Development of a Physiologically-Based Pharmacokinetic Model of the Rat Central Nervous System

Abstract

Central nervous system (CNS) drug disposition is dictated by a drug’s physicochemical properties and its ability to permeate physiological barriers. The blood–brain barrier (BBB), blood-cerebrospinal fluid barrier and centrally located drug transporter proteins influence drug disposition within the central nervous system. Attainment of adequate brain-to-plasma and cerebrospinal fluid-to-plasma partitioning is important in determining the efficacy of centrally acting therapeutics. We have developed a physiologically-based pharmacokinetic model of the rat CNS which incorporates brain interstitial fluid (ISF), choroidal epithelial and total cerebrospinal fluid (CSF) compartments and accurately predicts CNS pharmacokinetics. The model yielded reasonable predictions of unbound brain-to-plasma partition ratio (Kpuu,brain) and CSF:plasma ratio (CSF:Plasmau) using a series of in vitro permeability and unbound fraction parameters. When using in vitro permeability data obtained from L-mdr1a cells to estimate rat in vivo permeability, the model successfully predicted, to within 4-fold, Kpuu,brain and CSF:Plasmau for 81.5% of compounds simulated. The model presented allows for simultaneous simulation and analysis of both brain biophase and CSF to accurately predict CNS pharmacokinetics from preclinical drug parameters routinely available during discovery and development pathways.

Quantitative and Mechanistic Understanding of AZD1775 Penetration across Human Blood–Brain Barrier in Glioblastoma Patients Using an IVIVE–PBPK Modeling Approach

“…1 (17), where P app,A→B is the apparent permeability determined from MDCKII cell monolayer and SA is the human brain microvasculature surface area (SA; 15–25 m 2 ).…”

Development of a Region-Specific Physiologically Based Pharmacokinetic Brain Model to Assess Hippocampus and Frontal Cortex Pharmacokinetics

“…A three-stage workflow methodology was applied to model development. Step 1 focused on the validation of a whole-body PBPK model incorporating a previously published CNS PBPK model [ 28 ], for the prediction of Kp uu,brain for 10 passively transported compound. Step 2 adapted this CNS PBPK model to include two regional brain compartments, namely the frontal cortex and hippocampus, and validated these against two reported studies of phenytoin [ 31 ] and carbamazepine [ 33 ] regional brain ECF temporal concentration from rodent microdialysis studies.…”

“…The brain was modeled with a perfusion-limited compartment (see Supplementary Materials Figure S1 ). Absorption (permeability clearances) from the BBB, protein binding (plasma, brain tissue and CSF), metabolic clearance and predicted tissue partition coefficients ( Kp t ) were previously collated by our group [ 28 ] and implemented within the model as described by Equation (S2) in the Supplementary Materials . In this approach, in vitro permeability was scaled to in vivo permeability through correction for the brain microvascular endothelial surface area (150 cm 2 ·g·brain −1 for rats [ 42 ] or 157 cm 2 ·g·brain −1 [ 43 ] for humans) and was parameterized into the appropriate unidirectional PS term (Equations (4) and (5)): where brain weight was assumed to be 1.8 g in rats, 0.36 g in mice, and 1500 g in humans [ 44 , 45 , 46 ].…”

“…When only a single Papp was reported in the literature, the resultant predicted PS was assumed to be bidirectional. Furthermore, for active efflux compounds, the PS blood - to - brain was assumed to be bidirectional and the active efflux component was applied through correction of the PS brain - to - blood of the efflux ratio of the substrate [ 28 ].…”

“…A key benefit of the application of PBPK models is the ability to amalgamate existing relevant physiological processes, which may impact on the pharmacokinetics of compounds alongside a compound’s physicochemical properties to mechanistically describe a compound’s pharmacokinetics and allow both interspecies scaling and the prediction of whole organ and organ sub-compartment temporal concentration profiles. As opposed to empirical models, an integration between system-dependent (physiological) and compound-dependent parameters of PBPK models in predicting the compound’s PK profile has enabled an understanding of the underlying mechanisms of the PK [ 11 , 27 ] and recently been applied to model ECF pharmacokinetics of drugs [ 28 , 29 , 30 ].…”