The blueprint for better solutions
A new wave of sustainable solutions, inspired by nature, has been enabled by the confluence of advances in biological sciences and accelerating development of cheap computing power, automation and AI.
At Epoch, we have a new approach to bring these together for the development of new industrial solutions. We call this ‘Total BioDesign’. With it we’re developing novel technologies, powered by biology, to tackle our most pressing climate challenges.
Developing fit-for-purpose solutions requires a holistic approach rather than one focused on a single piece of the puzzle. From day one of development, we intersect seemingly disparate disciplines, such as synthetic biology and process design, to design for scale.
Economic modelling and process designs set functionality and performance targets for the biology. Novel biodesign tools enable us to quickly and systematically iterate through our development cycle to meet these targets.
Protein design with a systems approach
Scientists often struggle to achieve high enough enzyme performance to satisfy the needs of industrial applications. The problem faced in protein design is the enormity of sequence space and the lack of methods to efficiently navigate it. We employ a systems approach powered by a set of proprietary tools and processes to design novel protein functionality with the required performance to work at scale.
We study the relationships between enzymes and their functions to design candidates with a higher chance of possessing the desired properties than a randomised search or human-informed approach.
New Molecular Biology
We use novel and extensively multiplexed gene synthesis techniques to build libraries of tens of millions of individual enzyme variants to take forward to testing.
We input the latest biological data to predict further enzyme variants, combining favourable properties of multiple lab-verified candidates to generate starting points for future experiments.
Ultra High-Throughput Testing
We search for multiple application-relevant properties in parallel in order to maximise the efficiency of the search. These systems are designed to produce machine learning-quality biological data at scale.
Scale & Deploy
Once an enzyme has met our predetermined performance targets its production yields are improved and our team begins scaling the process.