Articles

Galixir's Chengtao Li: Finding the "Key" to Curing Disease with AI in the Universe of Compounds | Rong Talk --- In the vast "universe" of chemical compounds, finding the molecule that can precisely target a disease is like searching for a needle in a haystack — except the haystack contains more stars than there are in the Milky Way. This is where Galixir comes in. Founded in 2019, Galixir is an AI-driven drug discovery company that uses artificial intelligence to navigate the astronomical complexity of molecular space. At its helm is Chengtao Li, a Tsinghua University PhD who spent years at MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) before returning to China to build what he calls "a new kind of pharmaceutical R&D engine." "The traditional drug discovery process is incredibly inefficient," Li tells us in a wide-ranging conversation at the company's Beijing headquarters. "You're talking about 10 to 15 years and $2-3 billion to bring a single drug to market. And the failure rate is brutal. We think AI can fundamentally change that equation." Galixir's approach centers on what Li describes as "generative chemistry" — using deep learning models to design novel molecules from scratch, rather than merely screening existing compound libraries

Galixir's Chengtao Li: Finding the "Key" to Curing Disease with AI in the Universe of Compounds | Rong Talk --- In the vast "universe" of chemical compounds, finding the molecule that can precisely target a disease is like searching for a needle in a haystack — except the haystack contains more stars than there are in the Milky Way. This is where Galixir comes in. Founded in 2019, Galixir is an AI-driven drug discovery company that uses artificial intelligence to navigate the astronomical complexity of molecular space. At its helm is Chengtao Li, a Tsinghua University PhD who spent years at MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) before returning to China to build what he calls "a new kind of pharmaceutical R&D engine." "The traditional drug discovery process is incredibly inefficient," Li tells us in a wide-ranging conversation at the company's Beijing headquarters. "You're talking about 10 to 15 years and $2-3 billion to bring a single drug to market. And the failure rate is brutal. We think AI can fundamentally change that equation." Galixir's approach centers on what Li describes as "generative chemistry" — using deep learning models to design novel molecules from scratch, rather than merely screening existing compound libraries

How artificial intelligence technology is accelerating drug discovery and development.

高榕创投·