A Physiologically-Based Pharmacokinetic (PBPK) Model for the Prediction of Levodopa (L-dopa) Disposition in Plasma and Various Brain Compartments Across Species
Yeon-Jung Seo (1), Anumantha G. Kanthasamy (1), Karin Allenspach-Jorn (1), Elizabeth C.M. de Lange* (2), and Jonathan P. Mochel* (1)
(1) Iowa State University, College of Veterinary Medicine, Ames, IA, U.S.A. (2) Leiden University, Division of Pharmacology, Leiden Academic Centre for Drug Research, Leiden, The Netherlands. *: co-corresponding authors.
Objectives:
Levodopa, also known as L-dopa or L-3,4-dihydroxyphenylalanine, is the current standard of care for the treatment of Parkinson’s disease (PD) [1]. Symptoms of PD are associated with the loss of dopaminergic neurons in the central nervous system (CNS). Unlike dopamine (DA), L-dopa can readily cross the blood-brain-barrier (BBB) and be converted to DA by decarboxylases. However, prediction of target site concentrations for L-dopa is complex, and direct measurements of human brain concentrations are highly restricted for ethical reasons. Therefore, alternative methods that can robustly predict human brain concentrations of L-dopa based on in silico approaches are critically needed.The objective of this study was to develop a translational CNS PBPK model to enable predictions of L-dopa disposition in the brain across species.
Methods:
In this study, we developed a PBPK model of L-dopa disposition kinetics in rats and dogs using the generic PBPK model structure from [2]. The model combined a plasma PK and a CNS PBPK module consisting of brain microvessels (MV), brain extracellular fluid (ECF), intracellular fluid (ICF), and multiple cerebrospinal fluid compartments. This model also considered transcellular and paracellular passive diffusion as well as active transport to account for drug transport across the BBB and the blood-cerebrospinal fluid barrier (BCSFB). Literature values were used for system-specific parameters ofrats [2,3] and dogs [4] for all relevant CNS compartments [2,3]. Missing parameter values in dogs were estimated using linear interpolation of brain weight for scaling. For drug-specific parameters , the BBB transmembrane permeability was evaluated using the computed aqueous diffusivity coefficient of L-dopa. Asymmetric transport factors (AF, at the BBB and BCSFB with influx and/or efflux, [2]) were estimated using the fraction of unbound drug concentrations based on the plasma and brain ECF profiles for rats [5]. The same dataset [5] was also used to estimate the L-dopa binding factor value (BF, [2]) by fitting a NLME model in Monolix 2018 R2. L-dopa levels in plasma were used as input to the CNS PBPK model. Parameter estimates for the plasma module were estimated from literature data from rats [6,7] and dogs [8,9] using the SAEM algorithm implemented in Monolix 2018 R2.
Results:
A 2-compartment disposition model with 1st-order elimination was found to best describe the disposition kinetics of L-dopa in plasma in rats and dogs. Structural identifiability of the model parameters was further confirmed using sensitivity analyses, the estimated correlation of the random effects (< 0.10) and the accurate precision of the final parameters (RSE < 30%). For the CNS PBPK module, the simulated time-course of L-dopa concentrations in the brain ECF was compared to available literature data [6], using estimate of the symmetric mean absolute percentage error (SMAPE) for quantification. Results from our simulations (SMAPE = 24%) confirmed that the CNS PBPK model could predict L-dopa concentration-time profiles in the ECF with minimal prediction error.
Conclusions:
These preliminary data are encouraging as they support the ability of the CNS PBPK model to predict L-dopa disposition in the brain ECF in preclinical species. Additional efforts are warranted to further demonstrate the performances of the model in predicting L-dopa distribution in other compartments (in vivo data from dogs are pending). This contribution will be significant as it is expected to provide a mechanistic mathematical platform for modeling the transport, distribution and effect of L-dopa in the CNS.
References:
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