Next-Generation In Vitro Pulmonary Platforms for Respiratory Disease Modelling and Therapeutic Development: Current...

Area of Science:

• Pulmonary Medicine
• Biotechnology
• Computational Biology

Background:

• Pulmonary diseases like COPD and asthma pose global health challenges.
• Traditional 2D cultures and animal models inadequately replicate human lung complexity.
• Limited therapeutic options exist due to complex pathophysiology.

Purpose of the Study:

• To review advancements in in vitro lung models for disease research.
• To explore the integration of computational modeling and AI in pulmonary science.
• To highlight the synergy between advanced models and computational approaches for therapeutic development.

Main Methods:

• Progression from traditional monolayer cultures to air-liquid interface models and 3D lung organoids.
• Integration of computational modeling for simulating disease networks and responses.
• Application of Artificial Intelligence (AI) for high-throughput imaging and biomarker discovery.

Main Results:

• Advanced in vitro models mimic the lung's microenvironment more effectively.
• AI and computational tools enhance disease understanding and biomarker identification.
• Synergistic approach improves translational relevance and reduces animal testing.

Conclusions:

• Combining in vitro lung models with AI and computational methods transforms pulmonary research.
• This synergy accelerates the development of precision therapeutics for lung diseases.
• It paves the way for personalized interventions addressing complex human pulmonary conditions.