Estelle Yau (1, 2), Andrés Olivares-Morales (2), Michael Gertz (2), Kayode Ogungbenro (1) and Leon Aarons (1)
(1) Centre for Applied Pharmacokinetic Research, The University of Manchester, UK, (2) Roche Pharma and Early Development, Pharmaceutical Sciences, Roche Innovation Center Basel, Switzerland
Objectives:
Optimization of parameters in complex models, such as whole body physiologically-based pharmacokinetic (WBPBPK) models, by integrating observed data is time-consuming and further complicated by the large number of parameters and sparse data which are generally limited to observations from plasma [1]. This work investigated if preclinical in vivo data might provide improved unbound tissue-partitioning coefficients (Kpu) estimates and predictions of human drug distribution compared to the current gold-standard method for Kpu predictions (Rodgers and Rowland (R&R) method [2]). To this end, mechanistic models with different levels of complexity were investigated using a test compound. Optimization of in vivo Kpu-values were performed using plasma concentration-time data in rat and monkey and the success of human PBPK translation was evaluated.
Methods:
Criteria for compound selection were the availability of intravenous plasma concentrations-time data in rats, monkeys and humans and relevant and sensitive in vitro information for Kpu-predictions (e.g., logP, fup and B:P [3]). Diazepam (DZP) was selected as test compound for this study due to the fairly plentiful PK studies available in humans (n=36), monkeys (n=2) and rats (n=5).
In order to limit the number of parameters for estimation, the PBPK model was lumped (reduced-PBPK model) or alternatively common Kpu-values, based on similarity in tissue composition, were estimated while maintaining the structure of a full-PBPK model. Initial values of the (lumped) Kpus were calculated based on DZP physicochemical properties and human tissue composition data using R&R equations [2,4]. Blood flows and tissue volumes were calculated and scaled by body weight [5]. The different mechanistic models were fitted to the rat, monkey and human PK data and Kpu-values were estimated using FOCE-I or SAEM-I/ IMP methods in NONMEM v7.3. The Kpu estimates of the different species were compared and the utility of this approach to improve the prediction of human drug disposition compared to the a priori Kpu predictions using the R&R method was assessed.
Results:
The reduced-PBPK model was comprised of one central and two peripheral compartments. The central compartment contained tissues anticipated to rapidly equilibrate with plasma (e.g., lung, liver and kidney). To maintain physiological interpretability, blood- and lumped tissue-concentrations were computed from the total central concentrations. The blood concentration was used to supply the peripheral tissues which represented moderately (e.g., muscle) and slowly (e.g., adipose) equilibrating tissues. This model made strong assumptions lumping tissues primarily on the magnitude of their blood flows. For DZP, the reduced-PBPK model described the concentration-time profiles almost as well as an empirical two-compartment model and allowed estimation of physiologically relevant partitioning coefficients. The full-PBPK model made fewer assumptions, primarily on the basis of physiological similarity of the composition of tissues, and blood-flows were maintained altogether in this model. This model is therefore considered more generally applicable. Still, the reduced-PBPK model can be implemented as a closed form solution and executed rapidly, while optimization with the full-PBPK model is considerably slower. Predictions using the in vivo Kpu optimized in rats and monkeys with the reduced model showed better human PBPK translation compared to Kpu predictions by the R&R method. Further evaluation of the impact on the translation from preclinical species to humans and optimization of the second mechanistic model are ongoing.
Conclusions:
PBPK models represent the gold-standard to predict human PK for entry into human studies. Generating relevant information from in vitro and preclinical in vivo data might provide greater confidence particularly for drug distribution, as mechanisms of drug distribution are more similar between species than for instance metabolism. The current study provides two mechanistic models that allow a rationale and reproducible assessment of analyzing preclinical data to aid human PK translation. The work and models proposed therein may be extended to other compounds, for a more exhaustive evaluation.
References:
[1] Gueorguieva et al. J Pharmacokinet Pharmacodyn (2006) ; 33(5):571-94
[2] Rodgers & Rowland. J Pharm Sci (2005); 94(6):1259-76.
[3] Yau et al. AAPS J (2020); 22(41) :1-13
[4] Poulin et al. J Pharm Sci (2011) ; 100(10):4127-57
[5] ICRP Publication 89. Ann ICRP (2002); 32 (3–4): 5–265
Reference: PAGE () Abstr 9551 [www.page-meeting.org/?abstract=9551]
Poster: Methodology - New Modelling Approaches