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The impact of P-gp functionality on non-steady state relationships between CSF and brain extracellular fluid.

Westerhout J, Smeets J, Danhof M, de Lange EC - J Pharmacokinet Pharmacodyn (2013)

Bottom Line: It is concluded that in parallel obtained data on unbound brainECF, CSF and plasma concentrations, under dynamic conditions, is a complex but most valid approach to reveal the mechanisms underlying the relationship between brainECF and CSF concentrations.This relationship is significantly influenced by activity of P-gp.Therefore, information on functionality of P-gp is required for the prediction of human brain target site concentrations of P-gp substrates on the basis of human CSF concentrations.

View Article: PubMed Central - PubMed

Affiliation: Department of Pharmacology, Leiden/Amsterdam Center for Drug Research, Einsteinweg 55, 2333 CC, Leiden, The Netherlands.

ABSTRACT
In the development of central nervous system (CNS)-targeted drugs, the prediction of human CNS target exposure is a big challenge. Cerebrospinal fluid (CSF) concentrations have often been suggested as a 'good enough' surrogate for brain extracellular fluid (brainECF, brain target site) concentrations in humans. However, brain anatomy and physiology indicates prudence. We have applied a multiple microdialysis probe approach in rats, for continuous measurement and direct comparison of quinidine kinetics in brainECF, CSF, and plasma. The data obtained indicated important differences between brainECF and CSF kinetics, with brainECF kinetics being most sensitive to P-gp inhibition. To describe the data we developed a systems-based pharmacokinetic model. Our findings indicated that: (1) brainECF- and CSF-to-unbound plasma AUC0-360 ratios were all over 100 %; (2) P-gp also restricts brain intracellular exposure; (3) a direct transport route of quinidine from plasma to brain cells exists; (4) P-gp-mediated efflux of quinidine at the blood-brain barrier seems to result of combined efflux enhancement and influx hindrance; (5) P-gp at the blood-CSF barrier either functions as an efflux transporter or is not functioning at all. It is concluded that in parallel obtained data on unbound brainECF, CSF and plasma concentrations, under dynamic conditions, is a complex but most valid approach to reveal the mechanisms underlying the relationship between brainECF and CSF concentrations. This relationship is significantly influenced by activity of P-gp. Therefore, information on functionality of P-gp is required for the prediction of human brain target site concentrations of P-gp substrates on the basis of human CSF concentrations.

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Diagram of the SBPK model that was used to describe the intra-brain distribution in the rat. CLE is the elimination clearance from plasma, QPL–PERx is the inter-compartmental clearance between plasma and the first (x = 1) or second (x = 2) peripheral compartment. Further, for transfer clearances between compartments (CLfrom comp-to comp), denotations of the compartments are: PL plasma; ECF brainECF; DBR braindeep; LV lateral ventricle; TFV third and fourth ventricle; CM cisterna magna and SAS subarachnoid space. QECF is the flow rate of brain ECF, QCSF is the flow rate of CSF. For peripheral and plasma compartments, V volume of distribution; for brain compartments, V volume, not shown in the diagram
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Fig4: Diagram of the SBPK model that was used to describe the intra-brain distribution in the rat. CLE is the elimination clearance from plasma, QPL–PERx is the inter-compartmental clearance between plasma and the first (x = 1) or second (x = 2) peripheral compartment. Further, for transfer clearances between compartments (CLfrom comp-to comp), denotations of the compartments are: PL plasma; ECF brainECF; DBR braindeep; LV lateral ventricle; TFV third and fourth ventricle; CM cisterna magna and SAS subarachnoid space. QECF is the flow rate of brain ECF, QCSF is the flow rate of CSF. For peripheral and plasma compartments, V volume of distribution; for brain compartments, V volume, not shown in the diagram

Mentions: The final SBPK model is shown in Fig. 4. The differential equations of this model can be found in the appendix. The final estimation of the PK parameters is summarized in Table 4. Here, the parameters are the same as for Table 3, with the addition of the following: CLPL–TFV is the clearance from plasma to CSFTFV, CLTFV–PL is the clearance from CSFTFV to plasma, QECF is the flow rate of brain ECF, QCSF is the flow rate of CSF, VTFV is the volume of the third and fourth ventricle combined and VSAS is the volume of the subarachnoid space.Fig. 4


The impact of P-gp functionality on non-steady state relationships between CSF and brain extracellular fluid.

Westerhout J, Smeets J, Danhof M, de Lange EC - J Pharmacokinet Pharmacodyn (2013)

Diagram of the SBPK model that was used to describe the intra-brain distribution in the rat. CLE is the elimination clearance from plasma, QPL–PERx is the inter-compartmental clearance between plasma and the first (x = 1) or second (x = 2) peripheral compartment. Further, for transfer clearances between compartments (CLfrom comp-to comp), denotations of the compartments are: PL plasma; ECF brainECF; DBR braindeep; LV lateral ventricle; TFV third and fourth ventricle; CM cisterna magna and SAS subarachnoid space. QECF is the flow rate of brain ECF, QCSF is the flow rate of CSF. For peripheral and plasma compartments, V volume of distribution; for brain compartments, V volume, not shown in the diagram
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC4269305&req=5

Fig4: Diagram of the SBPK model that was used to describe the intra-brain distribution in the rat. CLE is the elimination clearance from plasma, QPL–PERx is the inter-compartmental clearance between plasma and the first (x = 1) or second (x = 2) peripheral compartment. Further, for transfer clearances between compartments (CLfrom comp-to comp), denotations of the compartments are: PL plasma; ECF brainECF; DBR braindeep; LV lateral ventricle; TFV third and fourth ventricle; CM cisterna magna and SAS subarachnoid space. QECF is the flow rate of brain ECF, QCSF is the flow rate of CSF. For peripheral and plasma compartments, V volume of distribution; for brain compartments, V volume, not shown in the diagram
Mentions: The final SBPK model is shown in Fig. 4. The differential equations of this model can be found in the appendix. The final estimation of the PK parameters is summarized in Table 4. Here, the parameters are the same as for Table 3, with the addition of the following: CLPL–TFV is the clearance from plasma to CSFTFV, CLTFV–PL is the clearance from CSFTFV to plasma, QECF is the flow rate of brain ECF, QCSF is the flow rate of CSF, VTFV is the volume of the third and fourth ventricle combined and VSAS is the volume of the subarachnoid space.Fig. 4

Bottom Line: It is concluded that in parallel obtained data on unbound brainECF, CSF and plasma concentrations, under dynamic conditions, is a complex but most valid approach to reveal the mechanisms underlying the relationship between brainECF and CSF concentrations.This relationship is significantly influenced by activity of P-gp.Therefore, information on functionality of P-gp is required for the prediction of human brain target site concentrations of P-gp substrates on the basis of human CSF concentrations.

View Article: PubMed Central - PubMed

Affiliation: Department of Pharmacology, Leiden/Amsterdam Center for Drug Research, Einsteinweg 55, 2333 CC, Leiden, The Netherlands.

ABSTRACT
In the development of central nervous system (CNS)-targeted drugs, the prediction of human CNS target exposure is a big challenge. Cerebrospinal fluid (CSF) concentrations have often been suggested as a 'good enough' surrogate for brain extracellular fluid (brainECF, brain target site) concentrations in humans. However, brain anatomy and physiology indicates prudence. We have applied a multiple microdialysis probe approach in rats, for continuous measurement and direct comparison of quinidine kinetics in brainECF, CSF, and plasma. The data obtained indicated important differences between brainECF and CSF kinetics, with brainECF kinetics being most sensitive to P-gp inhibition. To describe the data we developed a systems-based pharmacokinetic model. Our findings indicated that: (1) brainECF- and CSF-to-unbound plasma AUC0-360 ratios were all over 100 %; (2) P-gp also restricts brain intracellular exposure; (3) a direct transport route of quinidine from plasma to brain cells exists; (4) P-gp-mediated efflux of quinidine at the blood-brain barrier seems to result of combined efflux enhancement and influx hindrance; (5) P-gp at the blood-CSF barrier either functions as an efflux transporter or is not functioning at all. It is concluded that in parallel obtained data on unbound brainECF, CSF and plasma concentrations, under dynamic conditions, is a complex but most valid approach to reveal the mechanisms underlying the relationship between brainECF and CSF concentrations. This relationship is significantly influenced by activity of P-gp. Therefore, information on functionality of P-gp is required for the prediction of human brain target site concentrations of P-gp substrates on the basis of human CSF concentrations.

Show MeSH
Related in: MedlinePlus