Sample size re-estimation is commonly used in clinical trials to mitigate the risk of under powering due to uncertainty in trial design assumptions. A large number of publications in the statistical literature have been developed for this topic; however all in the context of maintaining the original randomization ratio across treatment groups. In practice, not all clinical trials are designed based on an optimal randomization ratio due to various considerations. In such cases, when sample size is to be increased, it can be more efficient to allocate the additional subjects such that the randomization ratio is brought closer to an optimal ratio. We have proposed such an adaptive randomization ratio change strategy, where the power boost is not only through the increase of the sample size, but also via efficient allocation of the additional subjects. The control of type I error rate is shown both analytically and via simulation.