The Rise of Synthetic Biology OS (SynBio OS), an OSS Library for Programming Protein Design with AI

Biology is becoming software — and this metaphor is no longer merely a metaphor. DNA is "the source code of life," a four-letter (A, T, G, C) programming language that can be read and written. Today, the DBTL cycle — Design, Build, Test, Learn — is accelerating explosively, driven by a growing ecosystem of open-source tools and AI models. MIT's Cello automatically compiles DNA sequences from Verilog (a hardware description language), while the iGEM Parts Registry provides a platform for sharing and forking genetic parts, much like GitHub. SBOL (Synthetic Biology Open Language) serves as an interface specification for genetic circuits, and Synbiopy is an orchestration framework for biofoundries. In the domain of protein design, EvolutionaryScale's ESM3 (93 billion parameters, published in Science) generated novel fluorescent proteins representing approximately 500 million years of evolution, while David Baker's lab's RFdiffusion3 made it possible to design proteins that interact with any molecule inside a cell. Profluent Bio's OpenCRISPR-1 is the world's first AI-generated open-source gene editor, reducing off-target activity by 95%. Meanwhile, DNA Script's SYNTAX, the world's first desktop DNA printer, enzymatically synthesizes 96 oligonucleotides within 24 hours. Carnegie Mellon University has published open-source designs for a 3D bioprinter buildable for under $500, and at BioCurious (Sunnyvale), biohackers are creating DIY bioprinters by modifying $150 inkjet printers. Venture investment in synthetic biology reached $12.2 billion in 2024; a16z allocated $700 million to Bio + Health in 2026 and established a co-investment fund of up to $500 million with Eli Lilly. EvolutionaryScale secured a $142 million seed round, and Generate:Biomedicines raised $400 million in an IPO in February 2026. McKinsey estimates the annual economic impact of synthetic biology between 2030 and 2040 at $2–4 trillion. However, AI-generated proteins bear no similarity to known sequences and may therefore pass conventional DNA synthesis screening; in December 2024, 38 scientists including George Church and Kevin Esvelt issued a warning in Science about the threat of mirror life. Drew Endy (Stanford University) testified before the U.S.-China Economic and Security Review Commission that "the choices made in the coming years will determine the architecture of the global biotechnology system." This article provides a comprehensive examination of synthetic biology — from its foundational concepts and the overall picture of the "SynBio OS," to key open-source libraries and AI models, the impact of DIY bio, major companies and VC investment, biosecurity challenges, and developments in Japan.

What is Synthetic Biology — The Science of Programming Life

Synthetic Biology (SynBio) is an interdisciplinary field that applies engineering principles to biology to design and construct biological systems that do not exist in nature, or to redesign existing biological systems.

At its core is the idea of reading and writing DNA like software code, and treating living organisms as programmable entities. Drew Endy (Stanford University, Chairman of the iGEM Foundation) testified before the U.S.-China Economic and Security Review Commission in February 2025, stating:

"Biology allows near-boundless possibilities. The composition and control that software provides the digital world is realized by biology in the physical world."

Jennifer Doudna (UC Berkeley, 2020 Nobel Prize in Chemistry) declared at an April 2025 lecture, "We're in an era of programmable genome editing," and spoke on the theme of "programming life" in a McKinsey interview.

What fundamentally distinguishes synthetic biology from conventional genetic engineering is its approach to "abstraction" and "standardization." Just as software engineering evolved from assembly language to C, then Python, and on to cloud-native microservices, synthetic biology has likewise evolved from individual gene manipulation to the combination of standardized parts (BioBricks), and further to AI-driven automated design.

"Synthetic Biology OS" — The Operating System of Life

Just as software development has operating systems, synthetic biology is forming its own "OS" for running DBTL (Design-Build-Test-Learn) cycles. This synthetic biology OS is not a single software product, but an ecosystem of interconnected standardized interfaces, open-source tools, shared libraries, AI models, and hardware automation infrastructure.

Mapped against software engineering analogues, the correspondence looks like this:

Programming language = DNA sequence (A, T, G, C). A living organism's genome is "source code" written in an alphabet of just four characters. The human genome contains roughly 3.2 billion base pairs — equivalent to a gigabyte-scale codebase.

API specification = SBOL (Synthetic Biology Open Language). SBOL is a community-driven open standard for representing and exchanging synthetic biology designs in a standardized format. It describes genetic parts — promoters, ribosome binding sites (RBS), coding sequences (CDS), and terminators — using a unified data model and visual symbols. Just as REST APIs standardize communication between microservices, SBOL standardizes the interfaces between components of a genetic circuit.

Package registry = iGEM Parts Registry. parts.igem.org is an "npm registry" or "PyPI" where thousands of genetic parts (BioBricks) are registered. These DNA parts, conforming to restriction enzyme assembly standards, can be used to construct large-scale genetic circuits. Each year, iGEM teams from around the world (over 5,000 participants at the 2025 Paris Jamboree) add new BioBricks, which the following year's teams reuse and improve — the biological equivalent of GitHub's fork-and-pull-request model.

Compiler = Cello 2.0. Developed by Christopher Voigt's lab at MIT, Cello is a compiler that automatically designs DNA sequences for genetic circuits from logic specifications written in Verilog (a hardware description language). Using a library of Boolean logic gates — AND, OR, NOT, and others — it implements genetic circuits in the E. coli genome that control output (fluorescent protein expression) based on input signals (chemical concentrations). The source code is publicly available on GitHub (CIDARLAB/cello).

Framework = SynBiopython. SynBiopython is a Python open-source library for building automated workflows in biofoundries. Where Biopython handles classical bioinformatics (sequence analysis, alignment), SynBiopython automates DBTL pipelines specific to synthetic biology — DNA design and assembly, robotic automation protocol generation, codon optimization, and more.

Cloud IDE = Benchling. Benchling is a cloud-based electronic lab notebook and molecular biology software platform used by over 200,000 scientists, more than 7,000 institutions, and over 600 companies. As of mid-2024, its annual recurring revenue (ARR) was approximately $210 million (~¥31.5 billion), with a valuation of $2.4 billion (~¥360 billion). It provides sequence design, plasmid mapping, CRISPR experiment management, and inventory management in one place.

MLOps = TeselaGen. TeselaGen is an enterprise-grade, ML-powered bioinformatics platform. AI agents assist with library design, sequence optimization, and accelerating DBTL cycles, automating the operation of large-scale biofoundries.

Open science community = OpenBioML. OpenBioML is a decentralized community advancing open-source research at the intersection of machine learning and biology. All project outputs are released under CC-BY, MIT, or Apache licenses, with backing from Stability AI.

AI Protein Design Tools — The Open-Source Shockwave

The fastest-evolving component within the synthetic biology OS is the suite of AI-driven protein design tools. The award of the 2024 Nobel Prize in Chemistry to Demis Hassabis, John Jumper (AlphaFold), and David Baker (computational protein design) symbolizes where this field has arrived.

Structure Prediction Models

AlphaFold 3 (Google DeepMind, May 2024) is a model that integrates 3D structure prediction across proteins, nucleic acids, and small molecules. Its accuracy in predicting protein–ligand interactions has improved by more than 50% over conventional methods. Commercial use, however, is restricted.

In contrast, OpenFold3 (Columbia University, Novo Nordisk, AWS, OpenFold Consortium) is a fully open-source alternative under the Apache 2.0 license. A preview was released in October 2025, trained on over 300,000 experimental structures and 13 million synthetic structures. It achieves performance on par with AlphaFold 3 for monomeric RNA structures.

Boltz-2 (MIT CSAIL + Recursion Pharmaceuticals, June 2025, MIT License) is the first model to perform structure prediction and binding affinity prediction simultaneously. It is the first AI approach to match the accuracy of free energy perturbation (FEP) methods, while being 1,000× faster and reducing cost dramatically—from $100 to just a few cents. Predictions are possible in 20 seconds on a single GPU.

Chai-1 (Chai Discovery, Apache 2.0) is an integrated prediction model covering proteins, small molecules, DNA, RNA, and glycan modifications, freely available for both academic and commercial use.

Protein Design (De Novo Design)

RFdiffusion3 (David Baker Lab, University of Washington Institute for Protein Design, December 2025) represents the state of the art in diffusion model-based protein design. It can generate proteins de novo—from scratch—that interact with every class of molecule found inside cells: proteins, DNA, RNA, and small molecules. It is 10× faster than its predecessor RFdiffusion2 and enables the design of DNA-binding proteins, enzymes, and biosensors. Training code and weights are openly available on GitHub (Rosetta Commons Foundry).

ProteinMPNN (also from the Baker Lab) is a neural network specialized for inverse folding—designing amino acid sequences that realize a desired 3D structure. The community is also driving extensions to handle cyclic peptides and larger proteins.

ESM3 (EvolutionaryScale, published in *Science*, January 2025) is a biological foundation model with 98 billion parameters, trained on 2.78 billion protein sequences and 771 billion tokens. It reasons jointly over sequence, structure, and function, and generated a novel fluorescent protein called esmGFP. Its sequence similarity to the closest known natural fluorescent protein is only 58%—meaning it artificially generated diversity equivalent to approximately 500 million years of natural evolution. A smaller 1.4B-parameter open version, ESM3-open, is available on GitHub. The successor, ESM Cambrian, offers 300M and 600M open-weight models, with the 6B model accessible via the Forge API (academic) and AWS SageMaker (commercial).

AI Gene Editors

OpenCRISPR-1 (Profluent Bio, April 2024, Apache 2.0-equivalent) is the world's first AI-generated open-source gene editor. It combines a Cas9-like protein and guide RNA generated by a large language model (LLM), demonstrating on-target activity comparable to natural SpCas9 (55.7% vs. 48.3%) while reducing off-target activity by 95%. Tens of thousands of researchers have accessed it, and commercial use is free. In April 2025, Profluent Bio announced in a *Fortune* interview that "scaling laws exist for protein design models as well," and in November 2025 the company raised $106 million (approximately ¥15.9 billion) in a Series B co-led by Jeff Bezos (Bezos Expeditions).

Lab Automation and DNA Synthesis — "Wet Lab DevOps"

The "runtime environment" equivalent of the synthetic biology OS is the foundation of lab automation and DNA synthesis.

Opentrons (New York, unicorn company) provides open-source software liquid handling robots (OT-2 / Flex). Used in thousands of labs across more than 40 countries, it has raised over $200 million in total funding. In February 2024, it announced a plug-and-play protocol library and generative AI tools, enabling researchers to build robot protocols without writing Python code. AssemblyTron, developed by MIT, is software that automates DNA assembly on the OT-2.

Twist Bioscience (South San Francisco, NASDAQ: TWST) leads the industry with its silicon chip-based DNA synthesis technology. FY2025 revenue was $376.6 million (approx. ¥56.5 billion, 20% year-over-year growth), with gross margins exceeding 50% in the most recent quarter.

The SYNTAX system from DNA Script (Paris/South San Francisco) is the world's first commercial desktop DNA printer. Its enzymatic DNA synthesis technology (EDS: Enzymatic DNA Synthesis) enables parallel synthesis of up to 96 oligonucleotides (up to 120 nt) within 24 hours without the use of hazardous organic solvents. Traditional DNA synthesis required ordering from external vendors, taking days to weeks — SYNTAX transforms that into an on-demand, on-site process.

The DIY Bio Shock — "Forking" Functional DNA Sequences and Printing Them on a Home Bioprinter

The most fundamental transformation in the world of synthetic biology is advancing quietly, yet with certainty. It is the rise of DIY Biology (Do-It-Yourself Biology) — the ability to fork functional DNA sequences like software and physically output them on personal desktop equipment.

The iGEM Parts Registry as a "GitHub Fork"

The iGEM Parts Registry is the world's largest open-source genetic parts library in synthetic biology. Thousands of BioBrick parts — promoters, ribosome binding sites, coding sequences, and terminators — are registered and freely accessible to anyone.

Its operational model is strikingly similar to that of GitHub. Each iGEM team (with more than 5,000 students participating annually) "forks" existing genetic parts to incorporate into their projects, then "commits" new parts or improved versions back to the registry. Other teams reuse and build upon them further. This fork-and-contribute cycle has steadily enriched the synthetic biology parts library year after year.

SBOL standardizes the data format for parts, Cello automatically compiles DNA sequences from logical specifications, and SynBiopython generates assembly protocols. This toolchain allows researchers to fork the "source code" of genetic circuits, customize it to their needs, and "build" it as physical DNA.

The Arrival of the Desktop DNA Printer

What decisively democratizes this "fork and build" pipeline is the desktop DNA printer.

DNA Script's SYNTAX is a commercial product as mentioned, but the DIY biology community is pursuing even lower-cost approaches.

BioCurious (Sunnyvale, California) is a biohacker space in Silicon Valley. There, a project is underway to modify an inkjet printer costing around $150 into a DIY bioprinter. A CD/DVD drive motor moves the print platform, controlled by an Arduino microcontroller. Instead of ink cartridges, cells and bioink are loaded to print three-dimensional biological structures.

Carnegie Mellon University has released the design for an open-source 3D bioprinter that can be built for under $500. Considering that commercial bioprinters cost from $10,000 to over $200,000, this is less than one-hundredth of the cost. A 2025 Nature paper also published an affordable DIY modification guide for a coaxial 3D bioprinting system.

OpenPCR is an open-source PCR (polymerase chain reaction) device, and BentoLab is a portable DNA analysis lab. Combining these open-source hardware tools with the aforementioned open-source software (Cello, SynBiopython, iGEM Parts Registry) and open-source robotics like the Opentrons OT-2 makes biofabrication by individuals and community labs technically feasible.

What DIY Biology Means

Let us consider this situation by drawing an analogy to the history of the software industry.

In the 1970s, computers were the exclusive domain of large corporations and universities. The Apple I in 1976, followed by the IBM PC, triggered the personal computing revolution. The Linux and open-source movement of the 1990s democratized software development. GitHub in the 2000s explosively accelerated collaboration among developers worldwide.

Where does synthetic biology stand on this trajectory today? The iGEM Parts Registry corresponds to GitHub's predecessor (the SourceForge era), and desktop DNA printers correspond to the Apple II. The "iPhone" has yet to appear, but the technological foundation is being rapidly established.

Drew Endy stated before the U.S. Congress:

"The choices we make, or fail to make over the next few years, will determine the architecture of a global biotechnology system."

On one path, just as the democratization of computing gave rise to GAFA, the democratization of biology will create a new giant industry. On another path, malicious use could bring catastrophic consequences. This duality is the essence of DIY biology's impact.

Key Corporate Profiles — From Platform Companies to AI Biotech Firms

Platform Companies

Ginkgo Bioworks (NYSE: DNA) is the leading platform company that calls itself the AWS of synthetic biology. FY2025 revenue was $170 million, down 25% from $227 million the previous year. Its valuation of $15 billion at the time of its 2021 SPAC listing has fallen to a market cap of $421 million as of March 2026. The company reduced its annual cash burn by 55% year-over-year and decided to divest its biosecurity business. CEO Jason Kelly declared, "We are concentrating our investment on winning the Autonomous Labs category." In 2022, the company acquired Zymergen (a synthetic biology company backed by SoftBank Vision Fund that IPO'd at a $6 billion valuation in 2021 before collapsing) for $300 million, integrating its software, automation, and biological assets.

Kelly spoke with longevity researcher and entrepreneur Bryan Johnson at the 2025 SynBioBeta conference about "the convergence of synthetic biology, data-driven optimization, and radical self-experimentation," articulating a vision for the fusion of biotech and tech. Kelly also served as former chair of the National Security Commission on Emerging Biotechnology and has been deeply involved in biosecurity policymaking.

Twist Bioscience (NASDAQ: TWST) is a leading DNA synthesis company that achieved FY2025 revenue of $376.6 million (20% year-over-year growth) with a gross margin exceeding 50%. Its proprietary technology for parallel DNA synthesis on silicon chips delivers orders-of-magnitude higher throughput compared to conventional 96-well plate methods.

AI Bio Companies — The "OpenAIs of Biology"

EvolutionaryScale (New York/San Francisco) raised $142 million in a seed round in June 2024. Nat Friedman (former GitHub CEO), Daniel Gross, and Lux Capital co-led, with participation from Amazon and NVentures (NVIDIA). The founding team has experience building protein language models within Meta. ESM3 was published in Science in January 2025, and ESM Cambrian is available as a next-generation model via the Forge API. Often called the OpenAI of biology, the company has established the concept of foundation models for proteins.

Profluent Bio (Berkeley) gained global attention with OpenCRISPR-1. In 2023, it was the first to demonstrate in Nature Biotechnology that "LLMs can generate functional proteins," and in April 2025 published "scaling laws for protein design models" in Fortune. The company raised $106 million in a Series B co-led by Jeff Bezos (Bezos Expeditions) and Altimeter Capital, bringing total funding to $150 million.

Generate:Biomedicines (Somerville, Massachusetts) was founded in 2020 by Flagship Pioneering, the firm behind Moderna. The company takes a generative AI approach to designing protein therapeutics from scratch and is known for "Chroma," a diffusion model published in Nature. It raised $273 million in a Series C (with participation from Amgen and NVIDIA NVentures) and IPO'd on Nasdaq in February 2026, raising $400 million. The company has entered into a multi-target partnership with Novartis.

Absci (Vancouver, Washington, NASDAQ: ABSI) has an "Integrated Drug Creation" platform that validates AI-designed antibodies in wet lab experiments in as little as six weeks. The company has formed partnerships with AstraZeneca worth up to $247 million and with Almirall worth up to $650 million (milestones plus royalties). In January 2025, AMD made a $20 million strategic investment to collaborate on accelerating AI inference.

Mammoth Biosciences (San Francisco) is a CRISPR company co-founded by Jennifer Doudna that has achieved unicorn status (valuation exceeding $1 billion). The company is developing a Cas12a-based diagnostic platform and therapeutics using ultracompact CRISPR systems.

VC Investment Landscape — Bio Is the Next Big Wave After Tech

Overall Market Trends

Synthetic biology venture investment in 2024 reached $12.2 billion, up from $10.7 billion in 2023 (SynBioBeta 2025 Investment Report). Across biotech broadly, $28.1 billion in VC funding was raised in the US and Europe in 2024, a 33% increase year-over-year. The IPO market also recovered, with 16 biotech IPOs raising $3 billion in the first three quarters of 2024.

PitchBook's 2025 report analyzed that "Wall Street's victories are signaling the beginning of the synthetic biology revolution."

Key VC Trends and Investment Theses

a16z (Andreessen Horowitz) Bio + Health has formed four funds since its founding in 2014, establishing a $1.5 billion fund in 2022. In its January 2026 $15 billion raise, $700 million was allocated to Bio + Health. The firm also established a co-investment fund of up to $500 million with Eli Lilly, investing in companies at all stages. Target areas include novel drug development, new modality platforms, and emerging health technologies. a16z's investment thesis is clear — converting Eroom's Law (the law of rising healthcare costs) into Moore's Law (the law of exponential improvement). Founding partner Vijay Pande (departing June 2025) stated: "AI will have its greatest impact in life sciences and health when it becomes capable of succeeding at specialized tasks like diagnostics and medical procedures. This transformation will unfold over 10 to 20 years."

Flagship Pioneering, known for creating Moderna, takes a distinctive approach of "creating companies" rather than "investing in them." In addition to Generate:Biomedicines, the firm has successively founded synthetic biology-related companies including Sana Biotechnology (cell therapy) and Indigo Agriculture (agricultural microbiome).

Lux Capital co-led EvolutionaryScale's $142 million seed round. Specializing in deep tech investments, the firm was also an early investor in Ginkgo Bioworks and supported Synonym (bioreactor scale-up) in its $30 million Series A.

DCVC (Data Collective Venture Capital) established the DCVC SynBioBeta Fund (focused on pre-seed and seed) in partnership with SynBioBeta's John Cumbers. The firm invested in three fermentation companies in 2025 alone, accelerating its investment in data-driven synthetic biology.

Khosla Ventures (AUM $16 billion, five vintage funds) has invested in Opentrons (open-source lab robotics) and is expanding its synthetic biology-related investments across healthcare, AI, and cleantech.

Fifty Years, a climate-focused VC, supported Living Carbon (enhanced trees) in its $15 million Series A, concentrating on applications of synthetic biology to climate change.

The Entry of Tech Giants

Tech giants are rushing into synthetic biology: Amazon (invested in EvolutionaryScale through AWS), NVIDIA (invested in EvolutionaryScale, Generate:Biomedicines, and Recursion through NVentures), AMD ($20 million into Absci), and Jeff Bezos personally (invested in Profluent Bio). Marc Andreessen once said "software is eating the world," but now biotech is poised to eat the world using software's methods.

Biosecurity — The Boundary Between Light and Shadow

Limitations of AI-Generated Proteins and DNA Synthesis Screening

The greatest risk posed by the open-sourcing and AI-ification of synthetic biology is biosecurity.

Current DNA synthesis screening relies on homology-based algorithms——comparing the DNA sequences of synthesis orders against databases of known threat sequences. The problem is that AI-generated proteins have "little or no similarity to known sequences." The esmGFP generated by ESM3 was only 58% similar to natural proteins. OpenCRISPR-1 is functionally equivalent to SpCas9, yet differs significantly in sequence. In other words, biologically active molecules designed by AI may slip through conventional screening.

At the 2025 BIRRI meeting, NTI (Nuclear Threat Initiative) discussed three priority areas: DNA synthesis screening, protection of AIxBio capabilities, and mirror life risks. IBBIS (International Biosecurity and Biosafety Initiative for Science, established 2024) and SecureDNA (a system that automatically screens all DNA synthesis orders while protecting privacy through cryptographic technology) operate a blind-test portal and propose a hybrid screening strategy——combining functional prediction algorithms with traditional homology-based approaches.

Kevin Esvelt (MIT Media Lab) has championed the concept of "information hazards," warning of the risk that publicly available information could be used for harm. Esvelt is also a co-developer of SecureDNA and has advocated for "stricter biosecurity and research transparency" in PLOS Pathogens.

The Mirror Life Threat

In December 2024, 38 scientists——including George Church (Harvard University), Kevin Esvelt, and two Nobel laureates——published a warning paper in Science. It warned that mirror bacteria——artificial life forms with chirality (molecular handedness) mirroring that of natural organisms——could evade immune defenses and invade natural ecosystems.

The immune system detects pathogens by recognizing specific molecular shapes (chirality), but this recognition fails with mirror molecules. The paper noted the possibility of "lethal infections that could spread through a significant proportion of plant and animal species, including humans." At present, no researchers are pursuing the creation of mirror life——indeed, researchers who had previously done so co-signed the paper and declared they were stopping——but as synthetic biology capabilities improve, the technical barriers will continue to fall.

OECD Recommendations

The OECD (Organisation for Economic Co-operation and Development) published two important reports in 2025: "Synthetic Biology in Focus" (February 2025, 69 pages) and "Synthetic Biology, AI and Automation: A Forward-Looking Technology Assessment" (December 2025). Convening 66 experts from 32 countries, it put forward five governance elements:

1. Embedding values: Incorporating ethical and social values from the earliest stages of technology development

2. Strengthening foresight and technology assessment: Building mechanisms to proactively assess the risks of emerging technologies

3. Multi-stakeholder engagement: Collaboration among scientists, industry, civil society, and policymakers

4. Agile and adaptive regulation: Flexible regulatory frameworks capable of keeping pace with the speed of technological progress

5. International cooperation: Biosecurity is a cross-border issue, making international coordination indispensable

Market Size and Future Outlook

Market Size Forecast

The global synthetic biology market size, based on aggregated estimates from multiple research firms, is as follows.

The market was valued at approximately $19.9 billion in 2024 (roughly ¥2.985 trillion, per Straits Research). It is projected to expand to $65.1–66.3 billion (approximately ¥9.765–9.945 trillion) by 2030, and to reach $130.7–234.8 billion (approximately ¥19.605–35.22 trillion) by 2035.

For AI × synthetic biology specifically, the market is expected to grow from approximately $94.7 million in 2024 to $438.4 million by 2034 (CAGR: 16.56%).

McKinsey's "Bio Revolution" report (2020) estimated the direct annual economic impact of synthetic biology at $2–4 trillion (approximately ¥300–600 trillion) over the 2030–2040 period. Approximately 400 use cases are deemed scientifically feasible, and up to 60% of the physical inputs to the global economy could, in principle, be produced biologically.

Timeline — Key Events to Watch

Late 2026–2027: Profluent Bio is expected to announce next-generation protein design models based on scaling laws. The emergence of a successor to ESM3 at the trillion-parameter scale is also anticipated.

2027–2028: Successors to RFdiffusion3 are expected to accelerate the entry of AI-designed protein therapeutics into clinical trials. Post-IPO pipeline progress at Generate:Biomedicines will serve as a key litmus test.

2028–2030: Desktop DNA printer prices are expected to drop to the low thousands of dollars, driving the mainstreaming of synthetic biology education at university and high school levels. International frameworks for DNA synthesis screening will either advance—or fall behind.

Post-2030: The "$2–4 trillion" economic impact projected by McKinsey begins to materialize. Cloud-based biofoundry services ("BioAWS") become a realistic prospect.

Positive Outlook

As a16z's Vijay Pande has noted, an era in which "AI understands biology beyond human capability" is dawning. Just as Boltz-2 achieved FEP-level accuracy with AI and reduced costs from $100 to mere cents, the dramatic decline in computational costs is driving the democratization of research. The growing number of open-source models—such as OpenFold3, Chai-1, and OpenCRISPR-1—means that academic researchers and startups can drive innovation without depending on large-scale platforms like AlphaFold 3 or Ginkgo Bioworks.

PitchBook analysts predict that "synthetic biology will undergo a 'Cambrian explosion' in the late 2020s," and SynBioBeta founder John Cumbers has stated: "The number of synthetic biology companies has exceeded 900, with 12,000 investment deals completed. This field is no longer niche."

Negative Outlook and Risks

The collapse of Ginkgo Bioworks' stock price (from $15 billion to $400 million) starkly illustrates the difficulty of commercializing synthetic biology companies. A deep gap remains between technological possibility and commercial viability. The failure of Zymergen—which could not commercialize its products after its IPO and was acquired by Ginkgo for $300 million—offers the same lesson.

From a biosecurity perspective, as Kevin Esvelt has warned, the risk that AI-designed biological molecules could evade existing screening systems is real. As DIY bio democratization advances, the barrier to malicious use also lowers. Drew Endy has stated that "the choices made in the coming years will determine the architecture of the global biotechnology system," but there is no guarantee those choices will be made wisely.

The "mirror life" paper by George Church and colleagues demonstrated that synthetic biology could, in theory, pose existential risks. The weight of 38 prominent scientists signing that warning cannot be dismissed lightly.

On the regulatory front, while the OECD report recommends "agile and adaptive regulation," national regulatory frameworks have not kept pace with technological progress. EU GMO regulations remain strict; in the United States, FDA and EPA jurisdictions overlap; and China is rapidly constructing its own regulatory framework.

Japan Trends — Synthetic Biology Selected as One of 17 Growth Strategy Sectors

National Strategy-Level Developments

In December 2025, the Japan Growth Strategy Headquarters under the Takaichi administration established 17 strategic fields, among which synthetic biology and biotech was included. This represents an elevation to national strategic status alongside AI and semiconductors, quantum, aerospace, fusion energy, and others.

The Ministry of Economy, Trade and Industry (METI) held the inaugural meeting of the "Synthetic Biology & Bio Working Group (WG)" on February 3, 2026, with plans to develop a public-private investment roadmap over four sessions (targeting completion in April–May 2026). The Bioeconomy Strategy revised in June 2024 sets the goal of "realizing the world's most advanced bioeconomy society by 2030."

NEDO invested a large budget of approximately 1 trillion yen in the biotech sector in FY2022 as part of its "Bio-Manufacturing Revolution Promotion Project." In the FY2025 biofoundry initiative, efforts are advancing to cultivate microbial and cell design platform operators and develop the biofoundry infrastructure.

Notable Startups

Fermentа (spun out of Ishikawa Prefectural University, founded October 2022) is a startup that uses synthetic biology to produce rare natural compounds (plant secondary metabolites) via E. coli fermentation. It raised 2 billion yen in a Series A round in August 2025, bringing total fundraising to 4.8 billion yen. A pilot plant is scheduled for completion in May 2026, where bioreactors at the 3,000-liter scale will be operated.

Synprogen (spun out of Kobe University) holds patents on the "OGAB method" DNA synthesis technology and works on drug discovery and development for gene therapy. It has raised approximately 540 million yen.

Biofoundry Hubs

The Kansai hub centered on Kobe University is building one of Japan's largest biofoundries as a DBTL-cycle smart cell development platform. In collaboration with Osaka University, Kyoto University, Chitose Research Institute, and others, it is developing 30-liter-scale production process development and AI-controlled sample production platforms. University spinouts including Biopalette, Synprogen, and Bacchus Bio Innovations have emerged from this ecosystem.

However, compared to U.S. counterparts such as EvolutionaryScale ($142 million seed round) and Generate:Biomedicines ($400 million via IPO), there remains a significant gap in the fundraising scale of Japan's synthetic biology startups. The key question is whether the roadmap being developed by METI's WG can put forward concrete investment strategies to close this gap.

Impact on the Industry

The maturation of the synthetic biology OS holds the potential to fundamentally transform not only biotech and pharma, but also the chemical, agricultural, energy, and materials industries. McKinsey's estimated annual economic impact of $2–4 trillion far exceeds the current cloud computing market (approximately $600 billion).

In the pharmaceutical industry, the acceleration of drug discovery through AI × synthetic biology has already begun. Profluent Bio's discovery of "scaling laws for protein design models" suggests that, just as LLMs evolved from chatbots toward general intelligence, protein design AI will also dramatically improve its capabilities as it scales.

In agriculture, advances are being made in improving nitrogen fixation through synthetic biology, designing disease-resistant crops, and developing biofertilizers. Flagship Pioneering's Indigo Agriculture improves crop productivity through microbiome technology, while Living Carbon accelerates carbon sequestration using genetically modified trees.

In the materials industry, the shift toward bio-based high-performance materials replacing petrochemical products is accelerating. However, as Zymergen's failure demonstrated, the "scale-up wall"—the challenge of translating lab-scale success to commercial scale—remains significant.

In the context of DIY bio, the impact on education is particularly significant. More than 5,000 students participate in iGEM annually, and the high school division is also expanding. Synthetic biology has the potential to become the next-generation literacy, much like programming education.

From an investment perspective, as symbolized by the establishment of a joint fund between a16z and Eli Lilly, the boundary between tech VCs and pharmaceutical companies is dissolving. Biotech is no longer exclusively the domain of specialized VCs; it has become a field in which general tech VCs are actively entering.

On the other hand, if biosecurity governance fails to keep pace with technological progress, there is a risk of increased regulation and public backlash against the industry as a whole. The "choices of the coming years" that Drew Endy speaks of will determine what this industry looks like a decade from now.

References: Drew Endy, U.S.-China Economic and Security Review Commission Testimony (2025/2), Drew Endy, House Science Committee Written Statement (2025/6), Jennifer Doudna, Berkeley Talks "The Exciting Future of Genome Editing" (2025/8), McKinsey "Programming Life: An Interview with Jennifer Doudna", Eric Topol Ground Truths "Jennifer Doudna: The Exciting Future of CRISPR", SBOL Standard (sbolstandard.org), iGEM Parts Registry (parts.igem.org), Cello 2.0 (Nielsen et al., Nature Protocols, 2021; GitHub: CIDARLAB/cello), SynBiopython (Synthetic Biology journal, Oxford Academic, 2021), OpenBioML (openbioml.org), Benchling Revenue & Valuation (Sacra, 2024), TeselaGen Platform (teselagen.com), AlphaFold 3 (Abramson et al., Nature, 2024/5), OpenFold3 Preview Release (BusinessWire, 2025/10), OpenFold Consortium Open-Source Protein Structure AI (Nature News, 2025), Boltz-2 Release (MIT CSAIL + Recursion, 2025/6), Chai-1 (GitHub: chaidiscovery/chai-lab, Apache 2.0), RFdiffusion3 (Institute for Protein Design, UW, 2025/12; GEN News), ProteinMPNN (Dauparas et al., Science, 2022), ESM3 (Hayes et al., Science, 2025/1; EvolutionaryScale Blog), ESM Cambrian (EvolutionaryScale, 2025), EvolutionaryScale $142M Seed Round (TechCrunch, 2024/6), Profluent OpenCRISPR-1 (BusinessWire, 2024/4), Profluent $106M Series B (BusinessWire, 2025/11), Profluent Scaling Laws for Protein Design Models (Fortune, 2025/4), Opentrons Generative AI Protocol Tools (2024/2), AssemblyTron (MIT/Opentrons), DNA Script SYNTAX System (dnascript.com), Twist Bioscience Q3 FY25 Earnings ($96.1M, 50%+ gross margin), Ginkgo Bioworks FY2025 Results (PRNewswire, 2025; $170M revenue), Ginkgo Bioworks Autonomous Labs Strategy, Jason Kelly SynBioBeta 2025 Keynote, Generate:Biomedicines IPO $400M (MedCity News, 2026/2), Generate:Biomedicines Series C $273M (Amgen, NVentures), Absci + AMD $20M Investment (2025/1), Absci-AstraZeneca Partnership ($247M), Absci-Almirall Partnership ($650M), Mammoth Biosciences (mammoth.bio), SynBioBeta 2025 Investment Report (900+ companies, 12,000+ investments, $12.2B in 2024), PitchBook "Wall Street Wins Signal Synthetic Biology Revolution", a16z Bio + Health Fund ($1.5B, 2022; $700M allocation in 2026), a16z + Eli Lilly Biotech Ecosystem Venture Fund (up to $500M), Vijay Pande, a16z "AI at the Intersection: The a16z Investment Thesis on AI in Bio + Health", Flagship Pioneering Portfolio (flagshippioneering.com), Lux Capital (EvolutionaryScale lead investor), DCVC SynBioBeta Fund, Khosla Ventures Portfolio (khoslaventures.com; AUM $16B), Fifty Years / Living Carbon Series A ($15M), Jeff Bezos / Bezos Expeditions (Profluent Bio investment), George Church et al. "Confronting Risks at the Dawn of Mirror Life" (Science, 2024/12), Kevin Esvelt, MIT Media Lab, Information Hazard Concept, SecureDNA Manuscript (securedna.org), NTI Biosecurity / IBBIS (International Biosecurity and Biosafety Initiative for Science, 2024), NTI "Developing Guardrails for AI Biodesign Tools", NTI BIRRI Meeting 2025 (DNA Synthesis Screening, AIxBio, Mirror Life), OECD "Synthetic Biology in Focus" (2025/2, 69pp, 32 countries, 66 experts), OECD "Synthetic Biology, AI and Automation: A Forward-Looking Technology Assessment" (2025/12), McKinsey "The Bio Revolution: Innovations Transforming Economies, Societies, and Our Lives" (2020; $2T-$4T annual impact by 2030-40), Synthetic Biology Market Size (Straits Research: $19.91B in 2024; Grand View Research; Nova One Advisor; Coherent Market Insights: $65.1B by 2030), AI in Synthetic Biology Market ($94.73M in 2024 → $438.37M by 2034, CAGR 16.56%), BioCurious DIY BioPrinting (3D Printing Industry), Carnegie Mellon Open Source 3D Bioprinter (3DPrint.com; sub-$500), Nature 2025 DIY Coaxial 3D Bioprinting System, OpenPCR Open Source PCR, BentoLab Portable DNA Lab, Japan Growth Strategy Headquarters 17 Strategic Fields (Synthetic Biology/Bio selected, 2025/12, NewsPicks), Ministry of Economy, Trade and Industry "Synthetic Biology/Bio WG" inaugural meeting (2026/2/3; roadmap targeted for completion April–May 2026), Bioeconomy Strategy revision (Cabinet Office, 2024/6), NEDO Biomanufacturing Revolution Promotion Project (FY2022–; scale of 1 trillion yen), Fermenta Series A ¥2 billion (PRTimes, 2025/8; cumulative ¥4.8 billion), Synplogen OGAB method (synplogen.com), Kobe University Biofoundry DBTL Platform, iGEM 2025 Highlights (Labiotech; 5,000+ participants, Paris), SynBioBeta "Meet the 8 Tech Titans Investing in Synthetic Biology", Synthetic Biology Investors 2026 (Ellty Blog)