For the success of a new drug development, it is crucial to select the sensitive patient populations. To potentially reduce timeline and cost, we may apply an adaptive patient population selection design to a therapeutic trial. In such a design, based on early results of the trial, patient population(s) will be selected/determined for the final stage and analysis. Because of this adaptive nature and the multiple between-treatment comparisons for multiple populations, alpha adjustment must be performed. In this paper, we propose a closed testing procedure for assessing treatment effects for multiple populations and a weighted combination test for sample size and population adaptations. Computation/simulation is used to compare the performances of the proposed method and other multiplicity adjustment methods. A trial example is presented to illustrate the applications of the methods.