White Paper

Bringing new drugs to the market is increasingly expensive with the highest costs incurred by sponsors during the clinical period. Factors affecting the rising costs of clinical trials include slower and more expensive patient recruitment, the trend toward targeted therapies in cancer research, and limited availability and higher costs of biologic and comparator drugs.

Among solutions, aimed at increasing the efficiency and reducing the time of research and development, are the globalization of clinical trials, adaptive design, and lean manufacturing. While those solutions can help sponsors reduce their estimated R&D costs, they also introduce a new level of complexity to the clinical trial supply chain. Considering that manufacturing and logistics make up a large portion of the cost of developing a new drug, clinical trial supply chain management is in need of innovation.

One of the main supply chain challenges in today’s clinical trials is to reduce product overage and waste while keeping the risk of stock-outs to a minimum. According to industry experts, it is “critical for companies to achieve a balance between the risks and costs to optimize the clinical supply chain” (Lamberti et al., 2016). Currently, this is done with the help of Randomization and Trial Supply Management systems (RTSM) and forecasting. However, the limited forecasting capabilities of RTSM systems as well as the complexity and high costs of proprietary and in-house simulation software force many sponsors to still rely on manual forecasting methods.

Our focus is on leveraging the sponsors’ experience by providing them with technology that adapts to their needs and accelerates their workflow. We recognize the changing role of clinical trial supply chain management and built our product with the following principle in mind: “A successful simulator can persist for the lifetime of its subject, changing to meet new requirements, to accommodate new data and methods of solution, and to reflect modifications to the system itself” (Nutaro, 2010). Above all we want Trifor to be a powerful, easy-to-use, and cost-effective alternative to existing solutions.

At its core, Trifor is an agent-based, discrete-event simulation designed with adaptability and extensibility in mind. It simulates every depot, site, shipment, patient, and product and each event is scheduled and executed at a distinct point in time. Our goal is to develop Trifor into a a fully configurable, interoperable, and programmable simulation platform with a simple and intuitive user interface and a robust representational state transfer application programming interface.

Lamberti, M.J., Hsia, R., Mahon, C., Milligan, C., Getz, K.A., 2016. Assessing Global Clinical Supply Logistics. Applied Clinical Trials, <http://www.appliedclinicaltrialsonline.com/assessing-global-clinical-supply-logistics>.

Nutaro, J.J., 2010. Building Software for Simulation: Theory and Algorithms, with Applications in C++. Hoboken, NJ: Wiley.