Optimization of inventory distribution in clinical trial supply chain

• Main Author: Ng, Jasper Kang Tai
• Other Authors: Wu Kan
• Format: Final Year Project
• Language: English
• Published: 2016
• Subjects: DRNTU::Engineering
• Online Access: http://hdl.handle.net/10356/68298
• Institution: Nanyang Technological University

Drug development and clinical trials are key factors in the pharmaceutical industry. An insight into the stages of drug development will be discussed in this research showing how each phase is conducted and the purpose for each phase. Thereafter, an in-depth analysis of the clinical trial supply chain will be presented covering issues such as possible problems faced and possible solutions for example risk pooling and the different replenishment methods. A study on the Interactive Voice Response Systems, IVRS, was also conducted to understand the operations of IVRS. After introducing IVRS, the research will present a possible way to improvise the IVRS for the clinical trial. Due to the numerous uncertainties and decision making required in the clinical trial, a 2 stage stochastic programming was formed to minimise the operational cost. However, to acquire an optimal solution for this optimisation problem, the computation would need to look into all the possible scenarios that could occur in the whole clinical trial. While this will give the optimal solution, it will be at the expense of long computation time. In a clinical trial, fast decision making is required and hence an improvement is required. In this research, an improvement in the form of progressive hedging was experimented where each stage scenarios are solved in parallel along with the use of penalty parameters. A simulation experiment based on a sample case was also created and conducted to solve the 2 stage stochastic model and progressive hedging designed to optimise the clinical trial. Further experiments were also subsequently carried out to explore the impact of some of the parameters such as penalty factor and termination criteria in an attempt to improve the progressive hedging’s quality and efficiency to develop solution for assisting decision making in the clinical trial. In conclusion, this report showcased the capability of progressive hedging and the various way to improve the clinical trial through IVRS, risk pooling and cutting inventory, etc.