The goal of this research project is to enable pharmaceutical companies to manage more effectively their R&D pipelines to reduce the cost of developing new drugs. To address these challenges the principal investigator (PI) will study four problems. First, he will consider the problem of project selection and portfolio management for the R&D pipeline. Simulation-based optimization will be used to account for the uncertainty in clinical trials. Second, he will address the problem of resource planning for new product development using a two-stage approach: in the first stage, he will generate different resource profiles for different realizations of uncertainty; in the second stage, we will solve a stochastic programming model to determine the optimal levels of in-house resources and outsourcing. Third, he will develop a stochastic programming approach for capacity planning under uncertainty in a) the outcome of clinical trials, b) the launch date of a new drug and c) the market conditions. Fourth, he will develop methods for effective integration of production planning and scheduling in the pharmaceutical industry. This research is also expected to advance the state-of-the-art in optimization under uncertainty, and especially in simulation-based optimization for discrete problems.
The percentage of graduates in chemical engineering that join bio-related and pharmaceutical companies has increased significantly the last 10 years. At the same time, optimization methods are becoming very popular in the chemical industry. The PI proposes integrating both the subject and the methods used in the proposed research into the curriculum of chemical engineering education. At the undergraduate level, he will develop instructional material (case studies) based on the proposed research. These case studies will be used in the senior process design course that the PI teaches to improve students understanding about the broader impacts of engineering, ethical and professional responsibility, and contemporary issues. At the graduate level, the PI will develop a new graduate level course on optimization methods for chemical engineers. At the same time, the PI will be involved as research mentor in diversity related programs and initiatives of UW - Madison to attract students from underrepresented groups. Finally, through involvement in the Delta program learning community, an NSF-funded center, this project will have a clear and lasting impact on the professional development of the PI and the research assistant (RA) involved in this project.
