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Our Integrated Drug Creation™ Platform connects technology and big ideas to out-evolve nature and provide a path to developing drugs that could not otherwise exist. By unifying drug discovery and cell line development into a single process, we enable creation – and production – of next-generation biologics.
Generating non-obvious predictions about what are likely to be optimal drug candidate sequences and cell line designs for any protein-of-interest, our Denovium Engine™ AI models uncover a solution space of sequences that lie beyond those that exist in nature.
Starting with disease tissue samples or bulk RNA sequencing data, we reconstruct sequences of human monoclonal antibodies (potential drugs) that are prevalent in the tissue. Using the antibodies as probes, we identify corresponding antigens (potential drug targets).
Based on a program’s goals, we design custom libraries of protein-of-interest variants in the desired scaffold architecture, specify any desired non-standard amino acid placements, and determine any applicable parameters for folding and expression solutions to evaluate.
Using synthetic biology approaches, we construct billions of genetically-distinct SoluPro® or Bionic SoluPro® cells, each containing instructions to make one version of the protein-of-interest, as well as a different assortment of folding and expression solutions.
Our flow cytometry-based Activity-specific Cell Enrichment (ACE) Assay™ allows us to evaluate and sort billions of cells to collect subsets of the population that express the best hits—versions of the protein-of-interest, based on target binding, protein quality, and expression titer
Our HiPrBind™ Assay uses automated multiplexed plate-based methods to grow micro-batches of each of the thousands of hits from the ACE Assay™, and select leads based on protein function, quality, and titer, as well as additional biophysical attributes impacting development potential.
We take the selected lead cell line(s) through a scale-up process to optimize conditions for productivity and protein quality, and perform comprehensive analytics on the lead drug candidate(s) for evaluation and technology transfer to our partners.
Our process continuously generates large and complex datasets specifying determinants of protein function and manufacturability in our system. We use this data to train our Denovium™ Engine to enable its models to make increasingly refined predictions for scaffold sequence variants and cell line designs.
Imagine designing the optimal novel drug candidate—in the desired scaffold, with appropriate attributes—and selecting the appropriate folding and expression solutions for its production cell line…before stepping into the lab?
Impossible today, reality tomorrow.
Fueled by our datasets, we expect our Denovium Engine™ models to get smarter and smarter, understanding determinants of protein function and production in our system and beyond. Every cycle of predicting, evaluating, and learning, brings us closer to de novo drug and cell line design entirely in silico.