The need for mathematical modelling of spatial drug distribution within the brain

Vendel, Esmée; Rottschäfer, Vivi; Lange, Elizabeth C. M. de

doi:10.1186/s12987-019-0133-x

Cited by 69 publications

(63 citation statements)

References 246 publications

(348 reference statements)

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“…Next, we study how the drug distribution within the 3D brain unit is affected by v blood , P, T m-in and T m-out . Fig 9 shows cross-sections (for y ¼ 1 2 y r and z = 0) of the 3D brain unit at Table 2.…”

Section: The Effect Of the Brain Capillary Blood Flow Velocity In Thementioning

confidence: 99%

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

2020

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The 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 transcellular 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.

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Section: The Effect Of the Brain Capillary Blood Flow Velocity In Thementioning

confidence: 99%

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

2020

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“…In addition, the distribution of therapeutics entering the brain may be inhomogeneous, raising difficulties in ensuring proper target engagement. Vendel et al [159] reviewed the complexity of modelling brain distribution for therapeutics and concluded that more work is still needed. Another example of complexity of drug delivery to brain is the intranasal route.…”

Section: Drug Deliverymentioning

confidence: 99%

This was the year that was: brain barriers and brain fluid research in 2019

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Jones²,

Drewes

2020

Fluids Barriers CNS

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This editorial highlights advances in brain barrier and brain fluid research published in 2019, as well as addressing current controversies and pressing needs. Topics include recent advances related to: the cerebral endothelium and the neurovascular unit; the choroid plexus, arachnoid membrane; cerebrospinal fluid and the glymphatic hypothesis; the impact of disease states on brain barriers and brain fluids; drug delivery to the brain; and translation of preclinical data to the clinic. This editorial also mourns the loss of two important figures in the field, Malcolm B. Segal and Edward G. Stopa.

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“…In principle, the compartment model combined with a comprehensive understanding of where and when drugs penetrate should allow us to make predictions concerning the order in which drug resistance mutations occur. In practice, understanding where, when, and how certain drugs reach parts of the body is complicated (Vendel et al, 2019). Indeed, different studies have measured different relative penetrances of drugs into the tissue versus the plasma.…”

Section: Issues With Identifying and Measuring Compartmentsmentioning

confidence: 99%

Understanding patterns of HIV multi-drug resistance through models of temporal and spatial drug heterogeneity

Feder

Harper

Brumme

et al. 2019

Preprint

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Under the current standard of care, individuals with HIV take three antiretroviral drugs simultaneously. Triple-drug combination therapies limit HIV drug resistance evolution, because viruses resistant to a subset of the cocktail are suppressed by the remainder of the drugs and should not complete replication and spread. Despite this, reanalysis of HIV genetic data shortly after triple drug therapies became available (1990s and 2000s) reveals ongoing drug resistance in patients on three-drug therapies. In disagreement with expected patterns of evolution in three-drug therapy-treated HIV populations, resistance usually evolves one mutation at a time in a semi-predictable order. We argue here that these surprising observations can be explained using a model that divides the human body into compartments (for example, the gut, lymph nodes and brain). If one drug reaches a compartment that the other two drugs cannot, this creates a single-drug compartment that can select for single-drug resistant viruses. Such viruses can potentially become resistant to additional drugs, if they migrate to another compartment where a second drug is present, and so on. In addition to a compartment model, for some drug combinations, an alternative model of time-heterogeneity due to short half-lives combined with sub-optimal adherence could also explain the observations. We discuss how these lessons from HIV drug resistance evolution may be useful for other systems.

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The need for mathematical modelling of spatial drug distribution within the brain

Cited by 69 publications

References 246 publications

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

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

This was the year that was: brain barriers and brain fluid research in 2019

Understanding patterns of HIV multi-drug resistance through models of temporal and spatial drug heterogeneity

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