Michael Polansky is training an AI model on skin that’s still alive
Michael Polansky — better known publicly as Lady Gaga's partner and a former top deputy to Sean Parker — has quietly spent years building an AI-driven startup that keeps living human skin tissue alive for weeks outside the body to discover new skincare compounds, and is only now going public about it.
Michael Polansky, the founder of the AI and biology startup Outer Biosciences, is leading an extraordinary project: training an AI model on human skin that remains alive outside the body. Polansky, who is married to Lady Gaga, has been quietly working on this groundbreaking technology for over a year, keeping it under wraps from the public.
Raised in Minnesota, Polansky studied applied mathematics and computer science at Harvard before moving to Silicon Valley. He started his career at Bridgewater Associates, a hedge fund, before transitioning to the tech world through Sean Parker's assistant, who introduced him to Parker himself. Polansky joined Founders Fund, a venture capital firm led by Parker, Luke Nosek, Ken Howery, and Peter Thiel, where he helped manage Parker's business interests.
In 2022, Polansky founded Outer Biosciences, motivated by the desire to bridge the gap between the pace of innovation in biology and chemistry and that of software. The company sources human skin discarded after plastic surgery surgeries and works with vetted non-profit and commercial biobanks, such as the National Disease Research Interchange and the Cooperative Human Tissue Network, all under strict oversight and consent.
Polansky's team focuses on developing a reliable method to keep human skin alive outside the body for extended periods, ultimately aiming to create a bridge between in vivo and in vitro research. He has enlisted the help of Kyung-Jin Jang, the chief scientist at Outer Biosciences and a member of Haus Labs' scientific advisory board, revealing a deep collaboration between the two companies.
Written by urgent.news from TechCrunch's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.