In response to the unmet need for effective treatments for symptomatic patients, research efforts of inhaled therapy for COVID-19 patients have been pursued since the pandemic began. However, inhalation drug delivery to the lungs is sensitive to the lung anatomy and physiology, which can be significantly altered due to the viral infection. The ensued ventilation heterogeneity will change distribution and thus dosimetry of inhaled medications, rendering previous correlations concepts? of pulmonary drug delivery in healthy lungs less reliable. In this study, we first reviewed the recent developments of inhaled therapeutics and vaccines, as well as the latest knowledge of the lung structural variations documented by CT of COVID-19 patients' lungs. We then quantified the volume ratios of the poorly aerated lungs and non-aerated lungs in eight COVID-19 patients, which ranged 2-8% and 0.5-3%, respectively. The need to consider the diseased lung physiologies in estimating pulmonary delivery was emphasized. Diseased lung geometries with varying lesion sites and complexities were reconstructed using Statistical Shape Modeling (SSM). A new segmentation method was applied that could generate patient-specific lung geometries with an increased number of branching generations. The synergy of the CT-based lung segmentation and SSM-based airway variation showed promise for developing representative COVID-infected lung morphological models and investigating inhalation therapeutics in COVID-19 patients.