Unleashing the biomanufacturing revolution with an enzyme acceleration revolution

The most powerful technology platform, for the biggest bottleneck, in an industry with the greatest potential for the world's sustainability transition.

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Three disruptive technologies

EvolutionaryDE

UnleashedDrop

MillionFull

7 orders of magnitude greater evolution speed (screening capacity)

- The “numbers“ advantage (~10¹⁰ variants per round!)

4 orders of magnitude greater data collection capacity

- The data advantage (~10⁶ labeled enzyme data per round!)

- compared with mainstream high-throughput enzyme engineering platforms.

Trusted partners of:

Enzyme is the core hardware of biomanufacturing

Enzyme efficiency remains a foundational bottleneck for market-competitive biomanufacturing processes

The green transition of the world economy needs efficient biosolutions.

In labs around the world, there are now numerous proof-of-concept bioconversion pathways, going from 0 to 1, offering endless promises for a sustainable economy: food/feed ingredients, plastic monomers, and long-duration energy storage molecules.

Looking at the market, there are still too few biomanufacturing processes being economically competitive against fossil fuel-based ways, the “1 to 100”, compared with its vast potential.
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The green transition of the world economy needs efficient biosolutions.

A biomanufacturing revolution needs an enzyme engineering revolution.

Enzymes are the reason biomanufacturing can happen. In essense, biomanufacturing pathways are enzymatic conversion pathways linking the feedstock to the end products.
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It’s impossible to have a fast bioprocess when the enzymes are slow. It’s hard to have a slow bioprocess when the enzymes are fast.

A bioeconomy revolution needs an enzyme engineering revolution

‍Enzymes are the world’s most powerful manufacturing machines.

‍Imagine Earth without enzymes. It will be of barren lands and sterile sea, rocks and deserts. Enzymes made the entire organic living world possible. Even fossil fuels, the predominant feedstock of today’s economy, came eventually from enzymes’ work. They are not the predominant human manufacturing approach yet only because we hadn’t had the best way to tame them.

We are on our way to move past that age.

the dawn of AN enzyme engineering revolution

The ENZIDIA^® Evolutionary SuperWheel

Cracking the fundamental bottlenecks of enzyme optimization

Enzyme optimization is fundamentally constrained by two bottlenecks: evolution speed (namely screening throughput, - "the numbers game"), and intelligence (limited by data, - "the information game").

1. Evolution speed - the numbers game

The more you screen, the more likely you can find a great enzyme.

Combining EvolutionaryDE & UnleashedDrop (patent-pending), the ENZIDIA platform has a library creation and screening capacity of ~10¹⁰ variants per run. This is 10 million times greater than robotics-based platforms.

2. Intelligence - the information game

To have a great river of information flowing toward better sequences, we need more than just a river channel (AI). We need lots of water (data).

Our technology MillionFull (patent-pending) allows the collection of ~10⁶ data points per run, an unprecedented throughput. This data capacity provides the ultimate power for our use of AI.

The ENZIDIA Evolutionary Wheel - an "AI-second" reinforcement learning loop:

1. Build and screen a massive library
~10¹⁰ variants screened per run, - 10 million x greater than mainstream platforms.
2. Collect big data
~10⁶ labeled enzyme sequence-performance data per run, - 10 thousand x greater than mainstream platforms (cost held equal).
3. Learn from the big data through AI.
4. Design the next massive & intelligent library, informed by real big data.
Loop to step 1.

With evolution speeds 10 million times faster and AI-directed data collection 1000x greater than mainstream platforms (and even more than nature), we can accelerate nature’s most powerful manufacturing machines like never before. The scale of revolution this can unleash is hard to predict, but it won’t be small.

The ENZIDIA platform has been breaking enzyme bottlenecks on a roll

Dataset with approximately 100000 data points.

A dataset with >100,000 data points

Case 1. >100,000 data points of enzyme sequence-fitness relationship in a demo run of MillionFull (see graph), while achieving 369% performance improvement for a methyltransferase of a phenolic compound.
The data revealed >10k unique sequences with significantly improved performance, and ~100k positive & negative mutations/epistatic interactions.

Read the paper here.

Case 2. A rate-limiting enzyme in the bioproduction of a food/feed supplement: 94% performance improvement after one round of engineering.
(The benchmark sequence is commonly used in patents and papers. Enzyme performance is defined as level of product produced in a given timeframe, incorporating multiple contributing factors.)

Read the paper here.

Should our next project be the super-charged engineering of the bottleneck enzyme in your bioprocess?

Employ the ENZIDIA platform Find answers for FAQ

whERE DOES enzidia STand?

A new paradigm of enzyme engineering

The ENZIDIA platform is >3 orders-of-magnitude more powerful than state-of-the-art

Platform category

Selling points

Limitations

AI-centric platforms

Limited differentiation with open-source algorithms

No solution for (labeled) data

Metagenomic data-based platforms

Natural sequence data + annotation for enzyme discovery

No labeled data

No experimental optimisation

Automation-based platforms

Automation for high-throughput screening (10^{^2} - 10^{^4})

High cost: $20 - $50 / variant

Limited screening power & data

Microfluidics-based platforms

Microfluidics-based high-throughput screening (10^{^6} - 10^{^7})

Limited compatibility with big data extraction.

Limited applicability

Unprecedented screening power: 10^{^9} - 10^{^11}

Unprecedented data generation: 10^{^5} - 10^{^7}

Wide applicability

Low cost

New in town

Selling point:

Unprecedented screening power: 10⁹ - 10¹¹

Unprecedented data generation: 10⁵ - 10⁷

Wide applicability

Limitations:

New in town

Comapre the ENZIDIA platform with:
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‍Microfluidics-based platforms

Selling point:

Microfluidics-based high-throughput screening (10⁶ - 10⁷)

Limitations:

Limited generalizability

High noise

Limited resolution for data collection

Automation-based platforms

Selling point:

Automation for high-throughput screening (10² - 10⁴)

Limitations:

High cost

Limited screening throughput & data generation

AI-centric platforms

Selling point:

Limitations:

Limited differentiation with open-source algorithms

No solution for the need of big (labeled) data

Metagenomic data-based platforms

Selling point:

Natural sequence data + annotation for enzyme discovery

Limitations:

No data labeling

No experimental optimisation

The faces of enzidia

The Enzidia Team

A group of relentless problem solvers and disciplinary boundary breakers

Jinbei Li, Ph.D.

Founder, CEO & CSO

ENZIDIA platform designer and company growth orchestrator. Multi-discipline integrator. Guided by a mission to realize humanity's sustainability transition.

Prof. Alex Toftgaard Nielsen

Founding Advisor

Co-founder of Cysbio, Again, Mycropt; Application-drive professor @ DTU Biosustain. Former scientist at Genencor.

Simon Krarup

Founding Bioengineer

Highly dedicated scientist and engineer since Enzidia's beginning.

Wenqi Zhao

Founder's associate

People-oriented mind with a biotech background, driven by a deep passion to help others.

Rebecca Lennen, Ph.D.

Bio-design Counsel

Previously Director of Strain Engineering at Lygos, Scientist III at Zymergen, Senior Researcher at DTU Biosustain. Effective R&D leader with deep and broad knowledge.

Bruce Wittmann, Ph.D.

MLDE Advisor

Pioneer in machine learning-assisted directed evolution. Founder of the machine learning subgroup at the Arnold Lab at Caltech. Broad background in synbio x AI.

Adam Meyer, Ph.D.

HT Screening Counsel

Former Senior Director of Pooled Campaigns at Ginkgo Bioworks. The world's top expert in high-throughput screening systems.

Morten Birkeland

IP Advisor

CEO of IPTector. Former IP manager/director at Dupont, Novozymes, Novo Nordisk. Serial IP entrepreneur. MSc, M.Law, EPA, D.E.S.U. Leading Enzidia's IP strategy.

Rasmus Krogh-Meyer

Partnership Advisor

Director of Business Development at NNF Initiative for Vaccines and Immunity (NIVI). Previously global Head of License & Partnering at Novozymes. Guiding BD strategy and structuring IP-based partnerships.

Lene Lange, Ph.D.

Scientific Advisor

Founder of LL Bioeconomy. Previously Director of Molecular Biotechnology at Novozymes, Director of Research at Aalborg U., Head of Department of Biology at UCPH. Great repertoire for enzyme discovery.

Prof. Paul Jensen

Scientific Advisor

Pioneer in integrating deep reinforcement learning and automated science (U. Michigan).

Steffen Klamt, Ph.D.

Scientific Advisor

Pioneer in modeling biological networks. Group leader at Max Planck Institute for Dynamics of Complex Technical Systems.

WORK WITH enzidia

Partner with Enzidia for the most efficient enzymes and cell factories

Accelerated enzyme engineering, for augmented synthetic biology

Model 1 — Bioprocess co-development partnership

Long-term exclusive partnership for continuous optimization of enzymes and strains for a given chemical, ensuring industry-leading position in bioprocess efficiency and cost competitiveness.

Model 2 — Enzyme & cell factory optimisation service partnership

Fast feasibility evaluation for problem-platform fit (hours to days). Most enzymes in industrial bioprocesses and biosynthetic pathways can fit the ENZIDIA platform.

Small upfront fee to cover part of the project execution and establish mutual commitment.

5-12 months for most projects to complete. No more fee is asked regardless of if we do more work. ENZIDIA will aim for the best possible result that can be delivered.

Success-contingent payment based on the improvement achieved by ENZIDIA’s results. The metric is pre-determined based on relevance for the success of the overall bioprocess.

In addition: no restriction on the partner to disclose the success or failure of partnership projects. This is not a common practice. While we may not remain successful in 100% of the cases we work on (so far we are), we believe that having such transparency is essential to establish ENZIDIA as the best and most trusted choice in the industry.

Model 3 — Massive enzyme and protein data collection services

If you are developing great AI tools for protein optimization, you still need the data, especially labeled data, to train the AI models. Using our proprietary technology MillionFull (https://www.biorxiv.org/content/10.1101/2025.10.24.684421v1), we can collect millions of sequence-fitness datapoints for your target enzyme and protein. Properties we can collect data for include enzyme catalytic efficiency, protein expressibility and foldability in bacterial hosts.

Our uniqueness doesn't come from business models. No need to fit into the models above. - We fit them to your needs.
If you are looking to make your bioprocess the most competitive on the market, get in touch today.

Partner with Enzidia Answers to FAQ

FOR THE INTRIGUED

FAQ

Would our enzyme bottleneck fit the ENZIDIA platform?

Most likely yes.
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Most enzymes used in industrial biotech can fit the ENZIDIA platform. The current version of the platform is especially suited for enzymes involved in cell factories.
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We will let you know whether a problem can fit our platform, and if so, the difficulty level on a scale of 1-10. Just book a call or write a message with the buttons right below this section.

What conditions is the ENZIDIA platform most suited for?

Aqueous conditions, with close to physiological pH. We can suit a wide temperature range from 30 C to 80 C.

What aspects of enzyme performance is the ENZIDIA platform best suited for?

1. Higher Kcat

2. Lower Km

3. Higher stability / thermotolerance

The former two (Kcat and Km) are known to be among the hardest aspects in enzyme engineering, given the complexity of these parameters which makes rational design immensely challenging, compared with selectivity, pH, and stability. - That's where the ENZIDIA platform shines given its unique data output and screening throughput advantage.

What aspects of enzyme performance would ENZIDIA have a hard time for?

1. Product selectivity. This aspect will be evaluated on a case-by-case basis (less of an issue if the starting point enzyme is already highly selective).

2. Performance of enzymes in non-aqueous environments. Our screening system is an aqueous environment.

What info do we need to send to you?

Essential: the reaction that needs to be catalysed.

Great to have: essential info about the enzyme's necessary operation environment (pH, temperature, solvent).

Good to have if available: the current version of the enzyme; if substrate/product inhibition is present.

Would a ceiling, or local optimum, be hit in an enzyme engineering campaign? Can this be alleviated?

Optimization ceiling can more likely be hit when deriving variants from one template (specifically, negative epistasis between an existing residue and new mutations).

When more diversity is included in the library, such as building libraries through diverse natural homologs, especially aided with the massive data that we can collect using MillionFull, a great diversity can be included in the library so that there are many paths to avoid a local optimum.

Here is one theoretical reference (Fig.3) on this topic.

You can screen so many. Is it necessary?

We can never screen too many, based on empirical evidence and theoretical analysis.

a) Most beneficial mutations can not be predicted rationally or computationally.

In our massive data collection demo project, the amazing finding is that, while the most damaging mutations happened around the active site, as one would expect, the most beneficial mutations were spread across the entire sequence.

In extensive literature where the enzyme engineering efforts weren't limited to the neighborhood of the active site, this observation was consistent (one exception is when the focus is the catalytic selectivity rather than catalytic rate).

b) With extensive enzyme engineering, the trend is clear: greater screening efforts lead to the identification of sequences with greater improvements, and these improved sequences have more mutations (>20).

See Fig. 2 in this paper to get a meta view.

c) Even considering just a small number of random mutations, the size of the possibility space already exceeds any existing screening capacity. Yes, including Enzidia's, not to mention other platforms:

(for a 400-AA enzyme)

1 mutation: ~8*10^{^3} possibilities

2 mutations: >3*10^{^7}‍

3 mutations: >8*10^{^10}‍

4 mutations: 1.6*10^{^14}

...

d) Most importantly, the fundamental problem: the system of an enzyme has all the features of a "complex system".

Present in complex systems are different components interacting with each other in a nonlinear way. Small perturbations (e.g., one mutation of an enzyme) can lead to unpredictable changes in the whole system. This is why enzyme behaviours are so unpredictable, even when we are getting better with static structure predictions. This is also why there are so many amazing wonders, or "emergent behaviours", from the complex systems of enzymes. We can only approach them effectively through evolution.

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what we are guided by

Enzidia’s Core Principles: Truth, Mission, Learning

Truth is the ground we operate on, for everything, including how we set our mission and design our path. Truth, not preconceptions or ego.

Mission is what guides us. Enzidia was created and built as a tool, for the mission of the global sustainability transition.

Learning is the path. Path for how we find truth, and how we achieve our mission. We learn from everyone. We follow no one (including our past selves). We decide based on facts and first principles.

funding SOURCES

Unleashing the biomanufacturing revolution with an enzyme acceleration revolution

Enzyme is the core hardware of biomanufacturing

The green transition of the world economy needs efficient biosolutions.

A biomanufacturing revolution needs an enzyme engineering revolution.

The ENZIDIA® Evolutionary SuperWheel

1. Evolution speed - the numbers game

2. Intelligence - the information game

The ENZIDIA platform has been breaking enzyme bottlenecks on a roll

Should our next project be the super-charged engineering of the bottleneck enzyme in your bioprocess?

A new paradigm of enzyme engineering

The Enzidia Team

Partner with Enzidia for the most efficient enzymes and cell factories

FAQ

We are here for you

Enzidia’s Core Principles: Truth, Mission, Learning

Our journey is catalyzed by:

The ENZIDIA^® Evolutionary SuperWheel