Pharmacokinetic Research Progress of Anti-tumor Drugs Targeting for Pulmonary Administration

Background: Cancer is a major problem that threatens human survival and has a high mortality rate. The traditional chemotherapy methods are mainly intravenous injection and oral administration, but have obvious toxic and side effects. Anti-tumor drugs for pulmonary administration can enhance drug targeting, increase local drug concentration, and reduce the damage to systemic organs, especially for the treatment of lung cancer. Methods: The articles on the pharmacokinetics of anti-tumor drugs targeting pulmonary administration were retrieved from the Pub Med database. This article mainly took lung cancer as an example and summarized the pharmacokinetic characteristics of anti-tumor drugs targeting for pulmonary administration contained in nanoparticles, dendrimers, liposomes and micelles. Results: The review shows that the pharmacokinetics process of pulmonary administration is associated with a drug carrier by increasing the deposition and release of drugs in the lung, and retarding the lung clearance rate. Among them, the surface of dendrimers could be readily modified, and polymer micelles have favorable loading efficiency. In the case of inhalation administration, liposomes exhibit more excellent lung retention properties compared to other non-lipid carriers. Therefore, the appropriate drug carrier is instrumental to increase the curative effect of anti-tumor drugs and reduce the toxic effect on surrounding healthy tissues or organs. Conclusion: In the process of pulmonary administration, the carrier-embedded antitumor drugs have the characteristics of targeted and sustained release compared with non-packaging drugs, which provides a theoretical basis for the clinical rational formulation of chemotherapy regimens. However, there is currently a lack of comparative research between drug packaging materials, and more importantly, the development of safe and effective anti-tumor drugs targeting for pulmonary administration requires more data.