This workshop in Bayesian statistics is aimed to provide industry researchers (statisticians as well as domain experts), academicians and students working in medicine and healthcare with an introduction to the topic along with some specific examples and use cases from the pharmaceutical industry. The workshop will focus on translating historical data, for example, from previously conducted randomized clinical trials into informative priors for the parameters of interest which can then be used in the design and analysis of future trials. This approach of ~Bayesian-Borrowing is gaining interest particularly for investigations in rare diseases and for medical devices. We will discuss a common problem of Prior-Data conflict in this setting and methodologies to control borrowing from historical data in the presence of a conflict. We will also be discussing a recently conducted trial COVID vaccine trial that was conducted in the Bayesian framework. The workshop will conclude with a hands-on session implementing a Bayesian design using the open-source R software. Participants are encouraged to install R and the following packages on their laptops prior to attending the workshop: ggplot2, RBesT, parallel, mcmc, mvtnorm, rstan, rstanarm.