Multi omics reveals mesodermal fate bias and enables predictive cell state control in human pluripotent stem cell biomanufacturing
This study employs multi-omics profiling and random forest modeling to characterize how engineered bioprocess conditions influence human pluripotent stem cell states, revealing mesodermal fate biases and establishing a predictive framework for optimizing cell maintenance and differentiation in biomanufacturing.