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Leveraging our patented SoluPro™ E. coli cell lines and proprietary high throughput assay technologies ACE and HiPrBind™, we’ve created a synthetic biology platform to excel at producing complex mammalian proteins. We screen billions of distinct strains expressing drug sequence variants and/or diverse folding and expression solutions to identify drug candidates and cell lines that meet our program goals, while generating datasets that fuel our Denovium™ Engine AI pipeline. Our cutting-edge synthetic biology techniques unlock evolutionary opportunities by expanding the biological repertoire of proteins that can be produced to include new-to-nature proteins such as next-generation biologics and Bionic Proteins™ that incorporate non-standard amino acids.
Our proprietary SoluPro™ cell lines allow discovery screening within the context of the ultimate production cell line. This has the potential to reduce drug development time by consolidating processes that conventionally are performed sequentially via distinct technologies into one integrated platform that allows us to solve for drug function and manufacturability simultaneously. Our synthetic biology platform generates billions of protein sequence variants and cell line designs, and our state-of-the-art deep learning algorithms drive the process. We use proprietary artificial intelligence models to accelerate optimization for desired drug properties and manufacturing characteristics from the beginning of the discovery process. Using these machine learning models together with our synthetic biology platform, we can generate, test, and optimize orders of magnitude more potential drug candidates in a fraction of the time of traditional approaches.
Traditional mammalian expression systems are slow growing and challenging to engineer, and they are not readily adaptable to making new-to-nature proteins such as those built in novel scaffolds or incorporating non-standard amino acids (nsAAs). The flexibility of our SoluPro™ cell lines removes these technological and biological limitations and significantly widens the breadth of opportunities for discovery. Together with the in silico predictions made by our Denovium™ Engine, which are continually validated in the lab, our platform facilitates exploration of a vast sequence space of next-generation biologics – allowing evaluation and optimization of proteins that have been designed by science rather than selected from a limited repertoire of what nature has already come up with.
Incorporating non-standard amino acids is a desirable approach to accomplish controlled chemical modifications including glycosylation, PEGylation, ADC-payload conjugation, and generation of other molecular conjugates. Our Bionic SoluPro™ cell lines are specially engineered to accomplish programmable site-specific incorporation of nsAAs into proteins of interest, which we consequently call Bionic Proteins™. The nsAAs in our Bionic Proteins™ offer handles for custom chemistries and in vitro post-translational modifications; Bionic Protein™ technology provides the opportunity to create proteins with properties that extend beyond what is possible with natural sequences, and they have wide-ranging applications.
With our synthetic biology approach, and guided by our Denovium™ Engine AI predictions, we design and generate custom collections of drug candidate sequence variants, which we use to generate populations of cells for screening. In addition, we curate a diverse collection of folding and expression solutions – genetic tools such as ribosome binding site sequences, molecular chaperones, and codon-optimization conventions – that we use to customize SoluPro™ cell lines and optimize production of the desired protein. We create billions of different cell lines and with our proprietary ACE and HiPrBind™ assays we evaluate and sort the drug sequence and cell line variants we generate. Tailored for each of our programs, our high-throughput assays can rank and sort billions of cells based on desired parameters such as target affinity, protein quality, and production titer. We capture datasets from these activities that we use for training our Denovium™ Engine machine learning models.