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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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Related in: MedlinePlus

The visual predictive check of the compartmental model. The dots represent the individual data points and the gray area represents the 95 % prediction confidence interval. The different boxes represent the plasma, brainECF, CSFLV, CSFCM and braindeep data
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Fig3: The visual predictive check of the compartmental model. The dots represent the individual data points and the gray area represents the 95 % prediction confidence interval. The different boxes represent the plasma, brainECF, CSFLV, CSFCM and braindeep data

Mentions: The final estimation of the PK parameters of the compartmental model is summarized in Table 3. The visual predictive check of the final compartmental model is given in Fig. 3. It can be seen that the compartmental model describes the data very well within the 95 % prediction interval, and also can cope with the large inter-individual variation as observed in the different brain concentrations. The goodness of fit plots of the plasma, brainECF, CSFLV, CSFCM and brainECF data with the compartmental model are available as supplemental material.Table 3


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)

The visual predictive check of the compartmental model. The dots represent the individual data points and the gray area represents the 95 % prediction confidence interval. The different boxes represent the plasma, brainECF, CSFLV, CSFCM and braindeep data
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

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

Fig3: The visual predictive check of the compartmental model. The dots represent the individual data points and the gray area represents the 95 % prediction confidence interval. The different boxes represent the plasma, brainECF, CSFLV, CSFCM and braindeep data
Mentions: The final estimation of the PK parameters of the compartmental model is summarized in Table 3. The visual predictive check of the final compartmental model is given in Fig. 3. It can be seen that the compartmental model describes the data very well within the 95 % prediction interval, and also can cope with the large inter-individual variation as observed in the different brain concentrations. The goodness of fit plots of the plasma, brainECF, CSFLV, CSFCM and brainECF data with the compartmental model are available as supplemental material.Table 3

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