Abstract
This study investigates the development of a probabilistic design space (DS) for a tableting process, focusing on the uncertainty in critical model parameters. A an empirical model is used to assess the impact of critical process parameters (CPPs), including lubrication extent and porosity, on tablet tensile strength (CQA). By incorporating Monte Carlo and Bayesian techniques, the uncertainty of five model parameters is propagated, allowing the estimation of feasibility probabilities for achieving CQAs with a reliability greater than 0.95. The resulting probabilistic DS provides manufacturers with a tool to assess the likelihood of meeting CQAs under varying production conditions. The findings indicate that specific combinations of lubrication rate and porosity define a robust DS within the acceptable operating region, ensuring consistent tableting performance even in the presence of uncertainties. This approach emphasizes the importance of probabilistic DS in optimizing manufacturing processes and delivering built-in quality assurance.