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Physicochemical Selectivity of the BBB Microenvironment Governing Passive Diffusion—Matching with a Porcine Brain Lipid Extract Artificial Membrane Permeability Model

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ABSTRACT

Purpose

To mimic the physicochemical selectivity of the blood-brain barrier (BBB) and to predict its passive permeability using a PAMPA model based on porcine brain lipid extract (PBLE 10%w/v in alkane).

Methods

Three PAMPA (BD pre-coated and PBLE with 2 different lipid volumes) models were tested with 108 drugs. Abraham solvation descriptors were used to interpret the in vitro-in vivo correlation with 282 in situ brain perfusion measurements, spanning over 5 orders of magnitude. An in combo PAMPA model was developed from combining measured PAMPA permeability with one H-bond descriptor.

Results

The in combo PAMPA predicted 93% of the variance of 197 largely efflux-inhibited in situ permeability training set. The model was cross-validated by the “leave-many-out” procedure, with q2 = 0.92 ± 0.03. The PAMPA models indicated the presence of paramembrane water channels. Only the PBLE-based PAMPA-BBB model with sufficient lipid to fill all the internal pore space of the filter showed a wide dynamic range window, selectivity coefficient near 1, and was suitable for predicting BBB permeability.

Conclusion

BBB permeability can be predicted by in combo PAMPA. Its speed and substantially lower cost, compared to in vivo measurements, make it an attractive first-pass screening method for BBB passive permeability.

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Abbreviations

(ε/δ)2 :

porosity of paramembrane aqueous pores divided by the length of the water-filled channels in thin PAMPA-BBB membranes (δ ~0.01 cm)

ABL:

aqueous boundary layer—thin stagnant layer adjacent to the surface of a membrane

BLM:

bilayer lipid membrane, unilamellar barrier formed from egg lecithin

Daq :

aqueous diffusivity (cm2·s−1)

DRW:

dynamic range window: DRW = log PABL-log Ppara

hABL :

ABL thickness (cm)

in combo :

methodology where a measured property (e.g., PAMPA permeability coefficient) is aditively “combined” with a calculated (in silico) descriptor (e.g., H-bond potential)

PABL :

ABL permeability coefficient (cm·s−1): PABL = Daq / hABL

Pe :

PAMPA effective permeability coefficient (cm·s−1)—the experimentally-determined value

Pm :

PAMPA transmembrane permeability (cm·s−1)—Pe corrected for ABL and aqueous pore diffusion effects; pH dependence follows Henderson-Hasselbalch equation

Po :

PAMPA intrinsic permeability coefficient of the uncharged-form of permeant; for ionizable compounds, Po = Pm (10 ±(pH–pKa) + 1), where ‘+’ for acids, ‘−’ for bases

Ppara :

PAMPA paramembrane permeability coefficient (cm·s−1)—diffusion of permeant via aqueous pores formed in the thin PAMPA-BBB membrane: Ppara = (ε/δ)2 Daq

P in situc :

BBB transendothelial permeability coefficient (cm·s−1) from in situ brain perfusion technique: P in situc  = (PS)/S, where S = microcapillary surface area = 100 cm2 g−1

P in situo :

BBB intrinsic permeability coefficient of the uncharged-form of permeant; for ionizable compounds, P in situo  = P in situc (10 ±(pH–pKa) + 1), ‘+’ for acids, ‘−’ for bases

PAMPA-BBB:

parallel artificial membrane permeability assay, based on PBLE formulation

PBLE:

porcine brain lipid extract

PS:

capillary permeability-surface area product (mL·s−1·g−1), determined from the uptake rate constant (Kin) using Crone-Renkin equation: Kin = Fpf ( 1–e –PS/Fpf ), where Fpf is the regional cerebral flow of perfusion fluid (mL·s−1·g−1)

SC:

selectivity coefficient; slope in the log-log in vitro—in vivo correlation plot

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ACKNOWLEDGEMENTS

Part of this work was supported by Grant Number R44MH75211 from the National Institutes of Health (to pION). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institute of Mental Health or the National Institutes of Health.

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    Oksana Tsinman, Konstantin Tsinman, Na Sun & Alex Avdeef

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Correspondence to Alex Avdeef.

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The current article is contribution number 30 in the Drug Absorption in vitro Model series from pION. Ref. 28 is part 29 in the series.

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Tsinman, O., Tsinman, K., Sun, N. et al. Physicochemical Selectivity of the BBB Microenvironment Governing Passive Diffusion—Matching with a Porcine Brain Lipid Extract Artificial Membrane Permeability Model. Pharm Res 28, 337–363 (2011). https://doi.org/10.1007/s11095-010-0280-x

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