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The Global Market for Generative Biology 2024-2035

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  • 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

 

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
  • 3.7         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
  • 3.8         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

 

 

The Global Market for Generative Biology 2024-2035
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