Inhalation therapy is a hallmark of modern respiratory medicine. Over recent years, computational fluid-particle dynamics (CFPD) simulations of respiratory airflows and aerosol deposition in the lungs have rapidly developed into an increasingly mature research field in the biomedical engineering realm, owing, among others, to tremendous advances in computational capabilities and available resources. Despite such progress, the intrinsic anatomical and physiological complexity of the lungs prevents the straightforward implementation of 'brute force' simulation strategies applied across the entire pulmonary tract. Here, we discuss how knowledge gathered from recent in silico studies can be purposefully leveraged to design efficient hybrid multiscale lung models and explore quantitatively via computational fluid-particle dynamics inhalation therapy outcomes. In contrast to the efforts geared toward patient-specific applications, we argue instead that such in silico strategies hold tremendous promise for broad inter-subject variability studies that can help foster the development of clinically efficient inhalation therapies across large human patient populations.