Revolutionizing Therapeutics with Biologics and Machine Learning at Big Hat

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The chapter explores the shift towards using biologics, particularly antibodies, in therapeutics development at Big Hat. It discusses the application of machine learning and AI to create safer and more effective antibody therapies, aiming to make treatments more accessible and target a wider range of diseases. Additionally, it touches on the challenges and optimizations in drug discovery processes, the technical hurdles faced in life sciences engineering, and the structure of engineering teams within the biotech organization.

Antibodies are a type of protein molecule produced by the immune system. They recognize and attach to other molecules with remarkable precision. Typically antibodies target foreign objects, like viruses, to mark them for destruction. However, they can also be engineered to treat diseases like cancer, and they are one of the fastest growing classes of drugs.

Recently, AI-driven antibody engineering has taken off, and BigHat Bio is one of the leaders of this revolution.

Eddie Abrams is the Chief Information Officer at BigHat. He joins the show to talk about protein engineering, what’s different about software development in biotech, how the engineering team is organized at BigHat, and more.

Sean’s been an academic, startup founder, and Googler. He has published works covering a wide range of topics from information visualization to quantum computing. Currently, Sean is Head of Marketing and Developer Relations at Skyflow and host of the podcast Partially Redacted, a podcast about privacy and security engineering. You can connect with Sean on Twitter @seanfalconer .