LAUSR

Despite enormous success in biomedical science and technology, as well as increased research and development spending, pharmaceutical productivity has faced challenges. The success rates in drug development remain low and have shown a declining trend in the last two decades. The US FDA has also recognized the inefficiency in drug development and proposed model-based drug development (MBDD) to improve pharmaceutical productivity and decision making. Modeling and simulation provide a powerful tool to summarize and integrate information from different studies. Application of modeling and simulation can help decision making, design better studies, reduce costs, save time, and ultimately improve success rates. Beyond traditional types of modeling techniques or applications, MBDD is a paradigm that covers the entire spectrum of the drug development process. This review aims to provide an overview of modeling and simulation and their application to various drug development processes, from early discovery to preclinical and clinical stages, as well as formulation optimization. Several types of models will be discussed, and illustrative examples of their applications in the drug development process will be highlighted.