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