Engineering and Technology

Artificial intelligence application for rapid fabrication of size-tunable PLGA microparticles in microfluidics

S. A. Damiati, D. Rossi, et al.

This research merges artificial intelligence and microfluidics to create synthetic polymeric particles, showcasing an innovative use of artificial neural networks to accurately predict the size of PLGA microparticles. Conducted by Safa A. Damiati, Damiano Rossi, Haakan N. Joensson, and Samar Damiati, this study offers a quick and cost-effective solution for producing microparticles for biomedical use.

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Abstract

This study combines artificial intelligence (AI) and microfluidics to fabricate synthetic polymeric particles. Machine learning, specifically artificial neural networks (ANNs), was used to predict the size of poly(D,L-lactide-co-glycolide) (PLGA) microparticles produced by various microfluidic systems. The ANN models considered factors like PLGA concentration and flow rates to predict particle size with high accuracy, offering a rapid and economical platform for producing PLGA microparticles of defined sizes for biomedical and pharmaceutical applications.

Publisher

Scientific Reports

Published On

Nov 11, 2020

Authors

Safa A. Damiati, Damiano Rossi, Haakan N. Joensson, Samar Damiati

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