The present study extended the "p"-optimality method to the multistage computerized adaptive test (MST) context in developing optimal item pools to support different MST panel designs under different test configurations. Using the Rasch model, simulated optimal item pools were generated with and without practical constraints of exposure control. A total number of 72 simulated optimal item pools were generated and evaluated by an overall sample and conditional sample using various statistical measures. Results showed that the optimal item pools built with the "p"-optimality method provide sufficient measurement accuracy under all simulated MST panel designs. Exposure control affected the item pool size, but not the item distributions and item pool characteristics. This study demonstrated that the "p"-optimality method can adapt to MST item pool design, facilitate the MST assembly process, and improve its scoring accuracy.