Keywords: Bayesian, MDIC, Power prior
Recently, the Medical Device Innovation Consortium (MDIC) developed an innovative Bayesian statistical method for utilizing predictions from validated engineering models to inform clinical trials. The virtual patient model simulates the clinical outcome of interest, incorporating patient variability, as well as the uncertainty in the engineering model and in its input parameters. The number of virtual patients augmented into the clinical trial is controlled by a discount function which uses the similarity between modeled and observed data. This method is illustrated by a case study of cardiac lead fracture and reviewed by FDA via a mock pre-submission process. In this presentation, I will share my review experience in providing feedback to this innovative method from regulatory perspective. The pros and cons of this model will be discussed.