Where is there still room in synthetic biology?
In our synthetic biology market deck, you will find everything you need to understand the market
SUMMARY
There is still plenty of room in synthetic biology, but mainly in narrow bottlenecks and high-value products rather than another broad platform promising to program biology for everything.
The first synthetic biology cycle exposed the weakness of platform-first economics. Ginkgo Bioworks, Zymergen and Amyris failed in different ways, but all showed how quickly technical breadth becomes expensive when product-market fit, customer economics or downstream margins lag behind.
Funding has not disappeared; it has become much more concentrated. Large rounds still happen when investors can see a specific technical edge, a concrete product and a believable path to a very large outcome, while generic platform stories have become much harder to finance.
AI is changing where defensibility sits. Protein and biological design models are becoming easier to access, so the durable advantage is increasingly the proprietary experimental loop: running real tests, collecting clean data and improving the next design from results competitors cannot easily reproduce.
That makes autonomous labs the strongest infrastructure opening in the sector. AI can already generate more plausible biological ideas than conventional labs can test efficiently, and both public funding and commercial deployments are now moving toward closed-loop experimentation.
DNA synthesis remains open at the difficult end of the market. Standard ordering is mature, but longer constructs, faster turnaround, decentralized manufacturing, verification and secure on-demand synthesis are still improving fast enough to create new businesses.
Industrial synthetic biology still runs into the same ugly problem: scale-up. A strain that works in a small vessel can fall apart in a real fermenter, leaving room for scale-down systems, sensors, process-control software, purification tools and flexible pilot infrastructure.
The better product opportunities are the ones where biology gives the customer something hard to get another way. Engineered enzymes, scarce proteins, unusual biomaterials, agricultural traits and strategically important chemicals look stronger than bulk commodity replacements sold mainly on sustainability.
Precision-fermented food is therefore selective rather than broadly attractive. Premium or functionally scarce proteins can work; low-value bulk proteins still have to fight unforgiving manufacturing economics and entrenched supply chains.
Therapeutics remains wide open scientifically, but the entry bar is high. Investors are still backing differentiated modalities and programs that are already tied to a real medicine, while another general discovery platform with distant applications will struggle to stand out.
Biosecurity and domestic biomanufacturing are becoming more credible markets as synthesis becomes more distributed and governments care more about supply resilience. China makes commodity fermentation harder for Western startups, but that same pressure can strengthen the case for critical chemicals, secure synthesis and local production where origin actually changes the buying decision.
This market map, featured in our synthetic biology market deck, highlights top companies and startups in the synthetic biology market
Did the first big synthetic biology startup model actually fail?
Yes. Broad synthetic biology platforms have taken a real beating, and startups now need a much narrower reason to exist.
Ginkgo Bioworks is the clearest current example. In its latest reported quarter, revenue fell 48% year over year to $20 million. Revenue for the first half of the year was about $40 million, compared with $77 million over the same period a year earlier. The company still had $302 million in cash and marketable securities, but it was guiding to another $125 million to $150 million of cash burn for the full year.
That decline follows two much more dramatic failures from the previous synthetic biology cycle. Zymergen entered the public market at roughly a $3 billion valuation, then acknowledged that its first major products would generate essentially no near-term revenue. Ginkgo bought the company the following year in a deal worth roughly $300 million. Amyris went further downstream into ingredients and consumer brands, reached real industrial production, and still ended up in Chapter 11 with liabilities well above its reported asset range.
Three companies, three different problems, but the pattern is hard to ignore. Investors paid for broad technical platforms before anyone had proved that enough valuable products could move through them quickly enough to support the cost base. A new company these days needs to show which bottleneck it owns, who pays to remove it and why that budget can become large.
| Company | What investors originally backed | What happened | What a new startup should learn |
|---|---|---|---|
| Ginkgo Bioworks | A broad organism-engineering foundry | Latest quarterly revenue fell 48% year over year while the company narrowed its focus around autonomous labs | Platform breadth means little without repeatable customer economics |
| Zymergen | Automated biology feeding proprietary materials and products | Roughly $3B IPO valuation followed by a sale at about $300M | Product-market fit has to arrive before platform spending gets too large |
| Amyris | Engineered organisms, industrial fermentation and downstream products | Reached commercial production but ultimately filed for bankruptcy | Manufacturing success alone does not fix capital intensity or weak downstream economics |
If you want more recent data on this point, please see our latest synthetic biology market report.
Are investors still funding synthetic biology now?
Yes, but synthetic biology funding is much more concentrated than the big round announcements make it look.
Our review of 52 disclosed synthetic biology financings across five consecutive quarters found roughly $1.61 billion of funding in total. The average round was about $31 million, but that average hides a highly uneven market. In the most recent completed quarter, eight companies raised roughly $502 million, and NewLimit's $435 million round represented almost 87% of the entire quarter.
That concentration is more revealing than the headline total. Investors are still willing to write enormous checks when a company has a very specific technical edge and a believable path to a huge outcome. NewLimit is moving an epigenetic reprogramming program toward human trials. Tropic raised $105 million after getting gene-edited bananas into the market. Epicrispr recently raised another $90 million after reporting early human data from its programmable epigenetic therapy.
Smaller rounds continue across enzymes, biomanufacturing tools, agriculture and biological AI, but investors are asking much harder questions about how those companies eventually make money. A startup can still raise a lot of money today, but “large biological platform with many possible applications” has become a much weaker pitch than “we have already removed this expensive bottleneck.”
As this chart shows, and as featured in our synthetic biology market deck, search interest in gene editing has grown significantly
Is AI making synthetic biology software too easy to copy?
Yes. Generic AI for protein and biological design is getting easier to copy, while proprietary experimental feedback is becoming much harder to reproduce.
The model layer has moved extraordinarily fast. Systems such as BoltzGen can generate proteins and peptides against biological targets, and the model, training code and inference code have been released under a permissive license. A founder can now start with capabilities that would have required a serious internal research team only a short time ago.
Cradle gives us a better picture of where software can still become valuable. The company says its platform is now used across more than 50 R&D programs and by six of the world's 25 largest pharmaceutical companies. Bayer selected Cradle after a proof of concept and is using the platform inside antibody-design workflows. The valuable part is the connection between computational design and the scientist's next real experiment: potency, stability, expression, manufacturability and other constraints all have to be optimized together.
A protein can look impressive in silico and then express badly, aggregate, lose activity under manufacturing conditions or fail one of several properties required by the customer. That leaves room for companies that own the design-test-learn loop and accumulate experimental data competitors cannot easily recreate.
Are autonomous labs the biggest open infrastructure market in synthetic biology?
Autonomous labs are probably the clearest synthetic biology infrastructure opening right now.
AI has made biological hypotheses much cheaper to generate, but physical experiments still take instruments, consumables, preparation, quality control and time. Researchers can already generate more plausible ideas than conventional laboratories can efficiently test.
A recent experiment between OpenAI and Ginkgo showed what a tighter loop can look like. GPT-5 was connected to an automated laboratory and asked to optimize cell-free protein synthesis. Across roughly 36,000 reactions and six experimental rounds, the system reduced production cost per gram by 40% compared with the benchmark used in the study while increasing protein titer by 27%.
The public spending arriving around the same problem is unusually large. The National Science Foundation recently committed $380 million to 20 teams building a national network of AI-enabled automated laboratories, with additional philanthropic funding taking the program to about $400 million. The broader federal Genesis Mission now includes autonomous experimentation and biological scale-up among its national AI-for-science priorities.
Ginkgo's own business is also moving aggressively in this direction. Alongside the weak financial results discussed earlier, the company has recently won work to build autonomous laboratories for MIT, Caltech, Northwestern and the University of Maryland.
There should be room below and beside the giant general-purpose cloud lab. A company could own autonomous protein engineering, cell-line development, metabolic optimization, analytical chemistry or another narrow workflow where customers run the same expensive experimental loop again and again.
If you want more recent data on this point, please see our latest synthetic biology market report.
This chart, featured in our synthetic biology market deck, illustrates yearly VC funding for synthetic biology startups
Is DNA synthesis still an unsolved synthetic biology market?
Yes. Standard DNA ordering is mature, but long, difficult and on-demand DNA synthesis is still improving quickly.
Ansa Biotechnologies currently sells sequence-verified clonal DNA up to 50 kilobases long. Its latest commercial specifications advertise turnaround times as short as 11 business days and pricing starting around $0.13 per base pair for parts of the range. A few years ago, Ansa's initial commercial products were below one kilobase. Moving from hundreds of bases to constructs measured in tens of thousands materially expands what customers can outsource.
The incumbent response makes the opportunity more convincing. Integrated DNA Technologies, part of Danaher and one of the established DNA-synthesis suppliers, has added Ansa's products to its own synthetic biology portfolio. Customers can now order Ansa-built constructs from 100 base pairs to 50 kilobases through IDT.
DNA Script is attacking another part of the same market: making DNA where it is needed rather than shipping every sequence from a central factory. The company and GE HealthCare were recently awarded up to $26 million through ARPA-H to develop a modular, automated system for cell-free DNA manufacturing. The idea is effectively a secure DNA printer that could eventually sit closer to research groups and personalized-medicine manufacturing.
The remaining room in DNA synthesis sits around complexity, length, turnaround time, decentralization, verification and security. Making previously painful DNA routine still has real value.
Is scale-up now the biggest bottleneck in industrial synthetic biology?
For industrial synthetic biology, scale-up is now the bottleneck we would worry about before almost anything else.
A strain performing well in a small laboratory vessel says surprisingly little about what happens inside an industrial fermenter. Large reactors develop oxygen, nutrient, temperature and mixing gradients. Cells experience changing conditions as they circulate through the vessel. A strain optimized under uniform lab conditions can lose productivity once those stresses appear.
The economics then compound the problem. A recent Nature Communications review noted that many conventional commodity chemicals sell for only around $1 to $5 per kilogram. Biological production has to compete with chemical plants that are already huge, optimized and often largely depreciated. Even a successful fermentation process can lose the economic battle through lower productivity, expensive feedstock, purification costs or an oversized reactor.
The U.S. Department of Defense has reached a similar conclusion from a completely different angle. A recent GAO review found that DOD officials consider insufficient domestic infrastructure the primary constraint holding promising biotechnology back from commercial production. The report specifically pointed to a shortage of pilot-scale facilities.
That leaves room for industrially realistic scale-down systems, better bioreactor sensors, process-control software, downstream purification, strain-robustness testing and flexible pilot capacity.
| Stage | What synthetic biology can do fairly well | What still goes wrong | Where a startup can help |
|---|---|---|---|
| Biological design | Generate strains, proteins and pathways much faster | A promising design can fail under real process conditions | Better prediction tied to experimental process data |
| Lab validation | Screen many variants in small volumes | Small vessels hide industrial stresses | Scale-down systems that reproduce large-reactor conditions |
| Pilot production | Prove that a process can run beyond the bench | Pilot capacity is scarce and expensive | Flexible shared pilot infrastructure and faster process development |
| Commercial production | Produce many biological products at industrial volume | Productivity, purification and unit economics can deteriorate | Process control, monitoring, robust strains and downstream technology |
This chart, featured in our synthetic biology market deck, shows how Twist Bioscience is capturing share in synthetic biology
Is precision-fermented food still worth building?
Only selectively. Precision fermentation still makes sense in food when the protein is scarce, functional or valuable enough to absorb the manufacturing cost.
According to the Good Food Institute's latest industry review, fermentation companies focused on alternative proteins raised $357 million in 2025. That was down sharply from the previous year, and the largest rounds increasingly went toward commercialization rather than open-ended R&D.
Bulk replacement protein remains hard. Fermentation capacity is expensive, purification can be expensive, feedstocks matter, and conventional dairy or plant proteins already benefit from enormous supply chains.
Vivici shows a more attractive route. The company first secured customer offtake for precision-fermented beta-lactoglobulin, raised €32.5 million to expand production and then moved into lactoferrin. Lactoferrin is particularly interesting because natural supply is limited and expensive. Vivici has now launched its fermentation-produced version in the U.S. market after reaching self-affirmed GRAS status.
The Protein Brewery offers another version of the commercialization test. The company recently added €18 million to its Series B after receiving European authorization for its fermented mycelium ingredient and is using the money to expand production and launch commercially.
Food still looks open where fermentation unlocks a protein that is difficult to obtain, gives formulators a property they care about or fits into an existing premium category.
If you want more recent data on this point, please see our latest synthetic biology market report.
Which molecules and enzymes are actually worth making with synthetic biology?
The best synthetic biology products today are molecules and enzymes where biology changes performance, scarcity or industrial economics enough to justify the cost.
AMSilk is a useful example because its silk proteins are sold for what they can do. The company has moved from material demonstrations into actual products: its bioengineered yarn appears in commercially available Balenciaga garments, while other formulations are being developed for coatings and personal-care products. AMSilk has also signed longer-term manufacturing agreements with established industrial partners including Evonik and Ajinomoto rather than trying to build every fermentation plant itself.
Constructive Bio pushes the idea further. Its technology rewrites genomes and expands the genetic code so cells can incorporate amino acids outside biology's standard set. The company has raised $75 million in total, including a $58 million Series A, and is initially applying that capability to proteins and peptides with chemical properties that conventional biological manufacturing cannot easily produce.
Engineered enzymes can be even more attractive because a small biological input can improve a much larger industrial process. Samsara Eco's enzymes break nylon and other difficult polymers back into reusable chemical building blocks. KBR is designing a commercial plant around the process with planned capacity of 20,000 tonnes of nylon 6,6 per year. Samsara has already worked with lululemon on products using enzymatically recycled nylon and polyester.
Epoch Biodesign is chasing a similar industrial problem with a different technology stack. The company recently raised another $12 million, bringing total funding above $50 million, and is building a demonstration facility for enzymatic nylon recycling. It also signed an agreement with INVISTA, one of the major nylon producers, while moving from multi-tonne toward multi-kilotonne production.
There is fresh activity at the enzyme-design layer too. Imperagen recently raised £5 million to combine physics-based simulation, AI and experimental testing for industrial enzyme engineering. The company is explicitly targeting enzyme candidates that look good during early optimization but perform badly under industrial conditions.
This is the kind of synthetic biology we like much more than bulk commodity replacement. Performance materials, scarce proteins, industrial enzymes, hard-to-make pharmaceutical intermediates and strategically important chemicals all give biology a reason to win beyond sustainability alone.
This chart, featured in our synthetic biology market deck, illustrates yearly funding for synthetic biology startups
Is agriculture one of the clearest open synthetic biology markets?
Yes. Agriculture is one of the clearest places where synthetic biology can turn a biological improvement into an obvious customer outcome.
Tropic has moved unusually far beyond the normal gene-editing story. The company commercially launched new banana varieties with traits including reduced browning and longer shelf life, then raised $105 million after demand exceeded available supply. Its extended-shelf-life banana adds 12 days of green life, which can change shipping routes, waste levels and the amount of usable fruit reaching customers.
More recently, Tropic acquired Rahan Meristem, a large banana propagation business with relationships across major growing regions. Tropic can now connect genetics, propagation and distribution instead of waiting for somebody else to carry a better banana into the market.
Switch Bioworks is testing another direct economic problem. Its engineered microbes are designed to produce nitrogen around plant roots, potentially reducing dependence on conventional fertilizer. The company has now moved the product into authorized field trials in the U.S. The test will be brutally practical: can the microbes reliably save enough fertilizer or increase enough yield to make farmers buy them?
That direct connection to yield, waste and input costs is why agriculture remains attractive. The hard part is field validation and distribution, and Tropic's decision to buy propagation infrastructure shows how seriously that commercial layer has to be treated.
Is synthetic biology therapeutics still wide open?
Synthetic biology therapeutics still has huge room scientifically, but it is one of the hardest places for a new company to enter casually.
The capital available for differentiated programs remains enormous. NewLimit raised $435 million to move epigenetic reprogramming medicines toward clinical testing. The company has since reported a 100-fold manufacturing scale-up of its lead therapeutic asset while expanding its work beyond its original liver-cell programs.
Epicrispr gives us an even fresher read on what investors will fund. The company recently closed a $90 million Series C after reporting early human data for EPI-321, an epigenetic therapy designed to switch off harmful DUX4 expression in facioscapulohumeral muscular dystrophy. The program is already in a Phase 1/2 study, and the new money is intended to move it toward pivotal development.
Strand Therapeutics is taking another synthetic approach with programmable mRNA. Its first program is already in human testing, while later programs use RNA circuits and new delivery systems for systemic tumor treatment and in-vivo CAR-T.
All three companies have platform technology, but investors can see the actual medicine the platform is supposed to produce. We would still build in synthetic therapeutics around a genuinely new modality, delivery system or biological control mechanism with a strong disease application. Another broad discovery platform would face a much harder market.
If you want more recent data on this point, please see our latest synthetic biology market report.
This chart, featured in our synthetic biology market deck, compares the main business model options for synthetic biology platforms
Is biosecurity becoming a real synthetic biology market?
Yes. Biosecurity is becoming a real infrastructure market as DNA synthesis and automated biological design become easier to access.
The U.S. nucleic-acid screening framework already pushes DNA providers and benchtop synthesis manufacturers toward more comprehensive sequence screening, customer verification and record keeping. The technical expectations are also moving toward shorter screening windows and systems that can spot potentially concerning sequences spread across several separate orders.
The market opportunity is broader than one screening database. A distributed DNA printer needs to know who is operating it, what is being synthesized, whether orders should be combined for screening, whether the screening system has been tampered with and whether every sequence was checked against the current rules.
The new ARPA-H DNA-manufacturing program makes that integration explicit. The GE HealthCare and DNA Script system discussed earlier is expected to include both biosecurity and cybersecurity safeguards as part of the machine itself.
As synthesis moves toward more distributed production, compliance becomes harder to handle manually. That should create room for screening software, audit infrastructure, identity systems, secure synthesis controls and compliance tools built directly into laboratory workflows.
Does China make Western industrial synthetic biology a bad bet?
China makes commodity biomanufacturing a much worse bet for Western startups, while critical and high-value production currently looks more attractive.
China already has enormous fermentation infrastructure and production expertise. A recent U.S.-China Economic and Security Review Commission assessment estimated that the country controls roughly 70% of the global amino-acid market. Industrial biology improves through scale: plants, suppliers, engineers and operating experience accumulate around existing production.
A new American or European startup trying to make the same bulk molecule with similar fermentation economics starts from behind.
The calculation changes when the customer cares about where the product comes from. U.S. defense agencies have spent heavily on domestic biomanufacturing because dependence on overseas production can become a national-security problem. The recent GAO review found that American companies still lack enough pilot and commercial infrastructure and sometimes have to take their processes overseas simply to scale them.
Solugen shows how that can change a company's market. Its technology combines engineered enzymes with conventional catalysts to manufacture chemicals domestically. The company now markets part of its production directly around defense supply-chain resilience, including energetic precursors and specialty chemicals. It says one defense precursor was scaled 50-fold in less than six months and that it delivered 7.5 million pounds of product in 2024.
The broader U.S. policy direction is moving the same way. Federal programs are putting billions of dollars behind AI-driven science, domestic biomanufacturing, critical materials and scale-up infrastructure. Defense proposals have also explored advance purchase commitments and offtake agreements, which can give first-of-a-kind plants the customer demand needed to get financed.
We would avoid fighting China's fermentation base molecule for molecule. The better Western opportunity is where domestic production, faster product development, difficult chemistry or supply security changes the buying decision.
This chart, featured in our synthetic biology market deck, illustrates the share of revenue generated by each customer segment in the synthetic biology market
Where is there still room in synthetic biology today?
There is still a lot of room in synthetic biology today, but we would build around bottlenecks and expensive customer problems rather than around the general promise of programming biology.
Our highest-conviction opportunity is autonomous experimentation. Biological AI keeps improving, which means researchers can propose more experiments. The physical ability to run those experiments, capture clean data and feed the results back into the next decision is now becoming the scarce layer. The recent $380 million NSF commitment makes this one of the few synthetic biology opportunities where technology, customer demand and public infrastructure spending are all moving together.
Long and distributed DNA synthesis comes next. Ansa is stretching commercial DNA toward 50-kilobase constructs, IDT is distributing that capability, and DNA Script is now part of a federally funded push toward automated local DNA manufacturing.
Industrial scale-up is less fashionable but probably more important. Too many companies can engineer an organism and too few can predict what happens to it inside a large fermenter. Better scale-down models, sensing, process optimization, purification and flexible pilot infrastructure attack a problem that repeatedly kills otherwise good technologies.
On the product side, engineered enzymes, agricultural traits, scarce proteins, unusual biomaterials and critical chemicals look much better than bulk commodity replacements. Therapeutics remains attractive when the biological mechanism is genuinely differentiated, but the bar is far higher.
The weakest place to start today would be a generic synthetic biology platform with a long list of possible markets, followed closely by a commodity product that needs customers to pay more because it is sustainable.
| Opportunity | Why there is still room now | What could kill the company | Our view |
|---|---|---|---|
| Autonomous labs and closed-loop experimentation | AI is increasing experimental demand while physical testing remains slow | Hardware integration and long enterprise sales cycles | Highest-conviction opening |
| Long and distributed DNA synthesis | Complex DNA is getting longer, faster and more local, but the technology is still moving | Incumbents can absorb new synthesis methods | Very attractive |
| Bioprocess scale-up tools | Scale failure remains one of industrial biology's most repeated problems | Difficult integrations and fragmented customers | Very attractive |
| Engineered industrial enzymes | Small biological inputs can change the economics of huge material flows | Industrial validation can take years | Strong |
| Agricultural traits and biological inputs | Benefits can be measured directly in yield, waste and input costs | Field performance and distribution | Strong |
| Scarce proteins and high-value ingredients | Biology can unlock supply that conventional production cannot easily provide | Manufacturing economics and regulation | Strong |
| Critical domestic biomanufacturing | Supply security can justify local production even before pure cost parity | Dependence on government priorities | Strong in selected molecules |
| Performance biomaterials | Biology can create properties that are difficult to reproduce conventionally | Long qualification cycles | Selective |
| Programmable therapeutics | One successful medicine can support enormous value | Clinical failure and huge capital needs | Huge upside, very high bar |
| Generic biological AI software | Powerful models are becoming widely available | Rapid commoditization | Weak without proprietary experimental data |
| Bulk precision-fermented proteins | Technical feasibility is increasingly proven | Cost and scale remain unforgiving | Mostly unattractive |
| Generic bio-based commodity chemicals | Mature incumbents already produce them extremely cheaply | Fundamental unit-economics gap | Avoid unless the process advantage is exceptional |
If you want more recent data on this point, please see our latest synthetic biology market report.
OUR METHODOLOGY
This analysis asks where there is still meaningful room to build in synthetic biology today. We split the market into distinct technical and commercial layers rather than treating synthetic biology as one category, then compared each area across technical progress, customer adoption, financing, unit economics, infrastructure constraints, regulation, competition and public investment.
We weighted recent developments most heavily, while using older outcomes when they exposed structural problems that still shape the market. Ginkgo Bioworks, Zymergen and Amyris are used mainly to understand the limits of broad platform economics; newer financings and deployments are used to judge where investors and customers are still committing capital now.
Funding was treated as evidence of conviction, not as proof of a good market. Our financing review covered 52 disclosed synthetic biology rounds across five consecutive quarters, and we looked at concentration as well as total dollars because a market dominated by one very large round behaves differently from a broadly funded startup category.
For AI and autonomous experimentation, we separated model capability from experimental defensibility. Open models such as BoltzGen show how quickly the software layer can commoditize, while the OpenAI-Ginkgo experiment and the NSF's $380 million automated-lab commitment show why physical testing, proprietary data and closed-loop experimentation are becoming more valuable.
For DNA synthesis and industrial scale-up, we focused on hard operational constraints: construct length, turnaround time, decentralization, pilot capacity, reactor behavior and process economics. Ansa Biotechnologies, IDT, ARPA-H and the U.S. GAO were especially useful for understanding where synthesis and biomanufacturing infrastructure are still moving rather than already mature.
Product opportunities were judged by whether biology creates a clear economic or performance advantage for the customer. That is why we distinguish scarce proteins, engineered enzymes, agricultural traits, unusual biomaterials and critical chemicals from bulk commodity replacements that still have to beat established supply chains on cost.
We also treated regulation, biosecurity and geopolitics as market-shaping forces rather than side issues. The U.S. nucleic-acid screening framework, ARPA-H's distributed DNA-manufacturing program, GAO's work on domestic biomanufacturing capacity and the U.S.-China Economic and Security Review Commission's analysis of Chinese fermentation scale all help show where compliance or supply security can create a real buying reason.
Key sources used for this analysis include: Ginkgo Bioworks investor materials, the SEC filing on Ginkgo's Zymergen acquisition, NewLimit's $435 million financing announcement, Tropic's $105 million Series C announcement, Epicrispr's $90 million Series C announcement, the BoltzGen repository, OpenAI on the GPT-5/Ginkgo autonomous-lab experiment, the NSF automated-laboratory program, Ansa Biotechnologies on commercial long-DNA synthesis, IDT on its Ansa partnership, ARPA-H on modular DNA manufacturing, the U.S. GAO review of biomanufacturing infrastructure, the Good Food Institute's fermentation industry review, Vivici on precision-fermented lactoferrin, AMSilk's corporate and commercialization updates, Constructive Bio's Series A announcement, Samsara Eco on its commercial nylon-recycling scale-up, the White House nucleic-acid synthesis screening framework, the U.S.-China Economic and Security Review Commission's assessment of Chinese industrial capacity, and Solugen on domestic defense chemical production.
This chart, featured in our synthetic biology market deck, shows how gene therapy technology has evolved over time
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