Decorative gradient element.

Enabling the bioeconomy revolution with
the fastest enzymes

We crack the fundamental bottlenecks of enzyme engineering with unprecedented screening and data collection capacity
Come back early November to check out our beta testing program—limited-time offer with money-back guarantee.
Three disruptive technologies
EvolutionaryDE
UnleashedDrop
MillionFull
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7 orders of magnitude greater screening capacity
- The “numbers“ advantage (107 x)
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4 orders of magnitude greater data collection capacity
- The data advantage (104 x)
- compared with mainstream enzyme engineering platforms.

Enzyme is the core hardware of biomanufacturing

Enzyme efficiency remains a foundational bottleneck for market-competitive biosolutions

The green transition of the world economy needs efficient biosolutions.

In labs around the world, there are now numerous proof-of-concept biosolutions, going from 0 to 1, offering endless promises for a sustainable economy.

Looking at the market, there are still too few biosolutions being economically competitive against fossil fuel-based ways, the “1 to 100”.

The green transition of the world economy needs efficient biosolutions.

A bioeconomy revolution needs an enzyme engineering revolution

In essence, synthetic biopathways are linked enzymatic steps catalyzing conversions one step after another, eventually from feedstocks to products.

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
the dawn of AN enzyme engineering revolution

The ENZIDIA® Enzyme Engineering Platform

Cracking the fundamental bottlenecks of enzyme engineering

EvolutionaryDE x UnleashedDrop x MillionFull

Enzyme engineering is fundamentally constrained by two bottlenecks: screening throughput (the numbers game), and data (the information game).

1. The numbers game

The more you screen, the more likely you can find a great enzyme.
Combining EvolutionaryDE & UnleashedDrop (proprietary), the ENZIDIA platform has a library creation and screening capacity of 109 - 1011 variants per run. This is 3 orders of magnitude greater than state of the art, and 7 orders of magnitude greater than robotics-based platforms.

2. 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 105 -107 data points per run, an unprecedented throughput. This data capacity gives our use of AI a unique advantage.
The numbers game and the information game graphic image.

The ENZIDIA wheel: an "AI-second" platform

1. Build and screen a massive library (~1010 per run)
2. Collect big data (~106 per run)
3. Learn from the big data through AI
4. Construct the next massive & intelligent library, guided by AI + big data, looping to step 1.

This loop multiplies the “numbers“ advantage (107 x) and “data“ advantage (104 x), poised to revolutionise the way enzymes are engineered.

The ENZIDIA platform has been breaking enzyme bottlenecks on a roll

Two enzymes, from two distinct classes, have been engineered by beta versions of the ENZIDIA platform. Large improvements were obtained in both cases, in just one to two rounds of engineering. Iterations can be easily done for further improvements.

Great surprises await us as the full platform is deployed for more enzymes.

Dataset with approximately 100000 data points.

A dataset with ~100,000 data points
(also plotted are ~400k sequences with premature stop codons, which clustered around 0)

Case 1. 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 product formation in a given timeframe.

Case 2. A rate-limiting enzyme for the synthesis of a high-value flavor compound: 140% performance improvement in two rounds.
During Case 2: >100,000 data points of enzyme sequence-fitness relationship in a demo run of MillionFull (see graph).
The data revealed >10k unique sequences with significantly improved performance, and ~100k positive & negative mutations/epistatic interactions.
A screening capacity of >109 has been reached in an ongoing project for our third enzyme engineering target.

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

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whERE DOES enzidia STand?

A new paradigm of enzyme engineering

The ENZIDIA platform is >3 orders-of-magnitude more powerful in key metrics than any other platform
Platform category
Selling points
Limitations
AI-centric platforms
ai
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
Enzidia logo
Unprecedented screening power: 10^9 - 10^11
Unprecedented data generation: 10^5 - 10^7
Wide applicability
Low cost
New in town
AI-centric platforms
Selling point:
AI
Limitations:
Limited differentiation with open-source algorithms
No solution for (labeled) data
Metagenomic data-based platforms
Selling point:
Natural sequence data + annotation for enzyme discovery
Limitations:
No labeled data
No experimental optimisation
Automation-based platforms
Selling point:
Automation for high-throughput screening (102 - 104)
Limitations:
High cost: $30 - $50 / variant
Limited screening power & data
Microfluidics-based platforms
Selling point:
Microfluidics-based high-throughput screening (106 - 107)
Limitations:
Limited compatibility with big data extraction.
Limited applicability
Enzidia logo
Selling point:
Unprecedented screening power: 109 - 1011
Unprecedented data generation: 105 - 107
Wide applicability
Low cost
Limitations:
New in town
The faces of enzidia

The Enzidia Team

A group of relentless problem solvers and disciplinary boundary breakers
Jinbei Li profile image.
Jinbei Li, Ph.D.
CEO & CSO
Platform designer, big picture thinker, broad learner
Simon Krarup
Simon Krarup
Senior Bioengineer
"A most dedicated researcher who is too humble to ever call himself so" - anonymous
Bjarke Erichsen profile image
Bjarke Erichsen
AI Engineer
Machine learning engineer
and self-taught bioinformatician
Alex Toftgaard profile image
Prof. Alex Toftgaard Nielsen
Founding Advisor
Co-founder of Cysbio, Again, Mycropt
Professor at DTU Biosustain
Lene Lange profile image
Lene Lange, Ph.D.
Scientific Advisor
Former director of Molecular Biotechnology at Novozymes (among many things)
Steffen Klamt profile image
Steffen Klamt, Ph.D.
Scientific Advisor
Group leader at Max Planck Institute for Dynamics of Complex Technical Systems
Paul Jensen profile image
Prof. Paul Jensen
Scientific Advisor
Pioneer in integrating deep reinforcement learning and automated science (U. Michigan)
Eg Nicolajsen profile image
Eg Nicolajsen, MBA
Business Advisor
Former COO in Corporates, 2x founder, experienced mentor to 250+ startups
Morten Birkeland profile image
Morten Birkeland
IP Advisor
MSc, M.Law, EPA, D.E.S.U, CEO of IPTector, serial IP entrepreneur. Former Novo Nordisk, Novozymes, Dupont
WORK WITH enzidia

Let Enzidia accelerate your bottleneck enzyme

Accelerated enzyme engineering, for augmented synthetic biology
Icon for Fast feasibility evaluation
Fast feasibility evaluation for problem-platform fit (hours to days). Most enzymes in industrial bioprocesses and biosynthetic pathways can fit the ENZIDIA platform, and we’ll let you know if they don’t.
Icon for Small upfront fee
Small upfront fee to cover part of the project execution and establish mutual commitment.

We also offer pilot studies without significant commitments from you.
Icon for 5-12 months to complete
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, and decide on how many billions of variants to screen and how many millions of data points to learn from to find the best. Milestones will be communicated along the way.
Icon for success payment
Success-contingent payment based on the improvement achieved by ENZIDIA’s delivered results. The metric is pre-determined based on relevance for the success of the overall bioprocess.

We are also open to establishing exclusive co-development partnerships in a project-specific way.

Additionally, in partnership agreements with ENZIDIA, we place 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.

Co-development partnership: Enzidia is developing several long-term bioprocess projects internally. We will not take on service requests for these projects, but welcome de-development partners for their scale-up production. The list includes: 1) Pathways for using electrochemicals as feedstock (formate, methanol, acetate), 2) Chitosan production from chitin, 3) 3-HP, 4) Isoprene, 5) PFAS degrading enzymes, 6) Plastic (non-PET)-hydrolysing enzymes.

If you are looking to make your bioprocess the most competitive on the market, get in touch today by booking a meeting or sending a message to our founding team.

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How it works

FAQ

Plus icon to expand FAQ question
Would our enzyme bottleneck fit the ENZIDIA platform?
Most likely yes.

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.

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.
Plus icon to expand FAQ question
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.
Plus icon to expand FAQ question
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.
Plus icon to expand FAQ question
What aspects of enzyme performance would ENZIDIA have a hard time for?
1. Product/substrate selectivity, and product inhibition. These aspects will be evaluated on a case-by-case basis.
2. Enzymes for the degradation of large polymers. We are developing our platform for such cases, but we will not be eager to take on polymer degradation enzymes before this aspect of the platform is more mature.
3. Performance of enzymes in non-aqueous environments. Our screening system is an aqueous environment. The screening results don’t directly translate to different environments, though they can still serve as promising leads, just as all industrial enzymes are sourced from nature.
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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.
Plus icon to expand FAQ question
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.
Plus icon to expand FAQ question
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.
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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 self). We decide based on facts and first principles.
Initial team of Enzidia discussing in a meetingInitial team of Enzidia, having fun
funding SOURCES

Enzidia’s journey is catalyzed by

Innovation Fund logo
Biosolutions Zealand logo
Food & Bio Cluster Denmark logo
European Union logo
Denmarks Erhvervfremmebestyrelse logo
Fonden for Entrepenorskab logo
Miljo og energifonden logo