Scanning electron micrograph of a human T lymphocyte (also called a T cell) from the immune system of a healthy donor.
Using new machine learning techniques, researchers at UC San Francisco (UCSF), in collaboration with a team at IBM Research, have developed a virtual molecular library of thousands of “command sentences” for cells, based on combinations of “words” that guided engineered immune cells to seek out and tirelessly kill cancer cells.
The work, published online Dec. 8, 2022, in Science, represents the first time such sophisticated computational approaches have been applied to a field that until now has progressed largely through ad hoc tinkering and engineering cells with existing—rather than synthesized—molecules.
The advance allows scientists to predict which elements—natural or synthesized—they should include in a cell to give it the precise behaviors required to respond effectively to complex diseases.
“This is a vital shift for the field,” said Wendell Lim, Ph.D., the Byers Distinguished Professor of Cellular and Molecular Pharmacology, who directs the UCSF Cell Design Institute and led the study. “Only by having that power of prediction can we get to a place where we can rapidly design new cellular therapies that carry out the desired activities.”Continue reading… “How AI found the words to kill cancer cells”