The recent COVID-19 pandemic has highlighted the key role of the pharmaceutical industry and its supply chain operations in society. Like in many other sectors, this pandemic has unveiled important vulnerabilities and weaknesses across the pharmaceutical distribution network, calling the attention for the importance of resiliency, flexibility, and sustainability strategies.

One of the key challenges regarding resiliency is the ability to understand and anticipate the supply chain behaviour under uncertainty and dynamically manage capacity. In order to address this challenge, this paper proposes a simulation-based approach with a twofold goal: i) to understand the pharmaceutical supply chain network dynamics, in order to fast-track vulnerabilities and anticipate risks propagation across the network; and ii) to support decision-making for enhancing resiliency and flexibility, through capacity management strategic decisions.

The main contributions of this work are grounded on the integration and exploitation of different simulation paradigms, in order to understand the cause-effect relationships in complex systems, under several disruption scenarios. In this way, the disruption risks and their propagation are identified throughout the supply chain network, providing insights for the proactive and timely development of contingency and risk mitigation plans.