Between-subject variability

The major difficulty in any functional brain studies is inter-subject comparisons. Essentially, all NIR functional brain studies report high variability between subjects. No true comparison can be made due to relative nature of hemodynamic data. Since path length is unknown under MBLL, it is not possible to assess absolute levels of hemodynamic parameters. Instead, each subject is compared with their own baseline measurements. However, generally speaking, the shape of the time evolution of the signals are similar between subjects and thus can be analyzed using qualitative comparisons. 

The bioavailability of vitamin E from a self-emulsifying preparation was evaluated in comparison to a commercially available soybean oil solution in soft gelatin capsule. Vitamin E administered as a self-emulsifying preparation had markedly higher plasma levels compared to the oil solution formulation, and the extent of absorption was increased almost threefold. Moreover, variability between subjects was markedly reduced in the case of the self-emulsifying preparations [32],... 

Another important consideration in designing mineral absorption experiments is the effect of adaptation to a specific type of diet or level of mineral. Iii mineral absorption studies conducted to date, increasing periods of adaptation to a diet or to a level of nutrient results in decreased variability between subjects. Absorption determined from a diet which is fed only at one meal or on one day may be very different from absorption studied after a period of adaptation to the diet is allowed. 

In this notation, g(9, zj) is used to represent a function (g), perhaps a linear combination of CO variates, that describes the expectation of the /th subjects parameter vector 9i conditional on their demographic characteristics (z,) and population parameter values (0). The variance-covariance matrix (Q) therefore describes the random variability between subjects that is not able to be explained by covariates. 

Nonlinear mixed effects models are similar to linear mixed effects models with the difference being that the function under consideration f(x, 0) is nonlinear in the model parameters 0. Population pharmacokinetics (PopPK) is the study of pharmacokinetics in the population of interest and instead of modeling data from each individual separately, data from all individuals are modeled simultaneously. To account for the different levels of variability (between-subject, within-subject, interoccasion, residual, etc.), nonlinear mixed effects models are used. For the remainder of the chapter, the term PopPK will be used synonymously with nonlinear mixed effects models, even though the latter covers a richer class of models and data types. Along with PopPK is population pharmacodynamics (PopPD), which is the study of a drug s effect in the population of interest. Often PopPK and PopPD are combined into a singular PopPK-PD analysis. 

In a population analysis, there are usually two sources of variability between-subject variability (BSV), sometimes called intersubject variability, and residual variability. Between-subject variability refers to the variance of a parameter across different individuals in the population. In this text, intersubject variability will be used interchangeably with between-subject variability. Residual variability refers to the unexplained variability in the observed data after controlling for other sources of variability. There are other sources of variability that are sometimes encountered in the pharmacokinetic literature interoccasion variability (IOV) and interstudy variability. Each of these sources of variability and how to model them will now be discussed. 

After oral administration, concentrations of propoxyphene peak at 1-2 hours. There is great variability between subjects in the rate of clearance average t ofpropoxyphene in plasma after a single dose is 6-12 hours, which is longer than that of codeine. In humans, the major route of metabolism is H-demethylation to yield norpropoxyphene, which has a t of 30 hours and may accumulate to toxic levels with repeated doses. 

Ratio of variability between subjects or objects to the total variability of all measurements in the sample (Kottner et al., 2011)... 

Data from Yeh etal. [27]. Cmax refers to the maximum plasma concentration achieved, AUC is the calculated area under the plasma-time curve, and Irnax is the time at which Cmax occurs. The numbers in parentheses are the percentage variability on the means. The salt form has lower variability between subjects than the free base monohydrate. 

Hematology in human populations has a number of genetic determinants, and the genetic polymorphism for various components of human blood compartments has the potential to affect the binding of lead in blood, the subsequent dose—toxic response relationships for lead from such alterations, and to enhance the variability between subjects with the same overall external lead contact. 

Thomas and co-workers (221) have studied deposition of technetium-labeled human serum albumin particles, administered through a Siemens Servo 945 nebulizer system and a system 22 Acorn nebulizer unit. Total pulmonary deposition by percentage of the dose in the nebulizer was on the average 2.2%. There was considerable variability between subjects, with a coefficient of variation of 46%, but within subjects reproducibility was close, with a coefficient of variation of 15%. 

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