Pharmacokinetics population analysis

Inter-individual variability in pharmacokinetics, in particular with respect to clearance [10]. Little is known about the variability of transport to the target site and removal from the target site. Population analysis approaches in PK and PK/PD [50-52] may be helpful in... 

Although, during the early applications of therapeutic mAbs, pharmacokinetic modeling was rarely applied, a variety of analytical techniques has been used over the years to characterize the pharmacokinetics of this class of compounds. The application and information derived from three different methods of noncompart-mental analysis, individual compartmental analysis, and population analysis will be discussed in the following sections. 

Yu, R., L. Gibiansky, E. Gibiansky, and R.S. Geary. 2001. Population pharmacokinetics and pharmacodynamics of ISIS 2302 (Role of population analysis in drug development). In ASCPTAnnual Meeting, Orlando, Florida. 

The analysis of clinical pharmacokinetic data offers additional challenges. Typically, the number of samples available from an individual patient can be limited. In some cases, only one or two samples may be available. If population-based pharmacokinetic values are available, it may still be possible to analyze this limited clinical information using a Bayesian approach. Using patient and population information, the objective function becomes a function of both the residual between the observed and calculated data (as in weighted least squares) and the residual between the population and the calculated values of the parameters, as shown in Eq. (23) ... 

J. R. Wade, A. W. Kehnan, C. A. Howie, and B. Whiting, Effect of misspecification of the absorption process on subsequent parameter estimation in population analysis. I Pharmacokinet Biopharm 21 209-222 (1993). 

S. P. Riley, Pharmacokinetic model selection within a population analysis using NONMEM and WinBUGS, in AAPS Workshop on Bayesian Primer. AAPS, Sait Lake City, UT, 2003. 

P. O. Maitre, M. Buhrer, D. Thomson, and D. R. Stanski, A three-step approach combining Bayesian regression and NONMEM population analysis application to midazolam. J Pharmacokinet Biopharm 19 377-384 (1991). 

Y. Hashimoto and L. B. Sheiner, Designs for population pharmacodynamics value of pharmacokinetic data and population analysis. J Pharmacokinet Biopharm 19 333-353 (1991). 

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. 

It should be pointed out that not all software programs lead to the same model structural model parameter estimates and variance components. Roe (1997) compared the simulated pharmacokinetics of a drug having monoexponential kinetics where clearance was a function of saturable protein binding and renal function and volume of distribution was a function of saturable protein binding only. The basis for the simulated concentrations was a population analysis of 361 quinidine concentration-time measurements from 136 male patients who had experienced cardiac arrhythmia (Verme et al., 1992). The same distribution of simulated observations (e.g., 46 patients had only one sample collected, 33 patients had two samples collected) was used as in the actual study. She and many other participants on the project analyzed the dataset with seven different... 

Wright, P.M.C. Population based pharmacokinetic analysis Why do we need it what is it and what has it told us about anesthesia. British Journal of Anesthesia 1998 80 488-501. 

Gastonguay, M.R., Gibiansky, L., Gillespie, W.R., Khoo, K.-C., and the PPRU Network. Population pharmacokinetics in pediatric patients using Bayesian approaches with informative prior distributions based on adults. Presented at East Coast Population Analysis Group (ECPAG), 1999. 

Ribbing, J. and Jonsson, E.N. Power, selection bias and predictive performance of the population pharmacokinetic covariate model. Presented at Population Analysis Group in Europe Annual Meeting, Verona, Italy, 2003. 

Tod, M., Lokiec, F., Bidault, R., De Bony, F., Petitjean, O., and Aujard, Y. Pharmacokinetics of oral acyclovir in neonates and in infants A population analysis. Antimicrobial Agents and Chemotherapy 2001 45 150-157. 

Verme, C.N., Ludden, T.M., Clementi, W.A., and Harris, S.C. Pharmacokinetics of quinidine in male patients A population analysis. Clinical Pharmacokinetics 1992 22 468-480. 

Holford, N., Hashimoto, Y., and Sheiner, L. B., Time and theophylline concentration help explain the recovery of peak flow following acute airways obstruction. Population analysis of a randomised concentration controlled trial, Clin. Pharmacokinet., 25(6) 506-515, 1993. 

The manufacturer notes that population analysis revealed that amantadine did not have any relevant effects on ropinirole pharmacokinetics. ... 

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. 

Homestam, B., Jerling, M., Karlsson, M.O., and Held, P. DAAf Trial Group, Intravenously administered digoxin in patients with acute atrial fibrillation a population pharmacokinetic/pharmacodynamic analysis based on the digitalis in acute atrial fibrillation trial, Eur.. Clin. Pharmacol., 58, 747-755, 2003. 

WeU accepted Provides rich and high quahty data Can establish a causal link between altered pharmacokinetics and the variable of interest Early results from specific studies enable expansion of patient population in Phase 3 studies not usually difficult to perform Relatively straightforward and simple data analysis Not usually useful for screening Frequent sampling is very difficult in patients in large clinical trials or in children Relationship between altered pharmacokinetics and clinical response may not be established Study sample usually does not represent the target population Small sample may fail to elicit extremes of altered kinetics... 

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