Microfluidic platforms for high-throughput generation of stimuli-responsive liposome libraries

刺激响应型脂质体系统已经成为一种很有前途的部位选择性递送和释放药物的方法。本项目旨在开发一种新型的高通量微流控平台，用于制备刺激响应型脂质体。该系统将与机器学习方法和机器人技术相结合，以期构建脂质体文库，该文库可以根据用户定义的性能特征进行筛选和优化，这些用户定义的性能特征与体内传递性能保持一致。

Stimuli-responsive liposome systems have emerged as a promising way to deliver and release drugs in a site-selective manner. This project aims to develop a novel high-throughput microfluidic platform for fabricating stimuli responsive liposomes. This system will be coupled with machine learning approaches and robotics with a view to constructing liposome libraries that can be screened and optimised against user defined performance characteristics that are aligned with in-vivo delivery performance.