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CapsidMap -Â Adeno-Associated Virus (AAV)
Our CapsidMap™ platform uses AI to systematically and rapidly optimize AAV capsids, overcoming the limitations of naturally occurring virus capsids by improving targeting ability, payload size, immune evasion and manufacturability. By building a massive and detailed map of synthetic AAV capsid sequence space, we can quickly navigate the landscape to find enhanced gene therapy vectors with transformative potential.
Synthesis of DNA libraries encoding modified capsids
We design millions of capsid sequences, which are then synthesized on DNA printers and assembled into capsid libraries, ready for testing.
High-throughput measurement of capsid properties
Using next-generation sequencing, we track DNA barcodes identifying individual capsid variants within our libraries. In pooled experiments with millions of capsids, we simultaneously measure numerous properties important for therapeutic success.
Machine learning models of capsid fitness landscape
We train machine learning models to predict the function of new sequences, building out a map of the AAV capsid fitness landscape. With every new experiment our map becomes bigger and more detailed.
Balancing between exploration and optimization, we efficiently search the fitness landscape for improved capsids. Our optimized capsids make current gene therapies more effective and enable the treatment of new diseases by targeting capsids to new organs and cell types.
Repeating these steps allows us to build on the lessons and successes of previous experiments, train better models, and further climb the fitness landscape for vectors with desired properties, includingin vivodelivery efficiency and specificity, immune evasion, packaging size and manufacturability.
- Tissue targeting
- Immune evasion
- Packaging size
- Manufacturing