Their computer model identified key features associated with a specific response to the drug (i.e. PD-L1 inhibitor) and applied 36 different features-multi-modal data set into their machine learning algorithm and allowed the algorithm to identify patterns that could predict increases in potential tumor-fighting immune cells in a patient’s blood after treatment. The gene discussed is CD274; the disease is neoplasm.