Machine learning-assisted microfluidic approach for broad-spectrum liposome size control.

ABSTRACT: Liposomes serve as critical carriers for drugs and vaccines, with their biological effects influenced by their size. The microfluidic method, renowned for its precise control, reproducibility, and scalability, has been widely employed for liposome preparation. Although some studies have explored factors affecting liposomal size in microfluidic processes, most focus on small-sized liposomes, predominantly through experimental data analysis. However, the production of larger liposomes, which are equally significant, remains underexplored. In this work, we thoroughly investigate multiple variables influencing liposome size during microfluidic preparation and develop a machine learning (ML) model capable of accurately predicting liposomal size. Experimental validation was conducted using a sta

SUBMITTER: Jia Y 

PROVIDER: S-EPMC12226127 | biostudies-literature | 2025 Jun

REPOSITORIES: biostudies-literature