Subject variability sources

Absorption studies have been conducted using several dietary treatments. One dietary approach has been to use purified diets with egg albumen as the protein source. This approach reduces of day to day and between subject variability in the nutrient content of diets. It is well suited for use when levels of specific nutrients or dietary components must be carefully controlled and/or varied without changing any other factors in the diet. Since all other dietary components remain constant, any differences found between treatments can be ascribed to the altered nutrient under study. 

Inherent in any reported laboratory test results on patients are influences of (1) biological variation, (2) inherent analytical error, (3) preanalytical and postanalytical sources of variation, and (4) possible pathophysiological alterations. When repeated measurements are made over time in one individual, even under standardized conditions, there is a considerable variability in the test results. The variability within the individual is attributable to both analytical and intraindividual factors but the intraindividual (within-subject) variability is typically less than the variability among a group of individuals. This means that when ana-... 

Figure 6.1 illustrates this relationship graphically for a 1-compartment open model plotted on a semi-log scale for two different subjects. Equation (6.15) has fixed effects (3 and random effects U . Note that if z = 0, then Eq. (6.15) simplifies to a general linear model. If there are no fixed effects in the model and all model parameters are allowed to vary across subjects, then Eq. (6.16) is referred to as a random coefficients model. It is assumed that U is normally distributed with mean 0 and variance G (which assesses between-subject variability), s is normally distributed with mean 0 and variance R (which assesses residual variability), and that the random effects and residuals are independent. Sometimes R is referred to as within-subject or intrasubject variability but this is not technically correct because within-subject variability is but one component of residual variability. There may be other sources of variability in R, sometimes many others, like model misspecification or measurement variability. However, in this book within-subject variability and residual variability will be used interchangeably. Notice that the model assumes that each subject follows a linear regression model where some parameters are population-specific and others are subject-specific. Also note that the residual errors are within-subject errors. 

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. 

To obtain initial estimates, an Emax model was fit to the data set in a na ive-pooled manner, which does not take into account the within-subject correlations and assumes each observation comes from a unique individual. The final estimates from this nonlinear model, 84% maximal inhibition and 0.6 ng/mL as the IC50, were used as the initial values in the nonlinear mixed effects model. The additive variance component and between-subject variability (BSV) on Emax was modeled using an additive error models with initial values equal to 10%. BSV in IC50 was modeled using an exponential error model with an initial estimate of 10%. The model minimized successfully with R-matrix singularity and an objective function value (OFV) of 648.217. The standard deviation (square root of the variance component) associated with IC50 was 6.66E-5 ng/mL and was the likely source of the... 

Riuming, C.A., Mattes, R.D. Tucker, R.M. Fat taste in hnmans sources of within- and between-subject variability. Prog. Lipid Res. 2013, 52 438-445. 

Uncertainty, on the other hand, denotes the nondeterminism due to limited accuracy of models used to characterize the structural response. This lack of accuracy can be caused by inherent limitations of the model when representing the phenomena it is meant to capture (including issues such as model resolution). Also, it can be caused by limited data availability for model calibration. Another type of nondeterminism described by the term uncertainty is the subjective variability associated with the process of selecting a model from a set of concurrent models involving different experts. This source of uncertainty is particularly pronounced in probabilistic seismic hazard analysis. 

The collector contains an electrically-heated rubidium salt used as the thermionic source. During the elution of a molecule of a nitrogen compound, the nitrogen is ionized and the collection of these ions produces the signal. The detector is very sensitive but Its efficiency is variable subject to the type of nitrogen molecule, making quantification somewhat delicate. 

The regression models considered earlier apply only to functions containing a single independent variable. Analytical methods, however, are frequently subject to determinate sources of error due to interferents that contribute to the measured signal. In the presence of a single interferent, equations 5.1 and 5.2 become... 

Even the best-laid plans are subject to last minute changes and unexpected variables, and there is an element of uncertainty in every estimate. Some of the more common sources of variance include factors beyond your control, such as ... 

In an ESI source, the sample M is dissolved in a polar solvent and sprayed through a steel capillary tube. As it exits the tube, it is subjected to a high voltage that causes it to become protonated by removing H+ ions from the solvent. The volatile solvent is then evaporated, giving variably protonated sample... 

It is important to note that the fitting according to eq. (1) requires zero intercept behavior i.e., F =. 00 for H (for which Oj = Or =. 00). While we recognize that the data for the unsubstituted (H) member of a set may be as subject to experimental error as any other member, such error is generally relatively small for a set of reliable data. Any constant error from this source will be distributed among all of the substituents in such a manner as to achieve best fit. Any loss in precision of fitting of the set which may result by such a procedure we believe is a small price to pay compared to the violence done by introduction in eq. (I) of a completely variable constant parameter. The latter procedure has been utilized by other authors both in treatments by the simple Hammett equation and by the dual substituent parameter equation. 

Figure 21.3 Modeling and simulation in the general context of the study of xenobiot-ics. The network of signals and regulatory pathways, sources of variability, and multistep regulation that are involved in this problem is shown together with its main components. It is important to realize how between-subject and between-event variation must be addressed in a model of the system that is not purely structural, but also statistical. The power of model-based data analysis is to elucidate the (main) subsystems and their putative role in overall regulation, at a variety of life stages, species, and functional (cell to organismal) levels. Images have been selected for illustrative purposes only. See color plate.

After a brief period of use, the graphite tubes and rods that are commonly employed In electrothermal atomizers begin to deteriorate, and their electrical characteristics become subject to drift (7,9,47). This is one of the most troublesome sources of analytical variability. Maessen et al (47) demonstrated that the properties of graphite (e.g. porosity ancl conductivity)... 

Standards are used for a number of purposes. An external standard contains a mixture of substances typically observed in the sample. Knowledge of the concentration of the standard substances allows calibration of the detector to compensate for run-to-run or day-to-day variability. External standards should not be subjected to hydrolysis or other sample processing steps, except as necessary for detection, since this would add other sources... 

Ref. Subject Design Outcome variable(s) Source of caffeine data Findings... 

The effect of raw material variability on tablet production [2,30,31] and suggestions for improving tableting quality of starting materials [21] has been the subject of several publications. Table 3, which lists the characteristics of different sources of magnesium stearate, clearly illustrates the variability of this material [32]. Phadke and Eichorst have also confirmed that significant differences can exist between different sources, and even different lots, of magnesium stearate... 

The temperature in a sewer depends on a number of different conditions, e.g., climate, source of wastewater and system characteristics. The microbial community developed in a sewer is typically subject to annual temperature variations and, to some extent, a daily variability. Different microbial systems may be developed under different temperature conditions, and process rates relevant for the microorganisms vary considerably with temperature. Long-term variations may affect which microbial population will develop in a sewer, whereas short-term variations have impacts on microbial processes in the cell itself as well as on the diffusion rate of substrates. 

Literature. The publication of case reports in medical and scientific journals is an important primary source of information on ADRs. Many ADRs are noted in medical and scientific journals before they become well known. For example, the association of thalidomide with birth defects was first noted in a letter to the Lancet in 1961. The quality of ADR reports in the published literature can be variable and has been the subject of much criticism and correspondence, though guidelines have been promulgated for these (Jones, 1982). 

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