Agent-based modeling allows us to analyze the dynamics of economic systems by simulating the interactions and behaviors of entities in the system. However, developing agent-based models is challenging due to the complexity of economic systems. This complexity emerges from the variety of factors that influence the behaviors of entities within these systems. Data-driven techniques can facilitate the development process of agent-based models by integrating patterns derived from data into the model. In this paper, we use data-driven methods to identify key patterns and characteristics of market competitors and utilize these patterns to develop an agent-based model of price competition in the Danish pharmaceutical market as a case study.