CAREER: Modeling and Optimization of the Pharmaceutical Research and Development and Supply Chain

克里斯托斯·马拉维利亚斯研究所：威斯康星大学提议编号：0547443标题：职业：药物研发和供应链的建模和优化本研究项目的目标是使制药公司能够更有效地管理他们的研发管道，以降低开发新药的成本。为了应对这些挑战，首席调查员(PI)将研究四个问题。首先，他将考虑研发管道的项目选择和投资组合管理问题。基于模拟的优化将被用来考虑临床试验中的不确定性。其次，他将用两个阶段的方法解决新产品开发的资源规划问题：在第一阶段，他将为不同的不确定性实现生成不同的资源配置文件；在第二阶段，我们将求解随机规划模型，以确定内部资源和外包的最优水平。第三，他将开发一种随机规划方法，用于在a)临床试验结果、b)新药上市日期和c)市场状况不确定的情况下进行产能规划。第四，他将开发有效整合制药行业生产计划和调度的方法。这项研究也有望促进不确定性优化，特别是离散问题的基于仿真的优化研究的发展。在过去10年里，化学工程专业毕业生加入生物相关和制药公司的比例显著增加。与此同时，优化方法在化学工业中变得非常流行。PI建议将研究中使用的学科和方法整合到化学工程教育的课程中。在本科阶段，他将根据拟议的研究开发教学材料(案例研究)。这些案例研究将用于PI教授的高级工艺设计课程，以提高学生对工程、伦理和职业责任以及当代问题的更广泛影响的理解。在研究生阶段，PI将为化学工程师开发一门新的研究生水平的优化方法课程。同时，PI将作为研究导师参与威斯康星大学麦迪逊分校与多样性相关的项目和倡议，以吸引来自代表性不足群体的学生。最后，通过参与国家科学基金会资助的Delta项目学习社区，该项目将对参与该项目的PI和研究助理(RA)的专业发展产生明确和持久的影响。

ABSTRACTPI: Christos Maravelias Institution: University of WisconsinProposal Number: 0547443Title: CAREER: Modeling and Optimization of the Pharmaceutical Research and Development and Supply ChainThe 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.