Many chronic inflammatory diseases (CIDs) are characterized by relapsing-remitting activity that demands long-term, adaptable therapeutic intervention. Yet, most existing therapies, including conventional immunosuppressants and biologics, often require repeated administration over months to years to maintain disease control, creating substantial treatment burden without fully matching fluctuating disease activity. In this Perspective, we discuss how programmable long-acting injectable (LAI) nanomedicines are emerging as therapeutic platforms for chronic inflammation. By integrating temporal control (sustained, sequential, and flare-responsive release), spatial control (depot retention, lymphatic trafficking, and cell-selective uptake), and biological programming (pH-, ROS-, enzyme-, and cytokine-responsive release), these platforms can align drug action with disease biology rather than simply prolong exposure. We organize these three design axes around disease-informed principles and illustrate, through an arthritis case study, how their integration distinguishes next-generation platforms from simple depot formulations. However, increasing programmability also increases translational complexity. We define key translational questions that must be addressed, including depot pharmacokinetics, disease-modified drug disposition, material-driven variability, and clinical feasibility constraints, and propose an integrated framework to address them. Disease-relevant new approach methodologies (NAMs) can serve as experimental data engines, multiscale mechanistic pharmacokinetic and pharmacodynamic modeling can translate these parameters into human exposure and response predictions, and AI/ML tools can accelerate nanoformulation optimization across multiple design parameters. In this framework, these quantitative tools provide the translational infrastructure needed to advance programmable LAI nanomedicines toward clinical implementation.