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LSH
The global white (industrial) biotechnology market is experiencing significant growth, driven by increasing demand for sustainable alternatives to traditional petroleum-based products. White biotechnology leverages biological systems, enzymes, and microorganisms to produce chemicals, materials, and energy through environmentally friendly processes. With rising environmental concerns, government regulations supporting bio-based products, and technological advancements in synthetic biology, the sector is poised for substantial expansion. The market is characterized by diverse applications across multiple industries including biofuels, bio-based chemicals, bioplastics, pharmaceuticals, food ingredients, textiles, and construction materials. Major growth drivers include carbon taxation policies, increasing consumer preference for sustainable products, and corporate sustainability commitments. The transition toward circular economy principles is further accelerating adoption as white biotechnology enables the valorization of various waste streams including agricultural residues, forestry waste, municipal solid waste, and industrial by-products.
Technological innovations in synthetic biology, metabolic engineering, and the emerging field of generative biology are dramatically improving production efficiencies and expanding the range of possible bio-manufactured molecules. Advanced fermentation processes, cell-free systems, and the development of novel microbial chassis organisms are contributing to increased commercial viability of white biotechnology products.
Report Contents include:
Market Analysis and Forecasts 2025-2035
Global market revenues by molecule type
Market segmentation by application sector
Regional market analysis and growth projections
Competitive landscape and key player positioning
Technology Landscape Assessment
Production hosts (bacteria, yeast, fungi, marine organisms)
Biomanufacturing processes and optimization techniques
Synthetic biology advancements and applications
Generative biology approaches and impact
Feedstock analysis and alternative resource utilization
Application Sector Analysis
Biofuels (bioethanol, biodiesel, biogas, biojet fuel)
Bio-based chemicals (organic acids, alcohols, monomers)
Bioplastics and biopolymers (PLA, PHAs, bio-PET)
Food and nutraceutical ingredients
Agricultural biotechnology
Textile applications
Pharmaceuticals and cosmetics
Construction materials
Sustainability and Circular Economy Integration
White biotechnology for waste valorization
Carbon capture utilization
Industrial symbiosis opportunities
Environmental impact assessment
Strategic Insights and Opportunities
Technology adoption trends
Regulatory landscape analysis
Investment patterns and funding environment
Strategic recommendations for market participants
Comprehensive Company Profiles
Detailed analysis of 395+ market participants
Technology platforms and proprietary processes
Commercial deployments and capacity expansions
Partnership and collaboration networks
The report provides comprehensive profiles of over 395 companies operating across the industrial biotechnology value chain. These include established industry leaders like Novozymes, Braskem, LanzaTech, and Corbion, alongside innovative startups developing novel technologies and applications. The diverse ecosystem encompasses specialized synthetic biology platforms (Ginkgo Bioworks, Arzeda), biofuel producers (Aemetis, Gevo), bioplastics manufacturers (NatureWorks, Total Energies Corbion, Danimer Scientific), bio-based chemical developers (Avantium, METEX), cell-free system innovators (EnginZyme, Solugen), and companies focused on emerging applications like biocement (Biomason) and bio-textiles (Bolt Threads, Modern Meadow, Spiber). The landscape also includes AI-driven biotechnology platforms (Asimov, Zymergen) and specialized waste-to-value companies (Celtic Renewables, Full Cycle Bioplastics). This comprehensive company analysis provides unparalleled insights into the competitive dynamics, technological capabilities, and strategic positioning of key market participants across the global industrial biotechnology ecosystem.
TABLE OF CONTENTS
1. EXECUTIVE SUMMARY
1.1. Biotechnology "colours"
1.2. Definition
1.3. Comparison with conventional processes
1.4. Markets and applications
1.5. Advantages
1.6. Sustainability
1.7. White Biotechnology for the Circular Economy
1.7.1. Agricultural Waste
1.7.2. Forestry and Paper Waste
1.7.3. Gas Fermentation
1.7.4. Plastics Upcycling
1.7.5. Wastewater Valorization
2. TECHNOLOGY ANALYSIS
2.1. Production hosts
2.1.1. Bacteria
2.1.2. Yeast
2.1.3. Fungi
2.1.4. Marine
2.1.5. Enzymes
2.1.6. Photosynthetic organisms
2.2. Biomanufacturing processes
2.2.1. Batch biomanufacturing
2.2.2. Continuous biomanufacturing
2.2.3. Cell factories for biomanufacturing
2.2.4. Industry-Specific Microorganism Applications
2.2.4.1. Escherichia coli (E. coli)
2.2.4.2. Corynebacterium glutamicum (C. glutamicum)
2.2.4.3. Bacillus subtilis (B. subtilis)
2.2.4.4. Saccharomyces cerevisiae (S. cerevisiae)
2.2.4.5. Yarrowia lipolytica (Y. lipolytica)
2.2.5. Machine learning
2.2.6. Downstream processing
2.2.7. Perfusion bioreactors
2.2.8. Tangential flow filtration (TFF)
2.2.9. Hybrid biotechnological-chemical approaches
2.2.10. Process intensification and high-cell-density fermentation
2.3. Synthetic Biology
2.3.1. Technology Overview
2.3.2. Synthetic biology applied to white biotechnology
2.3.3. Metabolic engineering
2.3.3.1. DNA synthesis
2.3.3.2. CRISPR
2.3.3.2.1. CRISPR/Cas9-modified biosynthetic pathways
2.3.4. Protein/Enzyme Engineering
2.3.4.1. Computer-aided Design
2.3.4.2. Synthetic Biology and Metabolic Engineering (200 words)
2.3.4.3. Industrial Microbial Strains
2.3.4.4. Scaling
2.3.5. Strain construction and optimization
2.3.6. Smart bioprocessing
2.3.7. Cell-free systems
2.3.8. Chassis organisms
2.3.9. Biomimetics
2.3.10. Sustainable materials
2.3.11. Robotics and automation
2.3.11.1. Robotic cloud laboratories
2.3.11.2. Automating organism design
2.3.11.3. Artificial intelligence and machine learning
2.3.11.4. Automating Organism Design
2.3.11.5. De Novo Protein Prediction
2.3.11.6. Companies
2.3.12. Fermentation Processes
2.4. Generative Biology
2.4.1. Generative Models
2.4.2. Generative Adversarial Networks (GANs)
2.4.2.1. Variational Autoencoders (VAEs)
2.4.2.2. Normalizing Flows
2.4.2.3. Autoregressive Models
2.4.2.4. Evolutionary Generative Models
2.4.3. Design Optimization
2.4.3.1. Evolutionary Algorithms (e.g., Genetic Algorithms, Evolutionary Strategies)
2.4.3.1.1. Genetic Algorithms (GAs)
2.4.3.1.2. Evolutionary Strategies (ES)
2.4.3.2. Reinforcement Learning
2.4.3.3. Multi-Objective Optimization
2.4.3.4. Bayesian Optimization
2.4.4. Computational Biology
2.4.4.1. Molecular Dynamics Simulations
2.4.4.2. Quantum Mechanical Calculations
2.4.4.3. Systems Biology Modeling
2.4.4.4. Metabolic Engineering Modeling
2.4.5. Data-Driven Approaches
2.4.5.1. Machine Learning
2.4.5.2. Graph Neural Networks
2.4.5.3. Unsupervised Learning
2.4.5.4. Active Learning and Bayesian Optimization
2.4.6. Agent-Based Modeling
2.4.7. Hybrid Approaches
2.5. Feedstocks
2.5.1. C1. feedstocks
2.5.1.1. Advantages
2.5.1.2. Pathways
2.5.1.3. Challenges
2.5.1.4. Non-methane C1 feedstocks
2.5.1.5. Gas fermentation
2.5.2. C2 feedstocks
2.5.3. Biological conversion of CO2
2.5.4. Food processing wastes
2.5.5. Lignocellulosic biomass
2.5.6. Methane
2.5.7. Municipal solid wastes
2.5.8. Plastic wastes
2.5.9. Plant oils
2.5.10. Starch
2.5.11. Sugars
2.5.12. Used cooking oils
2.5.13. Carbon capture
2.5.14. Green hydrogen production
2.5.15. Blue hydrogen production
2.6. Blue biotechnology (Marine biotechnology)
2.6.1. Cyanobacteria
2.6.2. Macroalgae
2.6.3. Companies
3. MARKET ANALYSIS
3.1. Market trends
3.1.1. Demand for biobased products
3.1.2. Government regulation
3.1.3. Costs
3.1.4. Carbon taxes
3.2. Industry challenges and constraints
3.2.1. Costs
3.2.1.1. Oil prices
3.2.1.2. Green Premium
3.2.1.3. Cell Factory Cost
3.3. White biotechnology in the bioeconomy
3.4. SWOT analysis
3.5. Market map
3.6. Key market players and competitive landscape
3.7. Regulations
3.7.1. United States
3.7.2. European Union
3.7.3. International
3.7.4. Specific Regulations and Guidelines
3.8. Main end-use markets
3.8.1. Biofuels
3.8.1.1. Market supply chain
3.8.1.2. Solid Biofuels
3.8.1.3. Liquid Biofuels
3.8.1.4. Gaseous Biofuels
3.8.1.5. Conventional Biofuels
3.8.1.6. Next-generation Biofuels
3.8.1.7. Feedstocks
3.8.1.7.1. First-generation (1-G)
3.8.1.7.2. Second-generation (2-G)
3.8.1.7.2.1. Lignocellulosic wastes and residues
3.8.1.7.2.2. Biorefinery lignin
3.8.1.7.3. Third-generation (3-G)
3.8.1.7.3.1. Algal biofuels
3.8.1.7.3.1.1. Properties
3.8.1.7.3.1.2. Advantages
3.8.1.7.4. Fourth-generation (4-G)
3.8.1.7.5. Energy crops
3.8.1.7.6. Agricultural residues
3.8.1.7.7. Manure, sewage sludge and organic waste
3.8.1.7.8. Forestry and wood waste
3.8.1.7.9. Feedstock costs
3.8.1.8. Bioethanol
3.8.1.8.1. Ethanol to jet fuel technology
3.8.1.8.2. Methanol from pulp & paper production
3.8.1.8.3. Sulfite spent liquor fermentation
3.8.1.8.4. Gasification
3.8.1.8.4.1. Biomass gasification and syngas fermentation
3.8.1.8.4.2. Biomass gasification and syngas thermochemical conversion
3.8.1.8.5. CO2 capture and alcohol synthesis
3.8.1.8.6. Biomass hydrolysis and fermentation
3.8.1.8.7. Separate hydrolysis and fermentation
3.8.1.8.7.1. Simultaneous saccharification and fermentation (SSF)
3.8.1.8.7.2. Pre-hydrolysis and simultaneous saccharification and fermentation (PSSF)
3.8.1.8.7.3. Simultaneous saccharification and co-fermentation (SSCF)
3.8.1.8.7.4. Direct conversion (consolidated bioprocessing) (CBP)
3.8.1.9. Biodiesel
3.8.1.10. Biogas
3.8.1.10.1. Biomethane
3.8.1.10.2. Feedstocks
3.8.1.10.3. Anaerobic digestion
3.8.1.11. Renewable diesel
3.8.1.12. Biojet fuel
3.8.1.13. Algal biofuels (blue biotech)
3.8.1.13.1. Conversion pathways
3.8.1.13.2. Market challenges
3.8.1.13.3. Prices
3.8.1.13.4. Producers
3.8.1.14. Biohydrogen
3.8.1.14.1. Biological Conversion Routes
3.8.1.14.1.1. Bio-photochemical Reaction
3.8.1.14.1.2. Fermentation and Anaerobic Digestion
3.8.1.15. Biobutanol
3.8.1.16. Bio-based methanol
3.8.1.16.1. Anaerobic digestion
3.8.1.16.2. Biomass gasification
3.8.1.16.3. Power to Methane
3.8.1.17. Bioisoprene
3.8.1.18. Fatty Acid Esters
3.8.2. Bio-based chemicals
3.8.2.1. Market supply chain
3.8.2.2. Acetic acid
3.8.2.3. Adipic acid
3.8.2.4. Aldehydes
3.8.2.5. Acrylic acid
3.8.2.6. Bacterial cellulose
3.8.2.7. 1,4-Butanediol (BDO)
3.8.2.8. Bio-DME
3.8.2.9. Dodecanedioic acid (DDDA)
3.8.2.10. Ethylene
3.8.2.11. 3-Hydroxypropionic acid (3-HP)
3.8.2.12. 1,3-Propanediol (1,3-PDO)
3.8.2.13. Itaconic acid
3.8.2.14. Lactic acid (D-LA)
3.8.2.15. 1,5-diaminopentane (DA5)
3.8.2.16. Tetrahydrofuran (THF)
3.8.2.17. Malonic acid
3.8.2.18. Monoethylene glycol (MEG)
3.8.2.19. Propylene
3.8.2.20. Succinic acid (SA)
3.8.2.21. Triglycerides
3.8.2.22. Enzymes
3.8.2.23. Vitamins
3.8.2.24. Antibiotics
3.8.3. Bioplastics and Biopolymers
3.8.3.1. Bioplastics via white biotechnology
3.8.3.2. Biobased polymers from monosaccharides
3.8.3.3. Market supply chain
3.8.3.4. Lactic Acid and Polylactic Acid (PLA)
3.8.3.4.1. Lactic Acid (C3H6O3)
3.8.3.4.2. Industrial production of lactic acid
3.8.3.4.3. Engineering Yeast Strains for Lactic Acid Production
3.8.3.4.4. Polylactic acid (PLA) production
3.8.3.5. Succinic Acid
3.8.3.5.1. Biobased succinic acid production
3.8.3.5.2. PBS
3.8.3.6. 2,5-furandicarboxylic acid (FDCA)
3.8.3.6.1. Monomer Production
3.8.3.7. Polyethylene Furanoate (PEF)
3.8.3.8. C6 monomers
3.8.3.9. Sebacic Acid
3.8.3.10. Dodecanedioic Acid
3.8.3.11. 1,5-Pentanediamine (PDA)
3.8.3.12. 1,3-Butadiene
3.8.3.13. Isoprene
3.8.3.14. Isobutene (Isobutylene)
3.8.3.15. PHAs
3.8.3.15.1. Production of PHAs
3.8.3.15.2. PHB, PHBV, and P(3HB-co-4HB)
3.8.3.15.3. Commercial PHA landscape
3.8.3.15.4. Short and medium chain-length PHAs
3.8.3.15.5. Economic viability of PHA production
3.8.3.15.6. Risks
3.8.3.15.7. Production scale
3.8.3.15.8. PHA production landscape
3.8.3.15.9. Commercially available PHAs
3.8.3.16. Bio-PET
3.8.3.17. Starch blends
3.8.3.18. Protein-based bioplastics
3.8.4. Bioremediation
3.8.5. Biocatalysis
3.8.5.1. Biotransformations
3.8.5.2. Cascade biocatalysis
3.8.5.3. Co-factor recycling
3.8.5.4. Immobilization
3.8.6. Food and Nutraceutical Ingredients
3.8.6.1. Market supply chain
3.8.6.2. Alternative Proteins
3.8.6.3. Natural Sweeteners
3.8.6.4. Natural Flavors and Fragrances
3.8.6.5. Texturants and Thickeners
3.8.6.6. Nutraceuticals and Supplements
3.8.7. Agricultural biotechnology
3.8.7.1. Market supply chain
3.8.7.2. Biofertilizers
3.8.7.2.1. Overview
3.8.7.2.2. Companies
3.8.7.3. Biopesticides
3.8.7.3.1. Overview
3.8.7.3.2. Companies
3.8.7.4. Biostimulants
3.8.7.4.1. Overview
3.8.7.4.2. Companies
3.8.7.5. Crop Biotechnology
3.8.7.5.1. Genetic engineering
3.8.7.5.2. Genome editing
3.8.7.5.3. Companies
3.8.8. Textiles
3.8.8.1. Market supply chain
3.8.8.2. Bio-Based Fibers
3.8.8.2.1. Lyocell
3.8.8.2.2. Bacterial cellulose
3.8.8.2.3. Algae textiles
3.8.8.3. Spider silk
3.8.8.4. Collagen-derived textiles
3.8.8.5. Recombinant Materials
3.8.8.6. Sustainable Processing
3.8.9. Consumer goods
3.8.9.1. Market supply chain
3.8.9.2. White biotechnology in consumer goods
3.8.10. Biopharmaceuticals
3.8.10.1. Market supply chain
3.8.10.2. Market overview for white biotechnology
3.8.11. Cosmetics
3.8.11.1. Market supply chain
3.8.11.2. Market overview for white biotechnology
3.8.12. Surfactants and detergents
3.8.12.1. Market supply chain
3.8.12.2. Market overview for white biotechnology
3.8.13. Construction materials
3.8.13.1. Market supply chain
3.8.13.2. Biocement
3.8.13.3. Mycelium materials
3.9. Global market revenues 2018-2035
3.9.1. By molecule
3.9.2. By market
3.9.3. By region
3.10. Future Market Outlook
4. COMPANY PROFILES (396 company profiles)
5. APPENDIX
5.1. Research methodology
5.2. Acronyms
5.3. Glossary of Terms
6. REFERENCES