Mathematical Modeling of Nanoparticle Transport across Blood-Brain Barrier (BBB)

Drug delivery to brain is a major challenge for the treatment of neurodegenerative disorders due to the presence of BBB, a highly selective barricade formed by microvascular endothelial cells. In recent years, different types of nanoparticles have been tested as potential drug carriers through BBB with varying degrees of success. In this study, we have developed a theoretical model to quantify the transport of nanoparticles through BBB endothelial cells based on mass action laws, where an artificial neural network (ANN) model is used to estimate the kinetic rate parameters from experimental data. Experimental data are obtained from a transwell (in-vitro) BBB model constructed with mouse endothelial cells. Results of mass action model with estimated parameters show that it can successfully predict the transient behavior of nanoparticle transport across BBB. Model results also indicate that the endocytosis of nanoparticles through apical membrane is much faster process than the exocytosis of nanoparticles via basolateral membrane. The results of this study can help in designing new drug carriers for effective and noninvasive cure of brain diseases.