Modelling Inter-Individual Variability in PBPK Models and Deriving Mechanistic Covariate Models for PopPK
Alexander Solms(1,2), Sabine Pilari(1,2), Ludivine Fronton(1,2), Wilhelm Huisinga(2)
(1)Graduate Research Training Program PharMetrX, Martin-Luther-University Halle, Freie University of Berlin and University of Potsdam; (2)Computational Physiology Group, Institute of Mathematics, University of Potsdam
Objectives: Covariate modeling in population pharmacokinetic (Pop PK) is mostly empirical and does rarely profit from the physiologically-based pharmacokinetic (PBPK) modeling framework where anthropometric data or other descriptors can be integrated in a mechanistic way. The objectives are to (i) model inter-individual variability in PBPK models based on body height (BH), body weight (BW), body surface area (BSA) and lean body weight (LBW) with a special emphasize on adipose tissue due to its importance for PK; and to (ii) derive mechanistic covariate models from PBPK models by exploiting the link to empirical models (EM) via lumping.
Methods:Physiological parameters for different age classes were reported in [2]. Partition coefficients were calculated using the methods published in [4,5]. Two approaches -a BH and LBW- were evaluated against data measured in an autopsy study published in [1]. Scaling of physiological parameters was subsequently translated from the PBPK parameters to parameters of the EM based on the lumping [3]. The results were illustrated for Lidocaine and compared to data published in [6]. Possible uncertainties for predicting partition coefficients as reported in [4,5] were considered by Monte Carlo simulations.
Results:
The LBW-scaling generated more variability than the BH-scaling in comparison to experimental data [1]. Compared to the impact of variability in anthropometric data, we found the impact of uncertainty in determining partition coefficients to be much more pronounced on the variability in the concentration-time profiles.
We derived a new mechanistic covariate model that specifically addressed the importance of adipose tissue for PK by simultaneously integrating BW and LBW as descriptors. Our predictions were in good agreement with experimental data of Lidocaine. However, not all patient data could be captured based on the variability generated by anthropometric data, which might be due to uncertainty in the partition coefficients.
For several compounds and children-age classes, we compared PBPK-based- to the commonly used allometric-scaling applied to adult parameters. The results are in good agreement and theoretically underpin the allometric scaling.
Conclusions: Our mechanistic approach gives a general strategy to integrate anthropometric or other descriptors into EM. We find and theoretically understand that the impact of uncertainty in partition coefficients can be more pronounced than the impact of variations in BH, LBW etc within a population.
References:
[1] GL de la Grandmaison, I Clairand, M Durigon, Organ weight in 684 adult autopsies: new tables for a Caucasoid population, Forensic Sci Int 119, 2001.
[2] International Commission on Radiological Protection (ICRP), Basic anatomical and physiological data for use in radiological protection: Reference
values, ICRP Publication 89, 2002.
[3] S Pilari, W Huisinga, Lumping of physiologically-based pharmacokinetic models and a mechanistic derivation of classical compartmental models, J PK PD 37, 2010.
[4] T Rodgers, D Leahy, M Rowland, Physiologically based pharmacokinetic modeling 1: predicting the tissue distribution of moderate-to-strong bases, J Pharm Sci 94, 2005.
[5] T Rodgers, M Rowland, Physiologically based pharmacokinetic modelling 2: predicting the tissue distribution of acids, very weak bases, neutrals and zwitterions, J Pharm Sci 95, 2006.
[6] GT Tucker, RA Boas, Pharmacokinetic aspects of intravenous regional anesthesia.Tucker, Anesthesiology 34, 1971.
