  Practical employment of Bayesian trial designs has been rare. Even if
accepted in principle, the regulators have commonly required that such designs
be calibrated according to an upper bound for the frequentist Type 1 error
rate. This represents an internally inconsistent hybrid methodology, where
important advantages from applying the Bayesian principles are lost. In
particular, all pre-planned interim looks have an inflating multiplicity effect
on Type 1 error rate. To present an alternative approach, we consider the
prototype case of a 2-arm superiority trial with binary outcomes. The design is
adaptive, using error tolerance criteria based on sequentially updated
posterior probabilities, to conclude efficacy of the experimental treatment or
futility of the trial. In the proposed approach, the regulators are assumed to
have the main responsibility in defining criteria for the error control against
false conclusions of efficacy, whereas the trial investigators will have a
natural role in determining the criteria for concluding futility and thereby
stopping the trial. It is suggested that the control of Type 1 error rate be
replaced by the control of a criterion called regulators' False Discovery
Probability (rFDP), the term corresponding directly to the probability
interpretation of this criterion. Importantly, the sequential error control
during the data analysis based on posterior probabilities will satisfy the rFDP
criterion automatically, so that no separate computations are needed for such a
purpose. The method contains the option of applying a decision rule for
terminating the trial early if the predicted costs from continuing would exceed
the corresponding gains. The proposed approach can lower the ultimately
unnecessary barriers from the practical application of Bayesian trial designs.
