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Table 3 Characteristics of models on drug distribution within the brain

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

Process

Blood flow

BBB transport

Transport within the brain ECF

Cellular exchange

Binding kinetics

Metabolism

Sections:

Modelling drug transport through the brain capillary system

Modelling drug transport across the BBB

Modelling drug transport within the brain ECF

Modelling intra-extracellular exchange

Modelling drug binding kinetics

Modelling drug metabolism in the brain

Model

  

Diffusion

Bulk flow

 

Specific

Non-specific

 

Brain vasculatue

 [125]

+

*

*

 [116]

+

+

+

 [121]

+

+

+

*

Brain ECF

 [133]

+

+

+

 [154]

+

+

+

+

+

 [129]

*

+

+

+

*

*

*

 [71, 150, 150, 156, 182, 182, 184]

+

 [33, 164]

+

+

 [192]

+

+

*

 [127]

+

+

+

*

*

 [107]

*

+

+

*

*

 [128]

*

+

 [135, 152]

*

+

*

*

 [153]

*

+

+

*

*

*

 [130, 131]

*

+

+

*

*

*

 [134]

+

+

*

*

Compartmental

 [142]

+

+

+

*

 [145]

+

+

*

*

 [136, 137, 139]

+

 [141]

+

+

 [140, 143]

+

+

*

Hybrid

 [111]

+

+

+

+

+

+

 [212]

 [106]

+

+

 [132]

*

+

+

*

*

*

*

 [54]

+

+

+

*

 [126]

+

+

+

+

*

  1. Models are categorised based on their inclusion of processes affecting drug distribution within the brain as discussed in this section. In simple compartmental models, discussed in “Modelling drug exchange between compartments”, transport within compartments (such as the brain ECF) is not described, but multiple of the other processes may be covered. Models on drug distribution within the brain are classified into models on transport to the brain from the brain vasculature, transport within the brain ECF (i.e. models that include spatial transport within the brain ECF), simple compartmental models (i.e. models that include drug exchange between several compartments representing components of or related to the brain tissue but do not include spatial distribution within the compartments) and hybrid models (i.e. models that are a combination of multiple classes)
  2. +The process is covered
  3. The process is not covered
  4. * The process is covered, but by an elimination rate constant rather than by a complete description of the process