scholarly journals A 3D brain unit model to further improve prediction of local drug distribution within the brain

2019 ◽  
Author(s):  
Esmée Vendel ◽  
Vivi Rottschäfer ◽  
Elizabeth C. M. de Lange
Keyword(s):  
Extracellular Fluid ◽  
Drug Distribution ◽  
Drug Binding ◽  
Brain Capillaries ◽  
Drug Concentrations ◽  
Unit Model ◽  
Quantitative Understanding ◽  
The Impact ◽  
The Brain ◽  
Excellent Tool

AbstractThe development of drugs targeting the brain still faces a high failure rate. One of the reasons is a lack of quantitative understanding of the complex processes that govern the pharmacokinetics (PK) of a drug within the brain. While a number of models on drug distribution into and within the brain is available, none of these addresses the combination of factors that affect local drug concentrations in brain extracellular fluid (brain ECF).Here, we develop a 3D brain unit model, which builds on our previous proof-of-concept 2D brain unit model, to understand the factors that govern local unbound and bound drug PK within the brain. The 3D brain unit is a cube, in which the brain capillaries surround the brain ECF. Drug concentration-time profiles are described in both a blood-plasma-domain and a brain-ECF-domain by a set of differential equations. The model includes descriptions of blood plasma PK, transport through the blood-brain barrier (BBB), by passive transport via paracellular and trancellular routes, and by active transport, and drug binding kinetics. The impact of all these factors on ultimate local brain ECF unbound and bound drug concentrations is assessed.In this article we show that all the above mentioned factors affect brain ECF PK in an interdependent manner. This indicates that for a quantitative understanding of local drug concentrations within the brain ECF, interdependencies of all transport and binding processes should be understood. To that end, the 3D brain unit model is an excellent tool, and can be used to build a larger network of 3D brain units, in which the properties for each unit can be defined independently to reflect local differences in characteristics of the brain.Author summaryInsights on how a drug distributes within the brain over both time and space are still limited. Here, we develop a ‘3D brain unit model’ in order to understand the factors that control drug concentrations within a small piece of brain tissue, the 3D brain unit. In one 3D brain unit, the brain capillaries, which are the smallest blood vessels of the brain, surround the brain extracellular fluid (ECF). The blood-brain barrier (BBB) is located between the brain capillaries and the brain ECF. The model describes the impact of brain capillary blood flow, transport across the BBB, diffusion, flow and drug binding on the distribution of a drug within the brain ECF. We distinguish between free (unbound) drug and drug that is bound to binding sites within the brain. We show that all of the above mentioned factors affect drug concentrations within brain ECF in an interdependent manner. The 3D brain unit model that we have developed is an excellent tool to increase our understanding of how local drug concentrations within the brain ECF are affected by brain transport and binding processes.

scholarly journals Modeling the Effect of Binding Kinetics in Spatial Drug Distribution in the Brain

2021 ◽  
Vol 2021 ◽  
pp. 1-18
Author(s):  
Nelson Kashaju ◽  
Mark Kimathi ◽  
Verdiana G. Masanja
Keyword(s):  
Specific Binding ◽  
Extracellular Fluid ◽  
Drug Distribution ◽  
Drug Binding ◽  
Binding Kinetics ◽  
Binding Parameter ◽  
Specific Binding Sites ◽  
Distribution Process ◽  
Parameter Values ◽  
The Brain

A 3-dimensional mathematical model is developed to determine the effect of drug binding kinetics on the spatial distribution of a drug within the brain. The key components, namely, transport across the blood-brain barrier (BBB), drug distribution in the brain extracellular fluid (ECF), and drug binding kinetics are coupled with the bidirectional bulk flow of the brain ECF to enhance the visualization of drug concentration in the brain. The model is developed based on the cubical volume of a brain unit, which is a union of three subdomains: the brain ECF, the BBB, and the blood plasma. The model is a set of partial differential equations and the associated initial and boundary conditions through which the drug distribution process in the mentioned subdomains is described. Effects of drug binding kinetics are investigated by varying the binding parameter values for both nonspecific and specific binding sites. All variations of binding parameter values are discussed, and the results show the improved visualization of the effect of binding kinetics in the drug distribution within the brain. For more realistic visualization, we suggest incorporating more brain components that make up the large volume of the brain tissue.

scholarly journals The 3D Brain Unit Network Model to Study Spatial Brain Drug Exposure under Healthy and Pathological Conditions

2020 ◽  
Vol 37 (7) ◽  
Author(s):  
Esmée Vendel ◽  
Vivi Rottschäfer ◽  
Elizabeth C.M. de Lange
Keyword(s):  
Brain Tissue ◽  
Network Model ◽  
Drug Exposure ◽  
Extracellular Fluid ◽  
Transport Processes ◽  
Drug Concentrations ◽  
Induced Changes ◽  
The Impact ◽  
The Brain ◽  
Unit Network

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.

scholarly journals A 3D brain unit model to further improve prediction of local drug distribution within the brain

PLoS ONE ◽  
2020 ◽  
Vol 15 (9) ◽  
pp. e0238397
Author(s):  
Esmée Vendel ◽  
Vivi Rottschäfer ◽  
Elizabeth C. M. de Lange
Keyword(s):  
Drug Distribution ◽  
Unit Model ◽  
The Brain

Antiepileptic drug distribution in cerebral cortex, Ammon's horn, and amygdala in man

1980 ◽  
Vol 52 (5) ◽  
pp. 686-692 ◽  
Author(s):  
Vittorio A. Sironi ◽  
Gianpiero Cabrini ◽  
Maria G. Porro ◽  
Luigi Ravagnati ◽  
Franco Marossero
Keyword(s):  
Drug Distribution ◽  
Anticonvulsant Drug ◽  
Scar Tissue ◽  
Content Type ◽  
Drug Concentrations ◽  
Drug Plasma ◽  
Epileptic Patients ◽  
Drug Plasma Levels ◽  
The Brain ◽  
Temporal Neocortex

✓ Significant correlations in the concentrations of phenobarbital, phenytoin, and carbamazepine in the brain, plasma, and cerebrospinal fluid were found in 12 surgically treated epileptic patients. These findings confirm the clinical reliability of monitoring anticonvulsant drug plasma levels as part of the routine management of epilepsy. Phenobarbital, phenytoin, and carbamazepine are uniformly distributed in the gray and white matter in different brain areas (except for a higher concentration of phenobarbital in the rhinencephalic structures in comparison with the corresponding temporal neocortex) and in normal and scar tissue. In these 12 patients, all of whom were medically resistant, molar cortex concentration of phenobarbital and phenytoin was at “therapeutic” levels or even higher. These data suggest that in therapy-resistant patients, despite cerebral drug concentrations of the same therapeutic level as, or higher than, those present in medically controlled patients, anticonvulsant drugs are pharmacologically ineffective.

scholarly journals Convection-Enhanced Delivery in silico study for personalized brain cancer treatment

2021 ◽  
Author(s):  
Chryso Lambride ◽  
Vasileios Vavourakis ◽  
Triantafyllos Stylianopoulos
Keyword(s):  
Brain Cancer ◽  
In Silico ◽  
Drug Transport ◽  
Drug Distribution ◽  
Local Drug Delivery ◽  
Patient Specific ◽  
Convection Enhanced Delivery ◽  
Formidable Challenge ◽  
The Impact ◽  
The Brain

Abstract Brain cancer therapy remains a formidable challenge in oncology. Convection-enhanced delivery (CED) is an innovative and promising local drug delivery method for the treatment of brain cancer, overcoming the challenges of the systemic delivery of drugs to the brain. To improve our understanding about CED efficacy and drug transport, we present an in silico methodology for brain cancer CED treatment simulation. To achieve this, a three-dimensional finite element biomechanics formulation is utilized which employs patient-specific brain model representation and is used to predict the drug deposition in CED regimes. The model encompasses nonlinear biomechanics and the transport of drugs in the brain parenchyma. Drug distribution was studied under various patho-physiological conditions of the tumor, in terms of tumor vessel wall pore size and tumor tissue hydraulic conductivity as well as for drugs of various sizes, spanning from small molecules to nanoparticles. Our contribution reports for the first time the impact of the size of the vascular wall pores and that of the therapeutic agent on drug distribution during and after CED. The in silico findings provide useful insights of the spatio-temporal distribution and average drug concentration in the tumor towards an effective treatment of brain cancer.

scholarly journals Modeling and Analysis of Drug-Eluting Stents With Biodegradable PLGA Coating: Consequences on Intravascular Drug Delivery

2014 ◽  
Vol 136 (11) ◽  
Author(s):  
Xiaoxiang Zhu ◽  
Richard D. Braatz
Keyword(s):  
Drug Delivery ◽  
Drug Release ◽  
Arterial Wall ◽  
Drug Distribution ◽  
Integrated Model ◽  
Drug Binding ◽  
Drug Eluting Stents ◽  
Drug Concentrations ◽  
Drug Eluting ◽  
Release Profiles

Increasing interests have been raised toward the potential applications of biodegradable poly(lactic-co-glycolic acid) (PLGA) coatings for drug-eluting stents in order to improve the drug delivery and reduce adverse outcomes in stented arteries in patients. This article presents a mathematical model to describe the integrated processes of drug release in a stent with PLGA coating and subsequent drug delivery, distribution, and drug pharmacokinetics in the arterial wall. The integrated model takes into account the PLGA degradation and erosion, anisotropic drug diffusion in the arterial wall, and reversible drug binding. The model simulations first compare the drug delivery from a biodegradable PLGA coating with that from a biodurable coating, including the drug release profiles in the coating, average arterial drug levels, and arterial drug distribution. Using the model for the PLGA stent coating, the simulations further investigate drug internalization, interstitial fluid flow in the arterial wall, and stent embedment for their impact on drug delivery. Simulation results show that these three factors, while imposing little change in the drug release profiles, can greatly change the average drug concentrations in the arterial wall. In particular, each of the factors leads to significant and yet distinguished alterations in the arterial drug distribution that can potentially influence the treatment outcomes. The detailed integrated model provides insights into the design and evaluation of biodegradable PLGA-coated drug-eluting stents for improved intravascular drug delivery.

Measuring antibiotic levels and their relationship with the microbiome in chronic rhinosinusitis

2019 ◽  
Vol 133 (10) ◽  
pp. 862-866
Author(s):  
J Siu ◽  
M D Tingle ◽  
R G Douglas
Keyword(s):  
Drug Therapy ◽  
Gut Microbiota ◽  
Antibiotic Therapy ◽  
Chronic Rhinosinusitis ◽  
Drug Distribution ◽  
The Body ◽  
Oral Antibiotics ◽  
Future Studies ◽  
Drug Concentrations ◽  
The Impact

AbstractBackgroundThe evidence supporting the efficacy of antibiotic therapy in the treatment of chronic rhinosinusitis is not compelling. A limited number of studies show that the changes in the nasal microbiome in patients following drug therapy are unpredictable and variable. The evidence for the impact of oral antibiotics on the gut microbiota is stronger, possibly as a result of differences in drug distribution to various sites around the body. There are few studies on sinus mucosal and mucus levels of oral antibiotics used in the treatment of chronic rhinosinusitis. The distribution dependent effects of antibiotics on the sinonasal microbiome is unclear.ConclusionThis review highlights that relative drug concentrations and their efficacy on microbiota at different sites is an important subject for future studies investigating chronic rhinosinusitis.

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