Pharmacokinetics data analysis

Pharmacokinetic data analysis requires determination of the analyte in various body fluids. In the case of therapeutic antibodies, serum is the most common matrix to be analyzed. For a critical interpretation of pharmacokinetic data the chosen bioanalytical methods must be considered. The most frequently used for mAbs include enzyme-linked immunosorbent assay (ELISA), capillary electrophoresis (CE)/polyacrylamide gel electrophoresis (PAGE), fluorescence-activated cell sorting (FACS), and surface plasmon resonance (SPR). The challenges and limitations of bioanalytical methods used for the analysis of mAb concentrations are discussed in detail in Chapter 6. 

Fig. 3.12 Data set for a population pharmacokinetic data analysis. Individual data points from one individual are connected by thin lines. The thick line represents the population time course.

Sheiner LB. The population approach to pharmacokinetic data analysis Rationale and standard data analysis methods. Drug Me tab Rev 1984 15 153-71. 

The pharmacokinetic results obtained with HPLC/ UV and HPLC/MS/MS are shown in Figure 12.10. Dotted lines indicate the LOQ for F-ddA by both assay methods. Data for F-ddI obtained by either method show good agreemeiiL being well above the LOQ for both techniques. On the other hand, all of the F-ddA data points are below the LOQ by HPLC/UV. Nonetheless, measurements reported below LOQs can be useful in that they help define what assay sensitivity must be achieved for pharmacokinetic data analysis. 

Atkinson AJ Jr. Gentamicin kinetics A simulation case study. In Foster DM, Atkinson AJ Jr. Principles of pharmacokinetic data analysis Modeling and simulation (workshop manual). Seattle SAAM Institute, Inc. 2004. 

Eluehler, H. Huber, H. Widmer, E. Brechbuehler, S. Experiences in the application of NONMEM to pharmacokinetic data analysis. Drug. Metab. Rev. 1984, 15, 317-339. 

Gompartmental models have been the foundation of pharmacokinetic data analysis. The compartmental approach is presented here to facilitate definition of important pharmacokinetic parameters. Gompartmental models are determin-... 

Intermediate workshop in population pharmacokinetic data analysis using the NONMEM system. Regents of the University of California, 1992. 

In recent years, non-compartmental or model-independent approaches to pharmacokinetic data analysis have been increasingly utilized since this approach permits the analysis of data without the use of a specific compartment model. Consequently, sophisticated, and often complex, computational methods are not required. The statistical or non-compartmental concept was first reported by Yamaoka in a general manner and by Cutler with specific application to mean absorption time. Riegelman and Collier reviewed and clarified these concepts and applied statistical moment theory to the evaluation of in vivo absorption time. This concept has many additional significant applications in pharmacokinetic calculations. 

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