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Pharmacokinetic-pharmacodynamic modeling of the D₂ and 5-HT (2A) receptor occupancy of risperidone and paliperidone in rats.

Kozielska M, Johnson M, Pilla Reddy V, Vermeulen A, Li C, Grimwood S, de Greef R, Groothuis GM, Danhof M, Proost JH - Pharm. Res. (2012)

Bottom Line: A two-compartment model best fit to the plasma PK profile of risperidone and paliperidone.This may stem from their high affinity for D₂ and 5-HT(2A) receptors.Receptor affinities and brain-to-plasma ratios may need to be considered before choosing the best PK-PD model for centrally active drugs.

View Article: PubMed Central - PubMed

Affiliation: Division of Pharmacokinetics, Toxicology and Targeting, University of Groningen, P.O. Box 196, 9700 AD, Groningen, The Netherlands.

ABSTRACT

Purpose: A pharmacokinetic-pharmacodynamic (PK-PD) model was developed to describe the time course of brain concentration and dopamine D₂ and serotonin 5-HT(2A) receptor occupancy (RO) of the atypical antipsychotic drugs risperidone and paliperidone in rats.

Methods: A population approach was utilized to describe the PK-PD of risperidone and paliperidone using plasma and brain concentrations and D₂ and 5-HT(2A) RO data. A previously published physiology- and mechanism-based (PBPKPD) model describing brain concentrations and D₂ receptor binding in the striatum was expanded to include metabolite kinetics, active efflux from brain, and binding to 5-HT(2A) receptors in the frontal cortex.

Results: A two-compartment model best fit to the plasma PK profile of risperidone and paliperidone. The expanded PBPKPD model described brain concentrations and D₂ and 5-HT(2A) RO well. Inclusion of binding to 5-HT(2A) receptors was necessary to describe observed brain-to-plasma ratios accurately. Simulations showed that receptor affinity strongly influences brain-to-plasma ratio pattern.

Conclusion: Binding to both D₂ and 5-HT(2A) receptors influences brain distribution of risperidone and paliperidone. This may stem from their high affinity for D₂ and 5-HT(2A) receptors. Receptor affinities and brain-to-plasma ratios may need to be considered before choosing the best PK-PD model for centrally active drugs.

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(a) A schematic representation of the PK-PD model. The plasma PK has been omitted (see Fig. 1) and brain kinetics and receptor binding have been presented here for one drug only because of the complexity of the model. The same model structure applies for RIS and PALI. (b) Representation of the competitive binding to the same receptors by RIS and PALI. Measured RO is the sum of occupancies obtained by both drugs. Here only binding to D2 receptors is shown. The same principle applies for 5-HT2A receptors. [D2] - concentration of free D2 receptors, [R] – unbound concentration of RIS, [D2R] - concentration of D2 receptor complex with RIS, [P] – unbound concentration of PALI, [D2P] - concentration of D2 receptor complex with PALI. D2 receptor occupancy (RO) is the sum of RO exerted by both drugs.
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Fig2: (a) A schematic representation of the PK-PD model. The plasma PK has been omitted (see Fig. 1) and brain kinetics and receptor binding have been presented here for one drug only because of the complexity of the model. The same model structure applies for RIS and PALI. (b) Representation of the competitive binding to the same receptors by RIS and PALI. Measured RO is the sum of occupancies obtained by both drugs. Here only binding to D2 receptors is shown. The same principle applies for 5-HT2A receptors. [D2] - concentration of free D2 receptors, [R] – unbound concentration of RIS, [D2R] - concentration of D2 receptor complex with RIS, [P] – unbound concentration of PALI, [D2P] - concentration of D2 receptor complex with PALI. D2 receptor occupancy (RO) is the sum of RO exerted by both drugs.

Mentions: The hybrid physiology-based PK-PD model consists of four compartments in brain: vascular, extra-vascular, striatum free and striatum bound compartment (Fig. 2). Volumes of these compartments were fixed to physiological values: 0.00024, 0.00656, 0.0002 L/kg for vascular, total extra-vascular and striatum, respectively (17,18). Clearance between plasma and vascular compartment (CLbv) was assumed to be equal to cerebral blood flow in rats, which is 0.312 L/h/kg (17), for both RIS and PALI. In the model, transport of RIS and PALI between the vascular and extra-vascular compartment across the blood-brain barrier (BBB) was governed by two processes: passive diffusion and active efflux. Separate values of passive clearance (CLbev) and active efflux clearance (CLefflux) were estimated for RIS and PALI when possible. We checked whether linear or saturable efflux processes described the data best. Only unbound drug could cross the brain-blood barrier (BBB). Plasma protein binding is constant over wide range of concentrations in humans (19). We assumed that the same is true for rats and plasma and brain fraction unbound were fixed to literature values: fuplasma-RIS = 0.0798, fubrain-RIS = 0.0699, fuplasma-PALI = 0.129, fubrain-PALI = 0.0755 (20).Fig. 2


Pharmacokinetic-pharmacodynamic modeling of the D₂ and 5-HT (2A) receptor occupancy of risperidone and paliperidone in rats.

Kozielska M, Johnson M, Pilla Reddy V, Vermeulen A, Li C, Grimwood S, de Greef R, Groothuis GM, Danhof M, Proost JH - Pharm. Res. (2012)

(a) A schematic representation of the PK-PD model. The plasma PK has been omitted (see Fig. 1) and brain kinetics and receptor binding have been presented here for one drug only because of the complexity of the model. The same model structure applies for RIS and PALI. (b) Representation of the competitive binding to the same receptors by RIS and PALI. Measured RO is the sum of occupancies obtained by both drugs. Here only binding to D2 receptors is shown. The same principle applies for 5-HT2A receptors. [D2] - concentration of free D2 receptors, [R] – unbound concentration of RIS, [D2R] - concentration of D2 receptor complex with RIS, [P] – unbound concentration of PALI, [D2P] - concentration of D2 receptor complex with PALI. D2 receptor occupancy (RO) is the sum of RO exerted by both drugs.
© Copyright Policy
Related In: Results  -  Collection

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getmorefigures.php?uid=PMC3369128&req=5

Fig2: (a) A schematic representation of the PK-PD model. The plasma PK has been omitted (see Fig. 1) and brain kinetics and receptor binding have been presented here for one drug only because of the complexity of the model. The same model structure applies for RIS and PALI. (b) Representation of the competitive binding to the same receptors by RIS and PALI. Measured RO is the sum of occupancies obtained by both drugs. Here only binding to D2 receptors is shown. The same principle applies for 5-HT2A receptors. [D2] - concentration of free D2 receptors, [R] – unbound concentration of RIS, [D2R] - concentration of D2 receptor complex with RIS, [P] – unbound concentration of PALI, [D2P] - concentration of D2 receptor complex with PALI. D2 receptor occupancy (RO) is the sum of RO exerted by both drugs.
Mentions: The hybrid physiology-based PK-PD model consists of four compartments in brain: vascular, extra-vascular, striatum free and striatum bound compartment (Fig. 2). Volumes of these compartments were fixed to physiological values: 0.00024, 0.00656, 0.0002 L/kg for vascular, total extra-vascular and striatum, respectively (17,18). Clearance between plasma and vascular compartment (CLbv) was assumed to be equal to cerebral blood flow in rats, which is 0.312 L/h/kg (17), for both RIS and PALI. In the model, transport of RIS and PALI between the vascular and extra-vascular compartment across the blood-brain barrier (BBB) was governed by two processes: passive diffusion and active efflux. Separate values of passive clearance (CLbev) and active efflux clearance (CLefflux) were estimated for RIS and PALI when possible. We checked whether linear or saturable efflux processes described the data best. Only unbound drug could cross the brain-blood barrier (BBB). Plasma protein binding is constant over wide range of concentrations in humans (19). We assumed that the same is true for rats and plasma and brain fraction unbound were fixed to literature values: fuplasma-RIS = 0.0798, fubrain-RIS = 0.0699, fuplasma-PALI = 0.129, fubrain-PALI = 0.0755 (20).Fig. 2

Bottom Line: A two-compartment model best fit to the plasma PK profile of risperidone and paliperidone.This may stem from their high affinity for D₂ and 5-HT(2A) receptors.Receptor affinities and brain-to-plasma ratios may need to be considered before choosing the best PK-PD model for centrally active drugs.

View Article: PubMed Central - PubMed

Affiliation: Division of Pharmacokinetics, Toxicology and Targeting, University of Groningen, P.O. Box 196, 9700 AD, Groningen, The Netherlands.

ABSTRACT

Purpose: A pharmacokinetic-pharmacodynamic (PK-PD) model was developed to describe the time course of brain concentration and dopamine D₂ and serotonin 5-HT(2A) receptor occupancy (RO) of the atypical antipsychotic drugs risperidone and paliperidone in rats.

Methods: A population approach was utilized to describe the PK-PD of risperidone and paliperidone using plasma and brain concentrations and D₂ and 5-HT(2A) RO data. A previously published physiology- and mechanism-based (PBPKPD) model describing brain concentrations and D₂ receptor binding in the striatum was expanded to include metabolite kinetics, active efflux from brain, and binding to 5-HT(2A) receptors in the frontal cortex.

Results: A two-compartment model best fit to the plasma PK profile of risperidone and paliperidone. The expanded PBPKPD model described brain concentrations and D₂ and 5-HT(2A) RO well. Inclusion of binding to 5-HT(2A) receptors was necessary to describe observed brain-to-plasma ratios accurately. Simulations showed that receptor affinity strongly influences brain-to-plasma ratio pattern.

Conclusion: Binding to both D₂ and 5-HT(2A) receptors influences brain distribution of risperidone and paliperidone. This may stem from their high affinity for D₂ and 5-HT(2A) receptors. Receptor affinities and brain-to-plasma ratios may need to be considered before choosing the best PK-PD model for centrally active drugs.

Show MeSH