Businesses continually face risks from disruptions that can seriously challenge their performance. The pharmaceutical supply chain is even more exposed to these disruptions than other industries. This is due to the products' critical nature, structural complexity, and high sensitivity to interruptions. The present study aimed to identify and explain the components for designing a risk management model for disruptions in the pharmaceutical supply chain. It also sought to systematically explain the components and relationships that affect the occurrence and management of disruptions. In the first step, researchers created a common conceptual language between pharmaceutical supply chain literature and model description requirements. This was achieved through a conceptual equivalence process between model design and concepts related to pharmaceutical supply chain disruptions. The results of this step provided a basis for organizing the data and guiding qualitative analysis. The research is descriptive in nature and applied in purpose. It was conducted using a qualitative, inductive approach. The study's statistical population consisted of pharmaceutical industry experts. Ten of these experts were selected using purposive and snowball sampling to reach theoretical saturation. Data were collected through semi-structured interviews and were analyzed thematically. As a result, 103 primary themes, 35 sub-themes, and 10 main themes were extracted and organized into a coherent conceptual framework. According to the results, emergence, adaptation, learning, prediction, sensing, interaction, Stochasticity, Collectives, observation, and heterogeneity were identified as the design concepts of the disruption risk management model in the pharmaceutical supply chain. The research findings provide a deeper understanding of the details and dynamics of disruption in the pharmaceutical supply chain. They also offer a basis for developing analytical models and for decision-making in intelligent disruption risk management.