BigHat Bio
A pioneer of deep learning applied to life science problems, Peyton has developed computational, statistical, and AI/ML techniques to model, understand, and optimize biological sequences in academia and industry. Peyton was an inaugural Schmidt Science Fellow, a computational biologist at the Broad Institute, a scientific founder of Valis, and holds a PhD from Stanford University (Accel Innovation Scholar), an MPhil in Computational Biology from Cambridge University (Herchel Smith Scholar), and a BA in Applied Math from Harvard.
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BigHat Bio
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BigHat’s mission is to improve human health by making it far easier to design advanced, next-generation antibody therapeutics. Our AI-enabled experimental platform integrates a high-speed characterization or “wet” lab with machine learning technologies to speed the antibody engineering process. When applied, these design capabilities have the potential to drive the development of new generations of safer and more effective treatments for patients suffering from today’s most challenging diseases.