Molecular Properties Determining Unbound Intracellular and Extracellular Brain Exposure of CNS Drug Candidates

Loryan, Irena; Sinha, Vikash; Mackie, Claire; Peer, Achiel Van; Drinkenburg, Wilhelmus; Vermeulen, An; Heald, Donald; Hammarlund‐Udenaes, Margareta; Wassvik, Carola M.

doi:10.1021/mp5005965

Cited by 54 publications

(55 citation statements)

References 41 publications

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“…The predictive performance in human data ranged between SMAPE of 35–90%. Even though errors <90% may appear large, such < two-fold error is not considered unacceptable when compared to for instance QSAR studies, which are used to predict unbound brain partition coefficients of drugs in drug development (60,61). Secondly, the prediction error is likely inflated because of the use of human data obtained from patients with traumatic brain injury or with nerve-root compression pain.…”

Section: Discussionmentioning

confidence: 99%

A Generic Multi-Compartmental CNS Distribution Model Structure for 9 Drugs Allows Prediction of Human Brain Target Site Concentrations

et al. 2016

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PurposePredicting target site drug concentration in the brain is of key importance for the successful development of drugs acting on the central nervous system. We propose a generic mathematical model to describe the pharmacokinetics in brain compartments, and apply this model to predict human brain disposition.MethodsA mathematical model consisting of several physiological brain compartments in the rat was developed using rich concentration-time profiles from nine structurally diverse drugs in plasma, brain extracellular fluid, and two cerebrospinal fluid compartments. The effect of active drug transporters was also accounted for. Subsequently, the model was translated to predict human concentration-time profiles for acetaminophen and morphine, by scaling or replacing system- and drug-specific parameters in the model.ResultsA common model structure was identified that adequately described the rat pharmacokinetic profiles for each of the nine drugs across brain compartments, with good precision of structural model parameters (relative standard error <37.5%). The model predicted the human concentration-time profiles in different brain compartments well (symmetric mean absolute percentage error <90%).ConclusionsA multi-compartmental brain pharmacokinetic model was developed and its structure could adequately describe data across nine different drugs. The model could be successfully translated to predict human brain concentrations.Electronic supplementary materialThe online version of this article (doi:10.1007/s11095-016-2065-3) contains supplementary material, which is available to authorized users.

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Section: Discussionmentioning

confidence: 99%

A Generic Multi-Compartmental CNS Distribution Model Structure for 9 Drugs Allows Prediction of Human Brain Target Site Concentrations

et al. 2016

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“…Gathering as much information as possible about unbound drug PK in the CNS is important to improve CNS drug development and CNS drug treatment, because it is the driver for drug-target binding kinetics and therewith for the drug effect profile. In contrast to the ex vivo techniques, such as brain homogenate and brain slicing techniques, as well as in silico approaches like quantitative structure-activity relationship models (Chen et al, 2011;Loryan et al, 2015) that can Fig. 3.…”

Section: Discussionmentioning

confidence: 99%

Prediction of human CNS pharmacokinetics using a physiologically-based pharmacokinetic modeling approach

Yamamoto

Välitalo

Wong

et al. 2018

European Journal of Pharmaceutical Sciences

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Knowledge of drug concentration-time profiles at the central nervous system (CNS) target-site is critically important for rational development of CNS targeted drugs. Our aim was to translate a recently published comprehensive CNS physiologically-based pharmacokinetic (PBPK) model from rat to human, and to predict drug concentration-time profiles in multiple CNS compartments on available human data of four drugs (acetaminophen, oxycodone, morphine and phenytoin). Values of the system-specific parameters in the rat CNS PBPK model were replaced by corresponding human values. The contribution of active transporters for the four selected drugs was scaled based on differences in expression of the pertinent transporters in both species. Model predictions were evaluated with available pharmacokinetic (PK) data in human brain extracellular fluid and/or cerebrospinal fluid, obtained under physiologically healthy CNS conditions (acetaminophen, oxycodone, and morphine) and under pathophysiological CNS conditions where CNS physiology could be affected (acetaminophen, morphine and phenytoin). The human CNS PBPK model could successfully predict their concentration-time profiles in multiple human CNS compartments in physiological CNS conditions within a 1.6-fold error. Furthermore, the model allowed investigation of the potential underlying mechanisms that can explain differences in CNS PK associated with pathophysiological changes. This analysis supports the relevance of the developed model to allow more effective selection of CNS drug candidates since it enables the prediction of CNS target-site concentrations in humans, which are essential for drug development and patient treatment.

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“…Whereas K p,uu describes the extent of drug distribution between brain ECF and blood at steady-state, V u,brain describes drug distribution inside the brain parenchyma [26,40]. For a drug that distributes evenly throughout the whole brain tissue, V u,brain is expected to be around 0.8 mL/g brain [41], the water volume in brain parenchyma of which brain ECF accounts for ~ 0.18 mL/g brain [25].…”

Section: Discussionmentioning

confidence: 99%

Influence of peptide transporter 2 (PEPT2) on the distribution of cefadroxil in mouse brain: A microdialysis study

Chen

Keep

Liang

et al. 2017

Biochemical Pharmacology

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Peptide transporter 2 (PEPT2) is a high-affinity low-capacity transporter belonging to the proton-coupled oligopeptide transporter family. Although many aspects of PEPT2 structure-function are known, including its localization in choroid plexus and neurons, its regional activity in brain, especially extracellular fluid (ECF), is uncertain. In this study, the pharmacokinetics and regional brain distribution of cefadroxil, a β-lactam antibiotic and PEPT2 substrate, were investigated in wildtype and Pept2 null mice using in vivo intracerebral microdialysis. Cefadroxil was infused intravenously over 4 hours at 0.15 mg/min/kg, and samples obtained from plasma, brain ECF, cerebrospinal fluid (CSF) and brain tissue. A permeability-surface area experiment was also performed in which 0.15 mg/min/kg cefadroxil was infused intravenously for 10 min, and samples obtained from plasma and brain tissues. Our results showed that PEPT2 ablation significantly increased the brain ECF and CSF levels of cefadroxil (2- to 2.5-fold). In contrast, there were no significant differences between wildtype and Pept2 null mice in the amount of cefadroxil in brain cells. The unbound volume of distribution of cefadroxil in brain was 60% lower in Pept2 null mice indicating an uptake function for PEPT2 in brain cells. Finally, PEPT2 did not affect the influx clearance of cefadroxil, thereby, ruling out differences between the two genotypes in drug entry across the blood-brain barriers. These findings demonstrate, for the first time, the impact of PEPT2 on brain ECF as well as the known role of PEPT2 in removing peptide-like drugs, such as cefadroxil, from the CSF to blood.

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Molecular Properties Determining Unbound Intracellular and Extracellular Brain Exposure of CNS Drug Candidates

Cited by 54 publications

References 41 publications

A Generic Multi-Compartmental CNS Distribution Model Structure for 9 Drugs Allows Prediction of Human Brain Target Site Concentrations

A Generic Multi-Compartmental CNS Distribution Model Structure for 9 Drugs Allows Prediction of Human Brain Target Site Concentrations

Prediction of human CNS pharmacokinetics using a physiologically-based pharmacokinetic modeling approach

Influence of peptide transporter 2 (PEPT2) on the distribution of cefadroxil in mouse brain: A microdialysis study

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