Lung-On-Chip Modeling of Nanodrug Dynamics
Inhaled therapies hold enormous potential, but replicating human breathing in the lab remains a major challenge. For lung-on-chip research, airflow and mucociliary clearance are critical. Traditional aerosol systems can deliver particles, yet they rarely mimic realistic breathing patterns or the dynamic mucus environment of the respiratory tract.
A recent study by Lin et al. (2025) explores how nanodrug carriers, such as liposomes, behave under different breathing conditions. To achieve this, researchers used precise airflow control to simulate normal and pathological breathing, stable aerosol delivery into a microfluidic lung-on-chip platform, and environmental regulation (temperature and humidity) to maintain healthy airway epithelial cells.
The Role of the inExpose System
The inExpose Compact Inhalation Exposure system provided the backbone for this setup. It allowed the team to:
- Generate programmable airflow patterns. These ranged from gentle, low shear stress (LSS) breathing to rapid, high shear stress (HSS) conditions that mimic hyperventilation.
- Maintain physiological humidity and temperature during aerosolization.
- Deliver aerosols into the chip with stable pressure and no backflow.
Integration with the Lung-on-Chip
- Upper channel: Cultured airway epithelial cells exposed to aerosolized nanodrugs.
- Lower channel: Media perfusion mimicking blood flow.
- Central diffuser: Ensured airtight aerosol transfer from InExpose to the chip.
Key Findings
- High shear stress (HSS) led to deeper penetration of liposomes into the mucus layer.
- Aerosol deposition was significantly higher under HSS compared to LSS.
- The system successfully replicated human-like respiratory mechanics, validating the physiological relevance of the model.
Pairing inExpose with a lung-on-chip platform creates a next-generation preclinical model for inhaled nanomedicine. This approach bridges the gap between traditional in vitro assays and the complexity of the human lung. It enables researchers to design personalized inhaled therapies, predict drug clearance and efficacy with greater confidence, and develop safer, more effective nanocarrier designs.
Conclusion
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