5 Materials-by-Design 45
- 3.6.2.6 Intelligent Materials Systems 45
- 3.6.3 Synthetic biology 45
- 3.6.3.1 Genetic Circuit Design 47
- 3.6.3.2 Metabolic Pathway Engineering 48
- 3.6.3.3 Whole-Cell Modelling and Design 49
- 3.6.3.4 Directed Evolution and Protein Engineering 49
- 3.6.3.5 Synthetic Ecology and Microbiome Engineering 50
- 3.6.3.6 Automated Design and Prototyping 51
- 3.6.4 Software engineering and design 52
- 3.6.4.1 Software Architecture Design 52
- 3.6.4.2 Algorithm and Code Generation 53
- 3.6.4.3 Adaptive and Self-Organizing Software 54
- 3.6.4.4 Software Product Lines and Variability Management 54
- 3.6.4.5 Human-Computer Interaction and User Experience Design 55
- 3.6.5 Agricultural biotechnology and bioremediation 56
- 3.6.5.1 Crop Engineering 56
- 3.6.5.2 Microbial Engineering for Agriculture 57
- 3.6.5.3 Biofertilizer and Biopesticide Development 57
- 3.6.5.4 Bioremediation and Environmental Restoration 58
- 3.6.5.5 Biomass and Biofuel Production 59
- 3.6.5.6 Biosensing and Monitoring 60
- 3.6.1 Drug discovery and development 38
- 3.7 End use markets 61
- 3.7.1 Pharmaceuticals and biotechnology 62
- 3.7.1.1 Drug Discovery and Development 62
- 3.7.1.2 Protein Engineering and Biotherapeutics 63
- 3.7.1.3 Synthetic Biology and Cellular Engineering 64
- 3.7.1.4 Precision Medicine and Personalized Therapeutics 65
- 3.7.1.5 SWOT analysis 66
- 3.7.1.6 Key market players 67
- 3.7.2 Chemicals and materials 68
- 3.7.2.1 Novel Materials Discovery 69
- 3.7.2.2 Materials Optimization 69
- 3.7.2.3 High-Throughput Screening and Experimentation 70
- 3.7.2.4 Materials-by-Design 70
- 3.7.2.5 Intelligent and Adaptive Materials 71
- 3.7.2.6 SWOT analysis 72
- 3.7.2.7 Key market players 73
- 3.7.3 Technology and software 75
- 3.7.3.1 Software Architecture Design 75
- 3.7.3.2 Algorithm and Code Generation 75
- 3.7.3.3 Software Optimization and Refactoring 76
- 3.7.3.4 Adaptive and Self-Organizing Software 77
- 3.7.3.5 Software Product Lines and Variability Management 78
- 3.7.3.6 Human-Computer Interaction and User Experience Design 79
- 3.7.3.7 SWOT analysis 80
- 3.7.3.8 Key market players 82
- 3.7.4 Agriculture and environment 83
- 3.7.4.1 Crop Engineering 83
- 3.7.4.2 Microbial Engineering for Agriculture 83
- 3.7.4.3 Biofertilizer and Biopesticide Development 84
- 3.7.4.4 Bioremediation and Environmental Restoration 85
- 3.7.4.5 Biomass and Biofuel Production 85
- 3.7.4.6 Biosensing and Monitoring 86
- 3.7.4.7 SWOT analysis 88
- 3.7.4.8 Key market players 90
- 3.7.5 Other industries 92
- 3.7.5.1 Aerospace and Defense 92
- 3.7.5.2 Energy and Sustainability 93
- 3.7.5.3 Consumer Goods and Manufacturing 94
- 3.7.5.4 Intelligent Systems and Robotics 94
- 3.7.1 Pharmaceuticals and biotechnology 62
- 3.8 Market Size and Forecast, 2020-2035 (USD Billion) 96
- 3.8.1 By Technology 96
- 3.8.2 By Application 100
- 3.8.3 By End-User Industry 104
- 3.8.4 By Geographic Regions 108
4 COMPANY PROFILES 112
- 4.1 Absci Corp 112
- 4.2 AI Proteins 113
- 4.3 Alto Neuroscience 113
- 4.4 Amgen 114
- 4.5 Amply Discovery 115
- 4.6 AQEMIA 116
- 4.7 Amphista Therapeutics 116
- 4.8 AstraZeneca 117
- 4.9 Arzeda 118
- 4.10 Athos Therapeutics 119
- 4.11 Atomwise 120
- 4.12 Aurigene Pharmaceutical Services 121
- 4.13 Avicenna Biosciences 122
- 4.14 Basecamp Research 123
- 4.15 BenevolentAI 124
- 4.16 BigHat Biosciences 124
- 4.17 BioAge Labs 125
- 4.18 Biolexis Therapeutics 126
- 4.19 BioMap 127
- 4.20 Biomatter Designs 128
- 4.21 BioPhy 129
- 4.22 Bioptimus SAS 130
- 4.23 Cambrium GmbH 130
- 4.24 Century Health Technology, Inc. 131
- 4.25 Cradle 132
- 4.26 Deepcell 133
- 4.27 DeepCure 134
- 4.28 Deep Genomics 135
- 4.29 Design Therapeutics 136
- 4.30 Diagonal Therapeutics 137
- 4.31 Diffuse Bio 137
- 4.32 Etcembly 138
- 4.33 Evaxion Biotech A/S 139
- 4.34 Evozyne 140
- 4.35 Exscientia 140
- 4.36 Genie TechBio 141
- 4.37 Gene2Lead 142
- 4.38 Generate:Biomedicines 142
- 4.39 Genesis Therapeutics 143
- 4.40 Gero 144
- 4.41 GlaxoSmithKline (GSK) 145
- 4.42 Google Deepmind 146
- 4.43 Healx 147
- 4.44 Iambic Therapeutics 148
- 4.45 Ibex Medical Analytics 149
- 4.46 Idoven 150
- 4.47 Iktos 151
- 4.48 Inceptive 152
- 4.49 Insilico Medicine 153
- 4.50 Insitro 154
- 4.51 Isomorphic Laboratories 155
- 4.52 Integrated Biosciences 156
- 4.53 Kuano 156
- 4.54 Leash Biosciences 157
- 4.55 Mana.bio 158
- 4.56 Medeloop 159
- 4.57 Menten AI 159
- 4.58 MiLaboratories, Inc. 160
- 4.59 Model Medicines 161
- 4.60 Molecular Quantum Solutions 161
- 4.61 Nabla Bio 162
- 4.62 Noetik 163
- 4.63 Nobias Therapeutics 163
- 4.64 Novo Nordisk 164
- 4.65 Nucleai 165
- 4.66 NVIDIA 166
- 4.67 Odyssey Therapeutics 166
- 4.68 Orbital Materials 167
- 4.69 Ordaos Bio 168
- 4.70 Owkin 169
- 4.71 Perpetual Medicines 170
- 4.72 Polaris Quantum Biotech (POLARISqb) 171
- 4.73 PredxBio 172
- 4.74 Profluent Bio 172
- 4.75 ProPhase Labs 173
- 4.76 ProteinQure 174
- 4.77 QuantHealth 175
- 4.78 Recursion Pharmaceuticals 176
- 4.79 Relay Therapeutics 176
- 4.80 Roche 177
- 4.81 Roivant Sciences 178
- 4.82 Sanofi 178
- 4.83 Schrödinger 179
- 4.84 Seismic Therapeutic 180
- 4.85 SimBioSys 181
- 4.86 Superluminal Medicines 182
- 4.87 T-Cypher Bio 183
- 4.88 Ten63 Therapeutics 183
- 4.89 Terray Therapeutics 184
- 4.90 TRexBio 185
- 4.91 Valo Health 186
- 4.92 VantAI 187
- 4.93 Verge Genomics 188
- 4.94 Xaira Therapeutics 189
- 4.95 Xtalpi 189
- 4.96 Yoneda Labs 191
- 4.97 Zephyr AI 191
5 GLOSSARY 193
6 REFERENCES 195
List of Tables
- Table 1. Key techniques in generative biology. 15
- Table 2. Market drivers for generative biology. 29
- Table 3. Generative biology investments 2020-2024. 33
- Table 4. Industry collaborations in generative biology. 34
- Table 5. Generative biology market challenges and limitations. 36
- Table 6. Comparison of synthetic biology and genetic engineering. 47
- Table 7. Applications of Generative Biology Across Key Markets. 61
- Table 8. Generative biology in drug discovery and development. 62
- Table 9. Generative biology in protein engineering and biotherapeutics. 63
- Table 10. Generative biology in synthetic biology and cellular engineering. 64
- Table 11. Generative biology in precision medicine and personalized therapeutics, 65
- Table 12. Key market players in Generative biology in Pharmaceuticals and Biotechnology. 67
- Table 13. Generative biology in chemicals and materials. 68
- Table 14. Key market players in Generative biology in Chemicals and materials. 73
- Table 15. Applications of generative biology in software optimization and refactoring. 76
- Table 16. Key market players in Generative biology in Technology and software. 82
- Table 17. Key market players in Generative biology in Agriculture and environment. 90
- Table 18. Generative biology in aerospace and defence. 92
- Table 19. Generative biology applications in energy and sustainability. 93
- Table 20. Generative biology applications in consumer goods and manufacturing. 94
- Table 21. Generative biology applications in intelligent systems and robotics. 94
- Table 22. Global Generative Biology Market Size and Forecast, 2020-2035 (USD Billion), by technology, Conservative Estimate. 96
- Table 23. Global Generative Biology Market Size and Forecast, 2020-2035 (USD Billion), by technology, Optimistic Estimate. 98
- Table 24. Global Generative Biology Market Size and Forecast, 2020-2035 (USD Billion), by application, Conservative Estimate. 100
- Table 25. Global Generative Biology Market Size and Forecast, 2020-2035 (USD Billion), by application, Optimistic Estimate. 102
- Table 26. Global Generative Biology Market Size and Forecast, 2020-2035 (USD Billion), by End-User Industry, Conservative Estimate. 104
- Table 27. Global Generative Biology Market Size and Forecast, 2020-2035 (USD Billion), by End-User Industry, Optimistic Estimate. 106
- Table 28. Global Generative Biology Market Size and Forecast, 2020-2035 (USD Billion), by Region, Conservative Estimate. 108
- Table 29. Global Generative Biology Market Size and Forecast, 2020-2035 (USD Billion), by Region, Optimistic Estimate. 110
- Table 30. Glossary of terms. 193
List of Figures
- Figure 1. The design-make-test-learn loop of generative biology. 14
- Figure 2. Historical development of generative biology. 15
- Figure 3. Market map for generative biology. 32
- Figure 4. Investment in generative biology 2020-2024 (Millions USD). 33
- Figure 7. The composition of human proteins. 38
- Figure 8. SWOT analysis: Generative biology in Pharmaceuticals and Biotechnology. 67
- Figure 9. SWOT analysis: Generative biology in Chemicals and materials. 73
- Figure 10. SWOT analysis: Generative biology in Technology and software. 81
- Figure 11. SWOT analysis: Generative biology in Agriculture and environment. 89
- Figure 12.Global Generative Biology Market Size and Forecast, 2020-2035 (USD Billion), by technology, Conservative Estimate. 97
- Figure 13. Global Generative Biology Market Size and Forecast, 2020-2035 (USD Billion), by technology, Optimistic Estimate. 99
- Figure 14. Global Generative Biology Market Size and Forecast, 2020-2035 (USD Billion), by application, Conservative Estimate. 101
- Figure 15. Global Generative Biology Market Size and Forecast, 2020-2035 (USD Billion), by application, Optimistic Estimate. 103
- Figure 16. Global Generative Biology Market Size and Forecast, 2020-2035 (USD Billion), by End-User Industry, Conservative Estimate. 105
- Figure 17. Global Generative Biology Market Size and Forecast, 2020-2035 (USD Billion), by End-User Industry, Optimistic Estimate. 107
- Figure 18. Global Generative Biology Market Size and Forecast, 2020-2035 (USD Billion), by Region, Conservative Estimate. 109
- Figure 19. Global Generative Biology Market Size and Forecast, 2020-2035 (USD Billion), by Region, Optimistic Estimate. 111
- Figure 20. XtalPi’s automated and robot-run workstations. 190
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