Anjali Kurian
Independent Researcher
Kerala, India
Abstract
The clinical trial supply chain (CTSC) plays a pivotal role in ensuring the success of pharmaceutical research by delivering investigational medicinal products (IMPs) efficiently to trial sites. Delays, inefficiencies, or lack of visibility can compromise trial timelines, patient safety, and data integrity. This manuscript presents the design and application of a performance dashboard tailored to monitor key metrics across the clinical trial supply chain. The dashboard is conceptualized as a visual and analytical interface that captures real-time data on demand forecasting, inventory turnover, shipment lead times, site utilization, and waste rates. Through a comprehensive review of operational pain points, this study identifies critical KPIs and integrates them into a user-centric visualization platform. The dashboard facilitates proactive decision-making, enhances compliance, and optimizes resource planning. Drawing upon Lean and Six Sigma frameworks, the study highlights how digital tools, including BI platforms and data warehousing strategies, can be harnessed to transform static CTSC reports into actionable intelligence. The paper concludes that performance dashboards are instrumental in elevating transparency, traceability, and operational excellence in clinical trial logistics.
Keywords
Clinical Trial Supply Chain, Performance Dashboard, Key Performance Indicators, Trial Monitoring, Inventory Management, Data Visualization, Investigational Medicinal Product, Lean Six Sigma, Real-Time Analytics, Operational Metrics
References
- Eckerson, W. W. (2006). Performance dashboards: Measuring, monitoring, and managing your business. Wiley.
- George, M. L. (2003). Lean Six Sigma for Service: How to Use Lean Speed and Six Sigma Quality to Improve Services and Transactions. McGraw-Hill.
- Haughom, J., Kriz, R., & McMillan, C. (2009). Transforming Healthcare: Performance Improvement Through Information Management. HIMSS Publishing.
- Klopotek, D., & Van den Berg, M. (2009). Improving forecasting in clinical trials by integrating demand management. Applied Clinical Trials, 18(10), 36–42.
- Macher, J. T., & Nickerson, J. A. (2005). Theory-driven empirical research in the economics of innovation: Assessing the usefulness of the resource-based view. Research Policy, 34(8), 1233–1249. https://doi.org/10.1016/j.respol.2005.01.003
- Snee, R. D., & Hoerl, R. W. (2005). Six Sigma Beyond the Factory Floor: Deployment Strategies for Financial Services, Health Care, and the Rest of the Real Economy. Pearson Education.
- Tavares, A. P., & Oliveira, J. F. (2011). Clinical trials supply chain planning: Challenges and opportunities. Computers & Industrial Engineering, 60(4), 639–648. https://doi.org/10.1016/j.cie.2011.01.014
- Pocock, S. J. (2013). Clinical Trials: A Practical Approach. John Wiley & Sons.
- Getz, K. A. (2007). Improving protocol design feasibility to drive drug development economics and performance. International Journal of Environmental Research and Public Health, 4(2), 112–120. https://doi.org/10.3390/ijerph2007040012
- Arrowsmith, J. (2011). Trial watch: Phase II failures: 2008–2010. Nature Reviews Drug Discovery, 10(5), 328–329. https://doi.org/10.1038/nrd3439