This Ph.D. project, which is in the nexus of mobility, energy, and healthcare logistics, aims to design a distribution system that minimizes energy consumption and environmental impact, optimizes costs, and efficiently meets the demand for medical supplies through the utilization of multi-modal transportation, including drones. To explore various aspects of designing an efficient, effective, sustainable, and cost-effective drone-based distribution network in this project, different decisions ranging from the strategic level (e.g., Drone hubs location) to the operational level must be made, for which different tools based on Sequential Decision-making (e.g., Markov Decision Process (MDP)), Operations Research (OR), and Artificial Intelligence (AI) will be leveraged. In addition, the research will address tactical decisions regarding the deployment of drones and trucks, cost management, and the reduction of battery and energy waste. Considering the inherent stochasticity, the research also emphasizes the importance of optimizing real-time operational decisions. These decisions involve determining the optimal use of drones, trucks, and their combinations, as well as scheduling, allocating, and routing drone missions, loading packages, and managing drone batteries at the hubs (including charging, discharging, swapping, and replacement).