Future protein innovation will be based on designing
proteins.

We imagine a world in which we generate the perfect protein therapeutics instead of discovering them through trial and error.

The more we understand diseases and proteins the more we can encode in therapies.

Protein design is a computational problem at the intersection of biology, chemistry and mathematics.

We use machine learning-based computational tools to design protein therapies. Our design process enables the development of proteins with the properties of an ideal medicine, in terms of functionality, side effects, and bio-distribution.
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We generate proprietary data in our laboratory to build our models that allow the quick and accurate design of therapeutic proteins and leverage massive amounts of publicly stored data.

Our design engine

Backbone design

The backbone is the main body of the protein. We use machine learning to design the backbone of the protein candidate from scratch.

Functional site

We fine-tune the side chain, which helps improve the binding interaction between the designed proteins and the target.

In-silico evaluation

Energy scores and simulations are used to evaluate the designs in-silico.

Laboratory validation

In our laboratory we characterize our proteins and generate training data to ensure excellent biophysical properties.

Proprietary machine learning tailored data

We characterize our proteins and generate training data with our own laboratory and proprietary protocols.

Our laboratory is equipped with cutting-edge sample handling and is run by our world-class science team.

Advantages of our designed small therapeutic proteins

High degree of precision over design
and functions.
High stability and solubility.
Cryptic epitope access.
Ideal for large-scale production in microbial systems or cell-free systems making it inexpensive.
Produced more quickly and in higher yields than antibodies and recombinant proteins.
No need for post-translational modifications.
Higher freedom to operate in patent landscape.

Partnering

Get in touch to discuss how you can use our platform for
protein design and discovery

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Our team

"The future of therapies starts at the intersection of biology and data science"

We are a highly driven, interdisciplinary team with the vision to cure previously untreatable diseases and make gene therapies affordable for everyone.

Christian Wirsching

Co-Founder & CEO

Ex-McKinsey

Cuong To

Co-Founder & CTO

Ex-Machine Learning Researcher FU Berlin, IBM Zurich Lab

Martin Rosellen, PhD

Structural biologist

University College London, Max Planck Institute, FU Berlin

Elliott Higgin

Protein Engineer

Institute of Pharmaceutical Science, King's College London

Harald Petry, PhD

ADVISOR

Ex-CSO Uniqure
Ex-CDO Arctos Medical

Van Trung Chu, PhD

Scientific Advisor

Immune Regulation and Cancer Lab, Max Delbrück Center for Molecular Medicine

Van Duc Dang, PhD

Scientific advisor

German Rheumatism Research Center Berlin

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