Population pharmacokinetic analysis

Although the fundamental research for population analysis techniques was carried out almost 30 years ago, modern computing power has allowed a more sophisticated development of the technique and the transfer to applied research. 

Various methods are available to estimate population parameters, but today the nonlinear mixed effects modeling approach is the most common one employed. Population analyses have been performed for mAbs such as basiliximab, daclizu-mab and trastuzumab, as well as several others in development, including clenolixi-mab and sibrotuzumab. Population pharmacokinetic models comprise three submodels the structural the statistical and covariate submodels (Fig. 3.13). Their development and impact for mAbs will be discussed in the following section. 

---

Jen, J.F. et al., Population pharmacokinetic analysis of pegylated interferon alfa-2b and interferon alfa-2b in patients with chronic hepatitis C, Clin. Pharmacol. Then, 69, 407, 2001. 

Pharmacokinetics Population pharmacokinetic analysis gave the following values for a reference patient (white male, 45 years of age, with a body weight of 80 kg and no proteinuria) Systemic clearance is 15 mL/h, volume of central compartment is P.1160... 

Fruit juices such as grapefruit, orange, and apple may reduce the bioavailability and exposure of fexofenadine. This is based on the results from three clinical studies using histamine-induced skin wheals and flares coupled with population pharmacokinetic analysis. Therefore, to maximize the effects of fexofenadine, it is recommended that ALLEGRA-D 24 HOUR should be taken with water... 

Table 14.4 Cetuximab population pharmacokinetic analysis final model parameter estimates.

Fig. 14.6 Simulation of clearance (CL) for cetuximab versus concentration, based on the results of the integrated population pharmacokinetic analysis.

Additional population pharmacokinetic analysis may assist the overall evaluation... 

A data structure was created by combining PK and PD data from three clinical studies. In double-blind, randomized, placebo-controlled, parallel-group, 2 week Phase III studies performed in the target patient population, sparse blood samples were collected for population pharmacokinetic analysis (Table 6). 

Population pharmacokinetic analysis is an extension of the modeling procedure. The purpose of population pharmacokinetic analysis is summarized in Table 10.2. 

Population pharmacokinetic analysis provides not only an opportunity to estimate variability, but also to explain it. Variability is usually characterized in terms of fixed and random effects. The fixed effects are the population average values of pharmacokinetic parameters, which may in turn be a function of patient characteristics discussed above. The random effects... 

Pai, S.M. Shukla, U.A. Grasela, T.H. Knupp, C.A. Dolin, R. Valentine, F.T. McLaren, C. Liebman, H.A. Martin, R.R. Pittman, K.A. Barbhaiya, R.H. Population pharmacokinetic analysis of didanosine (2, 3 -dideoxyino-sine) plasma concentration obtained in phase I clinical trials in patients with AIDS or AIDS-related complex. J. Clin. Pharmacol. Ther. 1995, 52, 164—169. 

Metabolism and elimination Plasma concentrations of alosetron increase proportionality with increasing single oral doses up to 8 mg and more than proportionately at a single oral dose of 16 mg. Twice-daily oral dosing of alosetron does not result in accumulation. The terminal elimination half-life of alosetron is 1.5h (plasma clearance is 600 ml min ). Population pharmacokinetic analysis in IBS patients confirmed that alosetron clearance is minimally influenced by doses up to 8 mg. 

P. Girard, L. B. Sheiner, H. Kastrissios, and T. F. Blascke, Do we need full compliance data for population pharmacokinetic analysis J Pharmacokinet Pharmacodyn 24 265-282 (1996). 

F. Mentre, C. Dubmc, and J. P. Thenot, Population pharmacokinetic analysis and optimization of the experimental design for mizolastine solution in children. J Pharmacokinet Pharmacodyn 28 299-319 (2001). 

T. Funaki, Enterohepatic circulation model for population pharmacokinetic analysis. J Pharm Pharmacol 51 1143-1148 (1999). 

K. A. Jackson, S. E. Rosenbaum, B. M. Kerr, Y. K. Pithavala, G. Yuen, and M. N. Dudley, A population pharmacokinetic analysis of nelflnavir mesylate in human immunodeficiency virus-infected patients enrolled in a phase III clinical trial. Antimicrob Agents Chemother 44 1832-1837 (2000). 

Hanada, K., Nishijima, K., Ogata, H., Atagi, S., Kawahara, M. Population pharmacokinetic analysis of cisplatin and its metabolites in cancer patients possible misinterpretation of co variates for pharmacokinetic parameters calculated from the concentrations of unchanged cisplatin, ultrafiltered platinum and total platinum. Jpn J Clin Oncol 2001, 31, 179-184. 

Still, even with following Wagner s guidelines it may be that many different models fit the data equally well. The situations becomes more complex when variables other than time are included in the model, such as in a population pharmacokinetic analysis. Often then it is of interest to compare a number of different models because the analyst is unclear which model is the more appropriate model when different models fit almost equally to the same data. For example, the Emax model is routinely used to analyze hyperbolic data, but it is not the only model that can be used. A Weibull model can be used with equal success and justification. One method that can be used to discriminate between rival models is to run another experiment, changing the conditions and seeing how the model predictions perform, although this may be unpractical due to time or fiscal constraints. Another alternative is to base model selection on some a priori criterion. 

R. W. How many patients and blood levels are necessary for population pharmacokinetic analysis A study of a one compartment model applied to cyclosporine. European Journal of Clinical Pharmacology 1996 51 283-288. 

Jackson, K.A., Rosenbaum, S.E., Kerr, B.M., Pithavala, Y.K., Yuen, G. and Dudley, M.N. A population pharmacokinetic analysis of nelfinavir mesylate in human immunodeficiency virus-infected patients enrolled in a Phase III clinical trial. Antimicrobial Agents and Chemotherapy 2000 44 1832-1837. 

Laporte-Simitsidis, S., Girard, P., Mismetti, P., Chabaud, S., Decousus, H., and Boissel, J.P. Interstudy variability in population pharmacokinetic analysis When and how to estimate it Journal of Pharmaceutical Sciences 2000 89 155-166. 

M., and Stockis, A. Retrospective population pharmacokinetic analysis of cetirizine in children aged 6 months to 12 years. British Journal of Clinical Pharmacology 2004 57 402-411. 

Wade, J.R., Beal, S.L., and Sambol, N.C. Interaction between structural, statistical, and covariate models in population pharmacokinetic analysis. Journal of Pharmacokinetics and Biopharmaceutics 1994 22 165-177. 

Population pharmacokinetic analysis proceeds in stages. The most successful efforts have the benefit of prospective smdy designs, clearly defined objectives, and data analysis plans that are defined prior to study initiation. Although some deviation in the order of the analysis plan is possible, there is a typical sequence that is followed ... 

Prior to initiating a population pharmacokinetic analysis, an accurate representahon of the underlying pharmacokinehcs, the so-called structural model, must be made. Kinetic phenomena can be described by differenhal equations or via implicit or explicit integrated forms, typically with time as the independent variable. As with the eshmahon of any model, we are concerned with identifying the best values for parameters 9i, 02,..., O, of a model by minimizing or maximizing some objective function. For example, some function y that is expressed in terms of several 0 terms and an independent variable X, such as... 

---