A streamlined drug development process in early phase trials is important to enable efficient delivery of new medicines to patients. Therefore, it is not uncommon for a phase II trial to start recruitment in parallel to an ongoing phase I trial. The data from the phase I trial provides information that can be potentially used to aid decision making in the phase II trial. Within early clinical development at AstraZeneca (AZ), decisions to continue further development of an investigational product are based on a decision-making framework that gives a go, consider or stop recommendation, where these regions are determined from confidence intervals around pre-specified treatment effects. We explore a Bayesian version of the AZ decision criteria incorporating the phase I trial data by utilizing the robust mixture prior. The robust mixture prior will naturally discount the phase I trial data in the final analysis of the phase II trial if there is a difference between the phase I and II data. We explore how incorporating this additional information into the phase II design and analysis may impact development decisions, under different levels of agreement between the phase I and II data.