Evaluation of the BBMEC model for screening the CNS permeability of drugs

Otis, Kenneth W.; Avery, Michael L.; Broward-Partin, Suzanne M.; Hansen, Dannette K.; Behlow, Herbert; Scott, Dennis O.; Thompson, Thomas N.

doi:10.1016/s1056-8719(01)00120-4

Cited by 14 publications

(10 citation statements)

References 2 publications

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“…10,11 In vivo biological approaches include microdialysis, 12,13 cerebrospinal fluid sampling, 12,14 autoradiography, 15 nuclear magnetic resonance, 16 and positron emission spectroscopy. 17 In vitro methods use isolated brain capillaries 18 and cultured cells such as bovine brain microvessel endothelial cells, 19 brain capillary endothelial cells, 20 mouse brain endothelial cells 4, 21 and Caco-2 cells. 22 Other in vitro approaches of the parallel artificial membrane permeability assay (PAMPA) 23 and the immobilized artificial membrane (IAM) chromatographicy 24,25 have been reported.…”

Section: Introductionmentioning

confidence: 99%

Rapid Screening of Blood-Brain Barrier Penetration of Drugs Using the Immobilized Artificial Membrane Phosphatidylcholine Column Chromatography

Yoon¹,

Kim²,

Shin³

et al. 2006

SLAS Discovery

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The chromatographic capacity factors (k IAM ) of 23 structurally diverse drugs were measured by the immobilized artificial membrane (IAM) phosphatidylcholine chromatography for the prediction of blood-brain barrier (BBB) penetration. The k IAM was determined using the mobile phase consisting of acetonitrile:DPBS (20:80 v/v) and corrected for the molar volume of the solutes (k IAM /MW n ). The correlation between k IAM /MW n and CNS penetration was highest when measured at pH 5.5 with the power function of n = 4. This in vitro prediction method was validated with 7 newly synthesized PDE-4 inhibitors. The relationship between in vivo plasma-to-brain concentration ratios and in vitro CNS penetration was excellent (r = 0.959). The developed in vitro prediction method may be used as a rapid screening tool for BBB penetration of drugs with passive transport mechanism, with high success, low cost, and reproducibility. (Journal of Biomolecular

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Section: Introductionmentioning

confidence: 99%

Rapid Screening of Blood-Brain Barrier Penetration of Drugs Using the Immobilized Artificial Membrane Phosphatidylcholine Column Chromatography

Yoon¹,

Kim²,

Shin³

et al. 2006

SLAS Discovery

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“…In order to adapt this model assay to a high throughput method, the experimental design of the transport study has been simplified by calculating only the percentage of transport after a fixed period of time (60 min), known as %T 3600 , instead of calculating the P app . It should be noted that the %T 3600 shows a good linearity with the P app values [50]. This simplification allows the reduction of the total number of samples to be analysed by HPLC and also eliminates the need for the manipulation of plates during the study.…”

Section: Bbec Assaymentioning

confidence: 92%

“…In order to adapt this model assay to a high throughput method, the percentage of transport after 60 min, (%T 3600 ), was calculated instead of the P app values. This parameter shows a good linearity with the P app values [50]. In order to normalize the values, the %T 3600 of each compound was referred to the %T 3600 of propranolol.…”

Section: Bbec Assaymentioning

confidence: 99%

Evolutionary combinatorial chemistry, a novel tool for SAR studies on peptide transport across the blood-brain barrier. Part 2. Design, synthesis and evaluation of a first generation of peptides

et al. 2005

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The use of high-throughput methods in drug discovery allows the generation and testing of a large number of compounds, but at the price of providing redundant information. Evolutionary combinatorial chemistry combines the selection and synthesis of biologically active compounds with artificial intelligence optimization methods, such as genetic algorithms (GA). Drug candidates for the treatment of central nervous system (CNS) disorders must overcome the blood-brain barrier (BBB). This paper reports a new genetic algorithm that searches for the optimal physicochemical properties for peptide transport across the blood-brain barrier. A first generation of peptides has been generated and synthesized. Due to the high content of N-methyl amino acids present in most of these peptides, their syntheses were especially challenging due to over-incorporations, deletions and DKP formations. Distinct fragmentation patterns during peptide cleavage have been identified. The first generation of peptides has been studied by evaluation techniques such as immobilized artificial membrane chromatography (IAMC), a cell-based assay, log Poctanol/water calculations, etc. Finally, a second generation has been proposed.

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“…Each of them is characterised by different selective permeability to different compounds and by different transendothelial electrical resistance (TEER) values [35]. Additionally, a critical feature in any model system is the ability to discriminate between a compound of high permeability through the lipid bilayer and a compound that uses paracellular pathways (sucrose, mannitol) [36]. The most commonly used in vitro model is the so called Transwell system [37].…”

Section: In Vitro Models Based On Endothelial Cell Culturingmentioning

confidence: 99%

In Silico Prediction Models for Blood-Brain Barrier Permeation

Ecker

Noe

2004

CMC

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The ability to permeate across the blood brain barrier (BBB) is essential for drugs acting on the central nervous system (CNS). Thus, for speeding up the drug discovery process in the CNS-area, it is of great importance to develop systems that allow rapid and inexpensive screening of the BBB-permeability properties of novel lead compounds or at least small subsets of combinatorial CNS-libraries. In this field, in silico prediction methods gain increasing importance. Starting with simple regression models based on calculation of lipophilicity and polar surface area, the field developed via PLS methods to grid based approaches (e.g. VolSurf). Additionally, the use of artificial neural networks gain increasing importance. However, permeation through the BBB is also influenced by active transport systems. For nutrients and endogenous compounds, such as amino acids, monocarboxylic acids, amines, hexoses, thyroid hormones, purine bases and nucleosides, several transport systems regulating the entry of the respective compound classes into the brain have been identified. The other way round there is striking evidence that expression of active efflux pumps like the multidrug transporter P-glycoprotein (P-gp) on the luminal membrane of the brain capillary endothelial cells accounts for poor BBB permeability of certain drugs. Undoubtedly, P-gp is an important impediment for the entry of hydrophobic drugs into the brain. Thus, proper prediction models should also take into account the active transport phenomena.

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Evaluation of the BBMEC model for screening the CNS permeability of drugs

Cited by 14 publications

References 2 publications

Rapid Screening of Blood-Brain Barrier Penetration of Drugs Using the Immobilized Artificial Membrane Phosphatidylcholine Column Chromatography

Rapid Screening of Blood-Brain Barrier Penetration of Drugs Using the Immobilized Artificial Membrane Phosphatidylcholine Column Chromatography

Evolutionary combinatorial chemistry, a novel tool for SAR studies on peptide transport across the blood-brain barrier. Part 2. Design, synthesis and evaluation of a first generation of peptides

In Silico Prediction Models for Blood-Brain Barrier Permeation

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