Esmée Vendel1, Vivi Rottschäfer2, Elizabeth C M de Lange3. 1. Mathematical Institute, Niels Bohrweg 1, 2333CA, Leiden, The Netherlands. 2. Mathematical Institute, Niels Bohrweg 1, 2333CA, Leiden, The Netherlands. vivi@math.leidenuniv.nl. 3. Leiden Academic Center for Drug Research, Einsteinweg 55, 2333CC, Leiden, The Netherlands. ecmdelange@lacdr.leidenuniv.nl.
Abstract
PURPOSE: We have developed a 3D brain unit network model to understand the spatial-temporal distribution of a drug within the brain under different (normal and disease) conditions. Our main aim is to study the impact of disease-induced changes in drug transport processes on spatial drug distribution within the brain extracellular fluid (ECF). METHODS: The 3D brain unit network consists of multiple connected single 3D brain units in which the brain capillaries surround the brain ECF. The model includes the distribution of unbound drug within blood plasma, coupled with the distribution of drug within brain ECF and incorporates brain capillaryblood flow, passive paracellular and transcellular BBB transport, active BBB transport, brain ECF diffusion, brain ECF bulk flow, and specific and nonspecific brain tissue binding. All of these processes may change under disease conditions. RESULTS: We show that the simulated disease-induced changes in brain tissue characteristics significantly affect drug concentrations within the brain ECF. CONCLUSIONS: We demonstrate that the 3D brain unit network model is an excellent tool to gain understanding in the interdependencies of the factors governing spatial-temporal drug concentrations within the brain ECF. Additionally, the model helps in predicting the spatial-temporal brain ECF concentrations of existing drugs, under both normal and disease conditions.
PURPOSE: We have developed a 3D brain unit network model to understand the spatial-temporal distribution of a drug within the brain under different (normal and disease) conditions. Our main aim is to study the impact of disease-induced changes in drug transport processes on spatial drug distribution within the brain extracellular fluid (ECF). METHODS: The 3D brain unit network consists of multiple connected single 3D brain units in which the brain capillaries surround the brain ECF. The model includes the distribution of unbound drug within blood plasma, coupled with the distribution of drug within brain ECF and incorporates brain capillaryblood flow, passive paracellular and transcellular BBB transport, active BBB transport, brain ECF diffusion, brain ECF bulk flow, and specific and nonspecific brain tissue binding. All of these processes may change under disease conditions. RESULTS: We show that the simulated disease-induced changes in brain tissue characteristics significantly affect drug concentrations within the brain ECF. CONCLUSIONS: We demonstrate that the 3D brain unit network model is an excellent tool to gain understanding in the interdependencies of the factors governing spatial-temporal drug concentrations within the brain ECF. Additionally, the model helps in predicting the spatial-temporal brain ECF concentrations of existing drugs, under both normal and disease conditions.
Entities:
Keywords:
Brain extracellular fluid; drug binding; drug transport; mathematical; model; pharmacokinetics
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