Bayesian trial design offers increased flexibility but there remains concern about the validity of results within the regulatory setting. FDA Guidance (2010) indicates that evaluation of frequentist operating characteristics is essential in the regulatory setting. One potential advantage of Bayesian designs is the use of informative priors. Issues differ when applying informative priors to the control group only vs both groups in terms of type 1 error inflation and the ease of justifying the prior. Setting “tuning parameters” such as the threshold posterior probability that must be exceeded to support the claim so that type 1 error <=0.05 in conjunction with using an informative prior eliminates the desirable sample size reduction benefit associated with the use of an informative prior. This suggests that the concept of ‘excessive type 1 error’ needs refinement in order for it to be applicable to such designs: What criteria should be used to assess if a Bayesian informative prior design has excessive type 1 error? What approaches may be used to justify the amount of ‘borrowing’ especially in sparse settings such as when historical data consists of a single recent regulatory trial?