Human blood flow, characteristics

Later we proceed by taking into account the characteristics of human blood flow (Gorbyk, 2013), given in Table 10.2. 

Once the structure of the PBPK model is formulated, the next step is specifying the model parameters. These can be classified into a chemical-independent set of parameters (such as physiological characteristics, tissue volumes, and blood flow rates) and a chemical-specific set (such as blood/tissue partition coefficients, and metabolic biotransformation parameters). Values for the chemical-independent parameters are usually obtained from the scientific literature and databases of physiological parameters. Specification of chemical-specific parameter values is generally more challenging. Values for one or more chemical-specific parameters may also be available in the literature and databases of biochemical and metabolic data. Values for parameters that are not expected to have substantial interspecies differences (e.g., tissue/blood partition coefficients) can be imputed based on parameter values in animals. Parameter values can also be estimated by conducting in vitro experiments with human tissue. Partitioning of a chemical between tissues can be obtained by vial equilibration or equilibrium dialysis studies, and metabolic parameters can be estimated from in vitro metabolic systems such as microsomal and isolated hepatocyte syterns. Parameters not available from the aforementioned sources can be estimated directly from in vivo data, as discussed in Section 43.4.5. 

In this section, some of the characteristics of blood flow are described with emphasis on the fact that blood is a suspension of particulates. First, the types of cells present in human blood are described, and the flow of blood through the human vasculature is discussed with emphasis on the multiscale nature of the relevant phenomena. As an example of bioengineering research dealing with the vascular system, some of the transport-related aspects of the onset of atherosclerois are discussed. Finally, the use of DNS to model suspensions of red blood cells is reviewed, and prospects for multiscale models of transport phenomena associated with blood are discussed. 

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