Pancreatic ductal adenocarcinoma (PDAC) is among the deadliest types of cancer and has a 5-year survival of less than 8% owing to its complex biology. As PDAC is refractory to immunotherapy, we need to understand the functional dynamics of T cells in the PDAC microenvironment to develop alternative therapeutic strategies. In this study, we performed RNA velocity-based pseudotime analysis on a scRNA-seq dataset from surgically resected human PDAC specimens to gain insight into temporal gene expression patterns that best characterize the cell fates. The tumor microenvironment was seen to encompass a range of terminal states for the T cell trajectories with suppressive and non-tumor-responsive T cells dominating them. However, the results also reveal the existence of a functional branch of the T cell population that was not transitioning to exhausted and senescent states. These findings reveal various microenvironmental signals driving T cell patterns which can be useful in identifying new therapeutic avenues. Keywords: Bioinformatics; Cancer systems biology; Immune response.