In phase I clinical trials, our goal is to effectively treat the patient while minimizing the chance of exposing them to excessively toxic doses of a new drug. In order to choose the correct dose, we use an adaptive dose-finding design, the Bayesian optimal interval design (BOIN), to aid in this selection. Here, we propose evaluation of the Bayesian optimal interval design under the Weibull and uniform distribution, comparing it to a time-based algorithm of the BOIN (TITE-BOIN). Simulations show that under theWeibull distribution, standard BOIN surpasses the TITE-BOIN design in terms of recommendation of maximum tolerated dose and allocation of data. In addition, both designs under theWeibull perform better than the uniform distribution when selecting a dose. Further study of the effects of the Weibull parameters on the BOIN design and the duration of trial under the Weibull should be considered.