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

摘要：Christos Maravelias机构：威斯康星大学提案编号：0547443题目：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其&研发管道，以降低开发新药的成本。 为了应对这些挑战，主要研究者（PI）将研究四个问题。首先，他将考虑项目选择和项目组合管理的问题，为研发管道。基于模拟的优化将用于解释临床试验中的不确定性。其次，他将使用两个阶段的方法来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，我们将解决一个随机规划模型，以确定内部资源和外包的最佳水平。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）市场条件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。 该研究也有望推动不确定性优化领域的发展，特别是离散问题的基于仿真的优化。在过去的10年里，加入生物相关和制药公司的化学工程毕业生的比例显着增加。与此同时，优化方法在化学工业中变得非常流行。PI建议将拟议研究中使用的主题和方法融入化学工程教育课程。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，道德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个新的研究生阶段优化方法课程。与此同时，PI将作为研究导师参与UW -麦迪逊的多样性相关项目和倡议，以吸引来自代表性不足群体的学生。最后，通过参与三角洲计划学习社区，一个NSF资助的中心，这个项目将有一个明确的和持久的影响PI和研究助理（RA）参与这个项目的专业发展。

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.