Microfluidic Synthesis of Indomethacin-Loaded PLGA Microparticles Optimized by Machine Learning.

ABSTRACT: Several attempts have been made to encapsulate indomethacin (IND), to control its sustained release and reduce its side effects. To develop a successful formulation, drug release from a polymeric matrix and subsequent biodegradation need to be achieved. In this study, we focus on combining microfluidic and artificial intelligence (AI) technologies, alongside using biomaterials, to generate drug-loaded polymeric microparticles (MPs). Our strategy is based on using Poly (D,L-lactide-co-glycolide) (PLGA) as a biodegradable polymer for the generation of a controlled drug delivery vehicle, with IND as an example of a poorly soluble drug, a 3D flow focusing microfluidic chip as a simple device synthesis particle, and machine learning using artificial neural networks (ANNs) as an in silico tool t

SUBMITTER: Damiati SA 

PROVIDER: S-EPMC8493061 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature