The example dataset used here is the CYP2D6_I dataset, which contains 13,130 compounds. Figure : A stacked column chart of the ranking performances of five models on twenty-two ADMET endpoints blue) and the parallelized TPE with a median pruner (red) on dataset CYP2D6_I, across five data splits. In this experiment, the total optimization steps are set at 100, and the size of the parallel worker is set at 10. Examining the figure reveals that the approach without parallelization takes nearly five times longer to complete compared to the parallelized one. As anticipated, asynchronous parallelization enables the model to sample while an optimization loop is still in progress, leading to a significant reduction in training time.