Re-engineering the pharmaceutical clinical trial supply chain

• Main Author: Maithilli Anpazhahan
• Other Authors: Rajesh Piplani
• Format: Final Year Project
• Language: English
• Published: 2015
• Subjects: DRNTU::Engineering::Mechanical engineering
• Online Access: http://hdl.handle.net/10356/65287
• Institution: Nanyang Technological University

Clinical trials are forthcoming biomedical or behavioral research studies on human participants, designed to provide answers to specific questions regarding biomedical or behavioral interventions. They generally produce information on the efficacy and safety of drug products and medical devices. The process of manufacturing to being released in the market is a long and tedious one. It can take up to 15 years with a minimum of 6 years, and requires large funding of up to $1 billion. Despite this, the chances of clinical trial participants receiving successful drug formulations are slim. Out of all the drug products being explored, less that 20% are actually released into the market as new treatment methods. Since conducting clinical trials are costly yet have low chances of being successful, companies are starting to concentrate on lowering cost without compromising the efficacy and safety of drugs, as well as without lengthening the duration of trials. One way of reducing costs is to reduce supply chain expenditure. The main priority of clinical trial supply chain managements is to ensure the timely arrival of drug products to all patients without any interruption. To resolve the abovementioned challenges, many organizations have adopted a simulation model approach to observe the clinical trial supply chain and try all sorts of methods and ways to further improve it, therefore optimize it. This can be achieved by reducing lead times, maintaining supply demands, improving production efficiency as well as simulating demand forecast scenarios. For this project, a simulation model is designed to decide on the best supply chain approach to be used, by comparing the amount of drug wastage as well as the inventory holding times, which in turn can measure inventory holding costs.