Modeling, design, and machine learning-based framework for optimal injectability of microparticle-based drug formulations.

ABSTRACT: Inefficient injection of microparticles through conventional hypodermic needles can impose serious challenges on clinical translation of biopharmaceutical drugs and microparticle-based drug formulations. This study aims to determine the important factors affecting microparticle injectability and establish a predictive framework using computational fluid dynamics, design of experiments, and machine learning. A numerical multiphysics model was developed to examine microparticle flow and needle blockage in a syringe-needle system. Using experimental data, a simple empirical mathematical model was introduced. Results from injection experiments were subsequently incorporated into an artificial neural network to establish a predictive framework for injectability. Last, simulations and experiment

SUBMITTER: Sarmadi M 

PROVIDER: S-EPMC7455482 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature