Biological variability

Data from studies of biological variation may be used to assess the importance of changes in test values within an individual from one occasion to another, determining the appropriateness of reference intervals and, in conjunction with data from analytical variation, establish laboratory analytical goals. Application by cHnicians of information on biological variability could enhance their ability to precisely identify important changes in test results in their patients. 

Categories of biological variation include (1) within an individual and (2) between individuals. The change of laboratory data around a hemostatic set point from one occasion to another within one person is called within-subject or intraindividual variation (Table 17-14). The difference 

TABLE 17-14 Comparison of Intraindividual and Interindividual Variations and Indices of Individuality 

Reprinted with permission of AACC Press, from Fraser CG, Biological variation From principles to practice. Washington DC AACC Press, 2001. 

The test values in a healthy population used to derive a conventional reference interval are subject to the variety of influences including endogenous, exogenous, genetic or ethnic, and laboratory factors discussed above. The statistical approach used to calculate the interval also has considerable influence on the derived reference interval (see Chapter 16). No individual has test results that would span the entire reference interval. Indeed all the results within a healthy individual typically encompass only a small part of most reference intervals. Stratification into more appropriate intervals for subpopulations is sometimes required. The most typical stratifications are based on sex and age. Sinton et al have advocated that separate reference intervals are justified when the difference between the means of the potentially different populations (e.g., men and women or blacks and whites) is greater than 25% of the 95% reference interval of the entire population. An alternative approach to define whether stratification is appropriate is that of Harris and Boyd, which involves calculation of the standard deviations of all of the results from each of the potentially different populations and if the standard deviation of one is more than 1,5 times another stratification is justified.  

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The second perspective might be that of the leader of some large project where chemical analyses are just a side issue, where sample numbers are large and chemical niceties might be completely swamped by, say, biological variability here a statistician will be necessary to make sense of the results in the context of a very complex model. Chemistry is a bit harder to relate to than many other industries in that the measured quantities are often abstract, invisible, and only indirectly linked to what one wants to control. 

The customer might now be led to believe that the products are safer, because biological variability (huge, by comparison), medical practise (it is left to the doctor s discretion to adjust the dose), or compliance (dismal) are outside this discussion. 

Biological exposure indices (BEI) published by the ACGIH are given in Table 4.35. BEIs represent the levels of determinant which are most likely to be observed in specimens collected from a healthy worker who has been exposed to chemicals to the same extent as a worker with inhalation exposure to the TLV. Due to biological variability it is possible for an individual s measurements to exceed the BEI without incurring increased health risk. If, however, levels in specimens obtained from a worker on different occasions persistently exceed the BEI, or if the majority of levels in specimens obtained from a group of workers at the same workplace exceed the BEI, the cause of the excessive values must be investigated and proper action taken to reduce the exposure. 

The biplot in Fig. 37.3 has been constructed from the factor scores of the 12 compounds and the factor loadings of the five physicochemical and biological variables [42,43]. (The biplot graphic technique is explained in Section 31.2.) It is... 

It is widely held that differences exist in the usage and dosage of antipsychotics among ethnic minority groups. A number of factors are felt to account for these differences and include sociocultural variables (racial bias, cultural divide between patient and physician, language), as well as biological variables (pharmacogenetic, pharmacokinetic, and pharmacodynamic). 

Figures 4e and 4f show OCT images of two control seeds after 60 minutes when turgescence has started. Similar to the GMF seeds, individual structural differences of the seeds are clearly visible here. However, after the same time period the heterogeneous absorption zones (Fig. 4f) are less expressed than in the GMF seeds (Fig. 4d). The bright area corresponding to highly scattering regions (Fig. 4d) is narrower (about 100 im) in the control than in GMF seeds (about 200 pm). Thus OCT imaging of barley seeds can distinctly visualize water absorption processes within the first hour, as well as, individual variations in different seeds. The variations reflect the phenomenon of biological variability of seeds at the tissue level.

Stahlhofen, W., Gebhart, J. and Heyder, J. (1981). Biological variability of regional deposition of aerosol particles in the human respiratory tract. Am. Ind. Hyg. Assoc. J. 42 348-352. 

Large biological variability exists between more complex experimental units (i.e., individual animals). 

Enzymatic biologically variable but difficult to optimize Nonenzymatic no biological variability but easier to optimize... 

Prodrug activation occurs enzymatically, nonenzymatically, or, also, sequentially (an enzymatic step followed by a nonenzymatic rearrangement). As much as possible, it is desirable to reduce biological variability, hence the particular interest currently received by nonenzymatic reactions of hydrolysis or intramolecular catalysis [18][20], Reactions of cyclization-elimination appear quite promising and are being explored in a number of studies. 

In addition to and like innumerable other examples, these values are taken to reflect to some extent species differences in esterase activity and demonstrate how biological variability can complicate prodrug design. 

The design of prodrugs that are activated by intramolecular reactions, i.e., prodrugs that are partly or completely activated without the need for enzymatic contribution, is an area of great current interest. As outlined in Chapt. 1, this approach can lead to a decrease in biological variability that facilitates the development of clinically useful prodrugs. One important condition, however, is that intramolecular catalysis should not be so fast that it results in poor bioavailability. 

Structure-activity relationships are generally applied in the pharmaceutical sciences to drug molecules. The value of any structure-activity correlation is determined by the precision of the biological data. So it is with studies of the interaction of nonionic surfactants and biomembranes. Analysis of results is complicated by the difficulty in obtaining data in which one can discern small differences in the activity of closely related compounds, due to i) biological variability in tissues and animals, ii) potential differential metabolism of the surfactants in a homologous series (2), iii) kinetic and dynamic factors such as different rates of absorption of members of the surfactant homologous series (2) and iv) the typically biphasic concentration dependency of nonionic surfactant action (3 ). 

Three distinct regions are observed in the clearance curves. It begins with a region where data is gathered pre-bolus injection, and represents the baseline value for the subsequent experiments. The ICG plasma concentration rapidly peaks within a few seconds, followed by rapid exponential decay as the liver eliminates the dye from blood. Visually, the decay rates are similar for all three, and well within biological variability. After 15 minutes, approximately 90% of the initial signal is lost. The ICG elimination from blood follows the single compartment pharmacokinetics model described by Eq. (3). After several experi-... 

Statistically significant decreases in hematocrit and increases in mean corpuscular hemoglobin concentration have been reported in men occupationally exposed to 0.46-0.75 ppm EGBE for 1-6 years." It was noted that changes were small, showed no relationship to exposure concentration, and were still within normal biological variability. 

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