P-glycoprotein deficient mouse in situ blood-brain barrier permeability and its prediction using an in combo PAMPA model

Evaluation of the Ability of PAMPA Membranes to Emulate Biological Processes through the Abraham Solvation Parameter Model

Two parallel artificial membrane permeability assay (PAMPA) systems intended for emulating skin permeability have been characterized through the solvation parameter model of Abraham using multilinear regression analysis. The coefficients of the obtained equations have been compared to the ones already established for other PAMPA membranes using statistical tools. The results indicate that both skin membranes are similar to each other in their physicochemical properties. However, they are different from other PAMPA membranes (e.g., intestinal absorption and blood-brain PAMPAs), mainly in terms of hydrophobicity and hydrogen bonding properties. Next, all PAMPA membranes have been compared to relevant biological processes also characterized through the solvation parameter model. The results highlight that skin-PAMPA membranes are a very good choice to emulate skin permeability.

Development of artificial neural network models to predict the PAMPA effective permeability of new, orally administered drugs active against the coronavirus SARS-CoV-2

Responding to the pandemic caused by SARS-CoV-2, the scientific community intensified efforts to provide drugs effective against the virus. To strengthen these efforts, the "COVID Moonshot" project has been accepting public suggestions for computationally triaged, synthesized, and tested molecules. The project aimed to identify molecules of low molecular weight with activity against the virus, for oral treatment. The ability of a drug to cross the intestinal cell membranes and enter circulation decisively influences its bioavailability, and hence the need to optimize permeability in the early stages of drug discovery. In our present work, as a contribution to the ongoing scientific efforts, we employed artificial neural network algorithms to develop QSAR tools for modelling the PAMPA effective permeability (passive diffusion) of orally administered drugs. We identified a set of 61 features most relevant in explaining drug cell permeability and used them to develop a stacked regression ensemble model, subsequently used to predict the permeability of molecules included in datasets made available through the COVID Moonshot project. Our model was shown to be robust and may provide a promising framework for predicting the potential permeability of molecules not yet synthesized, thus guiding the process of drug design.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13721-023-00410-9.

Intracellular Binding of Terfenadine Competes with Its Access to Pancreatic ß-cell ATP-Sensitive K+ Channels and Human ether-à-go-go-Related Gene Channels

Most blockers of both hERG (human ether-à-go-go-related gene) channels and pancreatic ß-cell ATP-sensitive K⁺ (K_ATP) channels access their binding sites from the cytoplasmic side of the plasma membrane. It is unknown whether binding to intracellular components competes with binding of these substances to K⁺ channels. The whole-cell configuration of the patch-clamp technique, a laser-scanning confocal microscope, and fluorescence correlation spectroscopy (FCS) were used to study hERG channels expressed in HEK (human embryonic kidney) 293 cells and K_ATP channels from the clonal insulinoma cell line RINm5F. When applied via the pipette solution in the whole-cell configuration, terfenadine blocked both hERG and K_ATP currents with much lower potency than after application via the bath solution, which was not due to P-glycoprotein-mediated efflux of terfenadine. Such a difference was not observed with dofetilide and tolbutamide. 37-68% of hERG/EGFP (enhanced green-fluorescent protein) fusion proteins expressed in HEK 293 cells were slowly diffusible as determined by laser-scanning microscopy in the whole-cell configuration and by FCS in intact cells. Bath application of a green-fluorescent sulphonylurea derivative (Bodipy-glibenclamide) induced a diffuse fluorescence in the cytosol of RINm5F cells under whole-cell patch-clamp conditions. These observations demonstrate the presence of intracellular binding sites for hERG and K_ATP channel blockers not dialyzable by the patch-pipette solution. Intracellular binding of terfenadine was not influenced by a mutated hERG (Y652A) channel. In conclusion, substances with high lipophilicity are not freely diffusible inside the cell but steep concentration gradients might exist within the cell and in the sub-membrane space.

Comparison of the Blood-Brain Barrier Transport and Vulnerability to P-Glycoprotein-Mediated Drug-Drug Interaction of Domperidone versus Metoclopramide Assessed Using In Vitro Assay and PET Imaging

Domperidone and metoclopramide are widely prescribed antiemetic drugs with distinct neurological side effects. The impact of P-glycoprotein (P-gp)-mediated efflux at the blood−brain barrier (BBB) on brain exposure and BBB permeation was compared in vitro and in vivo using positron emission tomography (PET) imaging in rats with the radiolabeled analogs [11C]domperidone and [11C]metoclopramide. In P-gp-overexpressing cells, the IC50 of tariquidar, a potent P-gp inhibitor, was drastically different using [11C]domperidone (221 nM [198−248 nM]) or [11C]metoclopramide (4 nM [2−8 nM]) as the substrate. Complete P-gp inhibition led to a 1.8-fold higher increase in the cellular uptake of [11C]domperidone compared with [11C]metoclopramide (p < 0.0001). Brain PET imaging revealed that the baseline brain exposure (AUCbrain) of [11C]metoclopramide was 2.4-fold higher compared with [11C]domperidone (p < 0.001), consistent with a 1.8-fold higher BBB penetration (AUCbrain/AUCplasma). The maximal increase in the brain exposure (2.9-fold, p < 0.0001) and BBB penetration (2.9-fold, p < 0.0001) of [11C]metoclopramide was achieved using 8 mg/kg of tariquidar. In comparison, neither 8 nor 15 mg/kg of tariquidar increased the brain exposure of [11C]domperidone (p > 0.05). Domperidone is an avid P-gp substrate that was in vitro compared with metoclopramide. Domperidone benefits from a lower brain exposure and a limited risk for P-gp-mediated drug−drug interaction involving P-gp inhibition at the BBB.

'Stirred not Shaken!' Comparing Agitation Methods for Permeability Studies Using a Novel Type of 96-Well Sandwich-Plates

In order to achieve a high sample throughput, permeation experiments are often carried out using 96-well sandwich plates. Even though agitation is regarded as important, permeation studies in 96-well format are often carried out without agitation since orbital shaking, the most common agitation method for 96-well plates, has been reported to create difficulties (e.g., well-to-well cross-talk), and high cost and low availability limits the use of other agitation techniques (e.g., magnetic stirring). This study investigates how orbital shaking and magnetic stirring affect the apparent permeability of model compounds with different water-solubilities (methylene blue, carbamazepine, and albendazole) using a novel 96-well sandwich plate comprising a cellulose-hydrate membrane (PermeaPlain® plate). Orbital shaking was found less efficient than magnetic stirring in terms of homogeneously distributing a small volume of dye within the donor compartment. Furthermore, in terms of achieving maximum trans-barrier flux, magnetic stirring was found a more effective agitation method than orbital shaking. Obviously, with orbital shaking the medium in the bottom compartment of the sandwich plates never was mixed in-phase. The impact of insufficient mixing on permeation was found strongest with the most lipophilic compound, which correlates with literature reports that the contribution of the unstirred water layer towards the overall resistance of the barrier is most expressed in case of lipophilic drugs. Finally, it was tested how different liquid volumes in the bottom compartment of the plates affect the well-to-well cross-talk during permeation experiments under orbital shaking. This study revealed that 250-300 µL should be used in the bottom compartment of the sandwich plates to reduce well-to-well cross-talk when using orbital shaking for agitation.

Lost in modelling and simulation?

Over the past few decades, physiologically-based pharmacokinetic modelling (PBPK) has been anticipated to be a powerful tool to improve the productivity of drug discovery and development. However, recently, multiple systematic evaluation studies independently suggested that the predictive power of current oral absorption (OA) PBPK models needs significant improvement. There is some disagreement between the industry and regulators about the credibility of OA PBPK modelling. Recently, the editorial board of AMDET&DMPK has announced the policy for the articles related to PBPK modelling (Modelling and simulation ethics). In this feature article, the background of this policy is explained: (1) Requirements for scientific writing of PBPK modelling, (2) Scientific literacy for PBPK modelling, and (3) Middle-out approaches. PBPK models are a useful tool if used correctly. This article will hopefully help advance the science of OA PBPK models.

Development of an a priori computational approach for brain uptake of compounds in an insect model system

Delivery of compounds to the brain is critical for the development of effective treatment therapies of multiple central nervous system diseases. Recently a novel insect-based brain uptake model was published utilizing a locust brain ex vivo system. The goal of our study was to develop a priori, in silico cheminformatic models to describe brain uptake in this insect model, as well as evaluate the predictive ability. The machine learning program Orange® was used to evaluate several machine learning (ML) models on a published data set of 25 known drugs, with in vitro data generated by a single laboratory group to reduce inherent inter-laboratory variability. The ML models included in this study were linear regression (LR), support vector machines (SVN), k-nearest neighbor (kNN) and neural nets (NN). The quantitative structure-property relationship models were able to correlate experimental logCtot (concentration of compound in brain) and predicted brain uptake of r² > 0.5, with the descriptors log(P*MW^-0.5) and hydrogen bond donor used in LR, SVN and KNN, while log(P*MW^-0.5) and total polar surface area (TPSA) descriptors used in the NN models. Our results indicate that the locust insect model is amenable to data mining chemoinformatics and in silico model development in CNS drug discovery pipelines.

Rapid discovery of a selective butyrylcholinesterase inhibitor using structure-based virtual screening

Acetylcholinesterase inhibitors are the mainstay of Alzheimer's disease treatments, despite having only short-term symptomatic benefits and severe side effects. Selective butyrylcholinesterase inhibitors (BuChEIs) may be more effective treatments in late-stage Alzheimer's disease with fewer side effects. Virtual screening is a powerful tool for identifying potential inhibitors in large digital compound databases. This study used structure-based virtual screening combined with physicochemical filtering to screen the InterBioScreen and Maybridge databases for novel selective BuChEIs. The workflow rapidly identified 22 potential hits in silico, resulting in the discovery of a human BuChEI with low-micromolar potency in vitro (IC₅₀ 2.4 µM) and high selectivity for butyrylcholinesterase over acetylcholinesterase. The compound was a rapidly reversible BuChEI with mixed-model in vitro inhibition kinetics. The binding interactions were investigated using in silico molecular dynamics and by developing structure-activity relationships using nine analogues. The compound also displayed high permeability in an in vitro model of the blood-brain barrier.

Oxidative stress-induced activation of Abl and Src kinases rapidly induces P-glycoprotein internalization via phosphorylation of caveolin-1 on tyrosine-14, decreasing cortisol efflux at the blood-brain barrier

Exposure of the brain to high levels of glucocorticoids during ischemia-reperfusion induces neuronal cell death. Oxidative stress alters blood-brain barrier (BBB) function during ischemia-reperfusion, and so we hypothesized that it might impair P-glycoprotein (P-gp)-mediated efflux transport of glucocorticoids at the BBB. Therefore, the purpose of this study was to clarify the molecular mechanism of this putative decrease of P-gp-mediated efflux function. First, we established that H₂O₂ treatment of a human in vitro BBB model (hCMEC/D3) reduced both P-gp efflux transport activity and protein expression on the plasma membrane within 20 min. These results suggested that the rapid decrease of efflux function might be due to internalization of P-gp. Furthermore, H₂O₂ treatment markedly increased tyrosine-14-phosphorylated caveolin-1, which is involved in P-gp internalization. A brain perfusion study in rats showed that cortisol efflux at the BBB was markedly decreased by H₂O₂ administration, and inhibitors of Abl kinase and Src kinase, which phosphorylate tyrosine-14 in caveolin-1, suppressed this decrease. Overall, these findings support the idea that oxidative stress-induced activation of Abl kinase and Src kinase induces internalization of P-gp via the phosphorylation of tyrosine-14 in caveolin-1, leading to a rapid decrease of P-gp-mediated cortisol efflux at the BBB.

Practical approaches to evaluating and optimizing brain exposure in early drug discovery

Developing drugs for CNS related diseases continues to be one of the most challenging endeavors in drug discovery. This is at least in part related to the existence of the Blood Brain Barrier (BBB), a complex multicellular organization that provides selective access to required nutrients and hormones, while removing waste and restricting exposure to potential harmful toxins, pathogens, and xenobiotics. Consequently, designing and selecting molecules that can overcame this protection system are unique and critical aspects of the CNS drug discovery. Here we review modern CNS pharmacokinetic concepts and methods suitable for early drug discovery, and medicinal chemistry strategies towards molecules with optimal CNS exposure.

Design and characterization of loratadine nanosuspension prepared by ultrasonic-assisted precipitation

Nanoparticle engineering is a well-defined technique employed as a novel and effective method in drug design and delivery. It is widely used to control particle size, as well as the morphological and physicochemical properties of active pharmaceutical ingredients. Furthermore, it serves as a method of pre-dispersion preparation for various dosage form developments. Nanotechnology produces nanomaterials with enhanced properties in terms of solubility, dissolution and permeability. In this work, ultrasonic-assisted precipitation was employed to produce nanosuspensions of poorly water-soluble loratadine, using different stabilizers. The objective of our study was attempting to prepare solid nanoparticles of loratadine to be used as a possible intermediate for designing various dosage forms. The effects of the type(s) and concentration(s) of stabilizer(s) on mean particle size were assessed. Optimal process parameters required to produce homogeneous nanoparticles with particle size below 500 nm and polydispersity less than 0.3 were determined both for precipitation and ultrasonication. Pre-dispersions were evaluated for their particle size, polydispersity index and zeta potential. Freeze-drying was employed to produce dry nanoparticles. Particle size, particle size distribution and zeta potential of the dried nanoparticles were measured after reconstitution in water. Besides thermal analysis using DSC and structural analyses (XRPD and FT-IR), the morphological characteristics and dissolution behaviors were also investigated. The selected freeze-dried nanoparticles had a mean particle size range of 353-441 nm, a polydispersity index ranging between 0.167 and 0.229 and a zeta potential between -25.7 and -20.7 mV. These results suggest that material and process parameters were successfully optimized. DSC and XRPD spectra confirmed interactions between the formulation's components during freeze-drying. The solid nanoparticles showed 30-42% of cumulative release after 10 min compared to less than 1% of dissolution characterizing loratadine without pre-processing. This study demonstrates that preparing dried loratadine nanoparticles suitable for designing effective drug preparations is a feasible approach.

Improved Prediction of Blood-Brain Barrier Permeability Through Machine Learning with Combined Use of Molecular Property-Based Descriptors and Fingerprints

Blood-brain barrier (BBB) permeability of a compound determines whether the compound can effectively enter the brain. It is an essential property which must be accounted for in drug discovery with a target in the brain. Several computational methods have been used to predict the BBB permeability. In particular, support vector machine (SVM), which is a kernel-based machine learning method, has been used popularly in this field. For SVM training and prediction, the compounds are characterized by molecular descriptors. Some SVM models were based on the use of molecular property-based descriptors (including 1D, 2D, and 3D descriptors) or fragment-based descriptors (known as the fingerprints of a molecule). The selection of descriptors is critical for the performance of a SVM model. In this study, we aimed to develop a generally applicable new SVM model by combining all of the features of the molecular property-based descriptors and fingerprints to improve the accuracy for the BBB permeability prediction. The results indicate that our SVM model has improved accuracy compared to the currently available models of the BBB permeability prediction.

Fosmetpantotenate (RE-024), a phosphopantothenate replacement therapy for pantothenate kinase-associated neurodegeneration: Mechanism of action and efficacy in nonclinical models

In cells, phosphorylation of pantothenic acid to generate phosphopantothenic acid by the pantothenate kinase enzymes is the first step in coenzyme A synthesis. Pantothenate kinase 2, the isoform localized in neuronal cell mitochondria, is dysfunctional in patients with pantothenate kinase-associated neurodegeneration. Fosmetpantotenate is a phosphopantothenic acid prodrug in clinical development for treatment of pantothenate kinase-associated neurodegeneration, which aims to replenish phosphopantothenic acid in patients. Fosmetpantotenate restored coenzyme A in short-hairpin RNA pantothenate kinase 2 gene-silenced neuroblastoma cells and was permeable in a blood-brain barrier model. The rate of fosmetpantotenate metabolism in blood is species-dependent. Following up to 700 mg/kg orally, blood exposure to fosmetpantotenate was negligible in rat and mouse, but measurable in monkey. Consistent with the difference in whole blood half-life, fosmetpantotenate dosed orally was found in the brains of the monkey (striatal dialysate) but was absent in mice. Following administration of isotopically labeled-fosmetpantotenate to mice, ~40% of liver coenzyme A (after 500 mg/kg orally) and ~50% of brain coenzyme A (after 125 μg intrastriatally) originated from isotopically labeled-fosmetpantotenate. Additionally, 10-day dosing of isotopically labeled-fosmetpantotenate, 12.5 μg, intracerebroventricularly in mice led to ~30% of brain coenzyme A containing the stable isotopic labels. This work supports the hypothesis that fosmetpantotenate acts to replace reduced phosphopantothenic acid in pantothenate kinase 2-deficient tissues.

The role of non-endothelial cells on the penetration of nanoparticles through the blood brain barrier

The blood brain barrier (BBB) is a well-established cell-based membrane that circumvents the central nervous system (CNS), protecting it from harmful substances. Due to its robustness and cell integrity, it is also an outstanding opponent when it comes to the delivery of several therapeutic agents to the brain, which requires the crossing through its highly-organized structure. This regulation and cell-cell communications occur mostly between astrocytes, pericytes and endothelial cells. Therefore, alternative ways to deliver drugs to the CNS, overcoming the BBB are required, to improve the efficacy of brain target drugs. Nanoparticles emerge here as a promising drug delivery strategy, due to their ability of high drug loading and the capability to exploit specific delivery pathways that most drugs are unable to when administered freely, increasing their bioavailability in the CNS. Thus, further attempts to assess the possible influence of non-endothelial may have on the BBB translocation of nanoparticles are here revised. Furthermore, the use of macrophages and/or monocytes as nanoparticle delivery cells are also approached. Lastly, the temporarily disruption of the overall organization and normal structure of the BBB to promote the penetration of nanoparticles aimed at the CNS is described, as a synergistic path.

Rapid micellar HPLC analysis of loratadine and its major metabolite desloratadine in nano-concentration range using monolithic column and fluorometric detection: application to pharmaceuticals and biological fluids

Background

Loratadine is a commonly used selective non-sedating antihistaminic drug. Desloratadine is the active metabolite of loratadine and, in addition, a potential impurity in loratadine bulk powder stated by the United States Pharmacopeia as a related substance of loratadine. Published methods for the determination of both analytes suffer from limited throughput due to the time-consuming steps and tedious extraction procedures needed for the analysis of biological samples. Therefore, there is a strong demand to develop a simple rapid and sensitive analytical method that can detect and quantitate both analytes in pharmaceutical preparations and biological fluids without prior sample extraction steps.

Results

A highly-sensitive and time-saving micellar liquid chromatographic method is developed for the simultaneous determination of loratadine and desloratadine. The proposed method is the first analytical method for the determination of this mixture using a monolithic column with a mobile phase composed of 0.15 M sodium dodecyl sulfate, 10% n-Butanol and 0.3% triethylamine in 0.02 M phosphoric acid, adjusted to pH 3.5 and pumped at a flow rate of 1.2 mL/min. The eluted analytes are monitored with fluorescence detection at 440 nm after excitation at 280 nm. The developed method is linear over the concentration range of 20.0–200.0 ng/mL for both analytes. The method detection limits are 15.0 and 13.0 ng/mL and the limits of quantification are 20.0 and 18.0 ng/mL for loratadine and desloratadine, respectively. Validation of the developed method reveals an accuracy of higher than 97% and intra- and inter-day precisions with relative standard deviations not exceeding 2%.

Conclusions

The method can be successfully applied to the determination of both analytes in various matrices including pharmaceutical preparations, human urine, plasma and breast milk samples with a run-time of less than 5 min and without prior extraction procedures. The method is ideally suited for use in quality control laboratories. Moreover, it could be a simple time-saving alternative to the official pharmacopeial method for testing desloratadine as a potential impurity in loratadine bulk powder.Graphical abstract

Molecular determinants of blood-brain barrier permeation

The blood-brain barrier (BBB) is a microvascular unit which selectively regulates the permeability of drugs to the brain. With the rise in CNS drug targets and diseases, there is a need to be able to accurately predict a priori which compounds in a company database should be pursued for favorable properties. In this review, we will explore the different computational tools available today, as well as underpin these to the experimental methods used to determine BBB permeability. These include in vitro models and the in vivo models that yield the dataset we use to generate predictive models. Understanding of how these models were experimentally derived determines our accurate and predicted use for determining a balance between activity and BBB distribution.

A new PAMPA model proposed on the basis of a synthetic phospholipid membrane

The purpose of this work was to investigate the synthetic phospholipid dependence of permeability measured by parallel artificial membrane permeability assay (PAMPA) method. Three phospholipids with hydrophobic groups of different lengths and phosphorylcholine as the hydrophilic group were concisely synthesized. Ten model drug molecules were selected because of their distinct human fraction absorbed (%FA) values and various pK_a characteristics. In vitro drug permeation experiments were designed to determine the effect of the incubation time (4–20 h), pH gradient (4.6–9.32) and carbon chain length (8, 10, 12) on the drug permeability through the synthetic phospholipid membrane in the PAMPA system. The results showed that intensive and significant synthetic phospholipids dependence of permeability influenced by the length of lipid’s hydrophobic carbon chain. The effective permeability constant (P_e) of each drug increased rapidly with time, then decreased slightly after reaching the maximum; the pH gradient changed the drug permeability according to the pH-partition hypothesis for drugs with diverse pK_a values; and longer hydrophobic chains in the synthetic phospholipid membrane improved the drug permeability, as observed for all test drugs at almost all incubation time points. This newly proposed PAMPA model considered the synthetic phospholipid membrane and showed good P_e-%FA correlation for the passive transport of drugs, making it a helpful supplementary method for PAMPA systems.

In vitro porcine blood-brain barrier model for permeability studies: pCEL-X software pKa(FLUX) method for aqueous boundary layer correction and detailed data analysis

In vitro blood-brain barrier (BBB) models from primary brain endothelial cells can closely resemble the in vivo BBB, offering valuable models to assay BBB functions and to screen potential central nervous system drugs. We have recently developed an in vitro BBB model using primary porcine brain endothelial cells. The model shows expression of tight junction proteins and high transendothelial electrical resistance, evidence for a restrictive paracellular pathway. Validation studies using small drug-like compounds demonstrated functional uptake and efflux transporters, showing the suitability of the model to assay drug permeability. However, one limitation of in vitro model permeability measurement is the presence of the aqueous boundary layer (ABL) resulting from inefficient stirring during the permeability assay. The ABL can be a rate-limiting step in permeation, particularly for lipophilic compounds, causing underestimation of the permeability. If the ABL effect is ignored, the permeability measured in vitro will not reflect the permeability in vivo. To address the issue, we explored the combination of in vitro permeability measurement using our porcine model with the pKa(FLUX) method in pCEL-X software to correct for the ABL effect and allow a detailed analysis of in vitro (transendothelial) permeability data, Papp. Published Papp using porcine models generated by our group and other groups are also analyzed. From the Papp, intrinsic transcellular permeability (P0) is derived by simultaneous refinement using a weighted nonlinear regression, taking into account permeability through the ABL, paracellular permeability and filter restrictions on permeation. The in vitro P0 derived for 22 compounds (35 measurements) showed good correlation with P0 derived from in situ brain perfusion data (r(2)=0.61). The analysis also gave evidence for carrier-mediated uptake of naloxone, propranolol and vinblastine. The combination of the in vitro porcine model and the software analysis provides a useful tool to better predict BBB permeability in vivo and gain better mechanistic information about BBB permeation.

Challenges of using in vitro data for modeling P-glycoprotein efflux in the blood-brain barrier

The efficacy of central nervous system (CNS) drugs may be limited by their poor ability to cross the bloodbrain barrier (BBB). Transporters, such as p-glycoprotein, may affect the distribution of many drugs into the CNS in conjunction with the restricted paracellular pathway of the BBB. It is therefore important to gain information on unbound drug concentrations in the brain in drug development to ensure sufficient drug exposure from plasma at the target site in the CNS. In vitro methods are routinely used in drug development to study passive permeability and p-glycoprotein efflux of new drugs. This review discusses the challenges in the use of in vitro data as input parameters in physiologically based pharmacokinetic (PBPK) models of CNS drug disposition of p-glycoprotein substrates. Experience with quinidine demonstrates the variability in in vitro parameters of passive permeability and active pglycoprotein efflux. Further work is needed to generate parameter values that are independent of the model and assay. This is a prerequisite for reliable predictions of drug concentrations in the brain in vivo.

cIEF for rapid pKa determination of small molecules: a proof of concept

A capillary isoelectric focusing (cIEF) method was developed for the determination of the ionization constants (pKa) of small molecules. Two approaches used to decrease the electroosmotic flow (EOF) were compared: (i) a hydroxypropylcellulose (HPC) coated capillary in aqueous medium and (ii) the addition of glycerol to act as a viscosifying agent. The cIEF method with the glycerol medium was selected, and the ionization constants of 22 basic and 21 acidic compounds, including 15 pharmaceutical drugs, were determined, resulting in pKa values from 3.5 to 7.4 and 6.4 to 9.3, respectively. cIEF offers an interesting alternative to other techniques for pKa determination with low sample consumption, high throughput and low cost.

The grasshopper: a novel model for assessing vertebrate brain uptake

The aim of the present study was to develop a blood-brain barrier (BBB) permeability model that is applicable in the drug discovery phase. The BBB ensures proper neural function, but it restricts many drugs from entering the brain, and this complicates the development of new drugs against central nervous system diseases. Many in vitro models have been developed to predict BBB permeability, but the permeability characteristics of the human BBB are notoriously complex and hard to predict. Consequently, one single suitable BBB permeability screening model, which is generally applicable in the early drug discovery phase, does not yet exist. A new refined ex vivo insect-based BBB screening model that uses an intact, viable whole brain under controlled in vitro-like exposure conditions is presented. This model uses intact brains from desert locusts, which are placed in a well containing the compound solubilized in an insect buffer. After a limited time, the brain is removed and the compound concentration in the brain is measured by conventional liquid chromatography-mass spectrometry. The data presented here include 25 known drugs, and the data show that the ex vivo insect model can be used to measure the brain uptake over the hemolymph-brain barrier of drugs and that the brain uptake shows linear correlation with in situ perfusion data obtained in vertebrates. Moreover, this study shows that the insect ex vivo model is able to identify P-glycoprotein (Pgp) substrates, and the model allows differentiation between low-permeability compounds and compounds that are Pgp substrates.

Blood-brain barrier structure and function and the challenges for CNS drug delivery

The neurons of the central nervous system (CNS) require precise control of their bathing microenvironment for optimal function, and an important element in this control is the blood-brain barrier (BBB). The BBB is formed by the endothelial cells lining the brain microvessels, under the inductive influence of neighbouring cell types within the 'neurovascular unit' (NVU) including astrocytes and pericytes. The endothelium forms the major interface between the blood and the CNS, and by a combination of low passive permeability and presence of specific transport systems, enzymes and receptors regulates molecular and cellular traffic across the barrier layer. A number of methods and models are available for examining BBB permeation in vivo and in vitro, and can give valuable information on the mechanisms by which therapeutic agents and constructs permeate, ways to optimize permeation, and implications for drug discovery, delivery and toxicity. For treating lysosomal storage diseases (LSDs), models can be included that mimic aspects of the disease, including genetically-modified animals, and in vitro models can be used to examine the effects of cells of the NVU on the BBB under pathological conditions. For testing CNS drug delivery, several in vitro models now provide reliable prediction of penetration of drugs including large molecules and artificial constructs with promising potential in treating LSDs. For many of these diseases it is still not clear how best to deliver appropriate drugs to the CNS, and a concerted approach using a variety of models and methods can give critical insights and indicate practical solutions.

Predicting efflux ratios and blood-brain barrier penetration from chemical structure: combining passive permeability with active efflux by P-glycoprotein

In order to reach their pharmacologic targets, successful central nervous system (CNS) drug candidates have to cross a complex protective barrier separating brain from the blood. Being able to predict a priori which molecules can successfully penetrate this barrier could be of significant value in CNS drug discovery. Herein we report a new computational approach that combines two mechanism-based models, for passive permeation and for active efflux by P-glycoprotein, to provide insight into the multiparameter optimization problem of designing small molecules able to access the CNS. Our results indicate that this approach is capable of distinguishing compounds with high/low efflux ratios as well as CNS+/CNS- compounds and provides advantage over estimating P-glycoprotein efflux or passive permeability alone when trying to predict these emergent properties. We also demonstrate that this method could be useful for rank-ordering chemically similar compounds and that it can provide detailed mechanistic insight into the relationship between chemical structure and efflux ratios and/or CNS penetration, offering guidance as to how compounds could be modified to improve their access into the brain.

Improving the prediction of drug disposition in the brain

INTRODUCTION

Ability to cross the blood-brain barrier is one of the key ADME characteristics of all drug candidates regardless of their target location in the body. While good brain penetration is essential for CNS drugs, it may lead to serious side effects in case of peripherally-targeted molecules. Despite a high demand of computational methods for estimating brain transport early in drug discovery, achieving good prediction accuracy still remains a challenging task.

AREAS COVERED

This article reviews various measures employed to quantify brain delivery and recent advances in QSAR approaches for predicting these properties from the compound's structure. Additionally, the authors discuss the classification models attempting to distinguish between permeable and impermeable chemicals.

EXPERT OPINION

Recent research in the field of brain penetration modeling showed an increasing understanding of the processes involved in drug disposition, although most models of brain/plasma partitioning still rely on purely statistical considerations. Preferably, new models should incorporate mechanistic knowledge since it is the prerequisite for guiding drug design efforts in the desired direction. To increase the efficiency of computational tools, a broader view is necessary, involving rate and extent of brain penetration, as well as plasma and brain tissue binding strength, instead of relying on any single property.

Synthesis and profiling of a diverse collection of azetidine-based scaffolds for the development of CNS-focused lead-like libraries

The synthesis and diversification of a densely functionalized azetidine ring system to gain access to a wide variety of fused, bridged, and spirocyclic ring systems is described. The in vitro physicochemical and pharmacokinetic properties of representative library members are measured in order to evaluate the use of these scaffolds for the generation of lead-like molecules to be used in targeting the central nervous system. The solid-phase synthesis of a 1976-membered library of spirocyclic azetidines is also described.

Computational prediction of blood-brain barrier permeability using decision tree induction

Predicting blood-brain barrier (BBB) permeability is essential to drug development, as a molecule cannot exhibit pharmacological activity within the brain parenchyma without first transiting this barrier. Understanding the process of permeation, however, is complicated by a combination of both limited passive diffusion and active transport. Our aim here was to establish predictive models for BBB drug permeation that include both active and passive transport. A database of 153 compounds was compiled using in vivo surface permeability product (logPS) values in rats as a quantitative parameter for BBB permeability. The open source Chemical Development Kit (CDK) was used to calculate physico-chemical properties and descriptors. Predictive computational models were implemented by machine learning paradigms (decision tree induction) on both descriptor sets. Models with a corrected classification rate (CCR) of 90% were established. Mechanistic insight into BBB transport was provided by an Ant Colony Optimization (ACO)-based binary classifier analysis to identify the most predictive chemical substructures. Decision trees revealed descriptors of lipophilicity (aLogP) and charge (polar surface area), which were also previously described in models of passive diffusion. However, measures of molecular geometry and connectivity were found to be related to an active drug transport component.

Brainpeps: the blood-brain barrier peptide database

Peptides are able to cross the blood-brain barrier (BBB) through various mechanisms, opening new diagnostic and therapeutic avenues. However, their BBB transport data are scattered in the literature over different disciplines, using different methodologies reporting different influx or efflux aspects. Therefore, a comprehensive BBB peptide database (Brainpeps) was constructed to collect the BBB data available in the literature. Brainpeps currently contains BBB transport information with positive as well as negative results. The database is a useful tool to prioritize peptide choices for evaluating different BBB responses or studying quantitative structure-property (BBB behaviour) relationships of peptides. Because a multitude of methods have been used to assess the BBB behaviour of compounds, we classified these methods and their responses. Moreover, the relationships between the different BBB transport methods have been clarified and visualized.

In vitro blood-brain barrier models: current and perspective technologies

Even in the 21st century, studies aimed at characterizing the pathological paradigms associated with the development and progression of central nervous system diseases are primarily performed in laboratory animals. However, limited translational significance, high cost, and labor to develop the appropriate model (e.g., transgenic or inbred strains) have favored parallel in vitro approaches. In vitro models are of particular interest for cerebrovascular studies of the blood-brain barrier (BBB), which plays a critical role in maintaining the brain homeostasis and neuronal functions. Because the BBB dynamically responds to many events associated with rheological and systemic impairments (e.g., hypoperfusion), including the exposure of potentially harmful xenobiotics, the development of more sophisticated artificial systems capable of replicating the vascular properties of the brain microcapillaries are becoming a major focus in basic, translational, and pharmaceutical research. In vitro BBB models are valuable and easy to use supporting tools that can precede and complement animal and human studies. In this article, we provide a detailed review and analysis of currently available in vitro BBB models ranging from static culture systems to the most advanced flow-based and three-dimensional coculture apparatus. We also discuss recent and perspective developments in this ever expanding research field.

Relationship between P-glycoprotein and second-generation antipsychotics

The membrane transport protein P-glycoprotein (P-gp) is an interesting candidate for individual differences in response to antipsychotics. To present an overview of the current knowledge of P-gp and its interaction with second-generation antipsychotics (SGAs), an internet search for all relevant English original research articles concerning P-gp and SGAs was conducted. Several SGAs are substrates for P-gp in therapeutic concentrations. These include amisulpride, aripiprazole, olanzapine, perospirone, risperidone and paliperidone. Clozapine and quetiapine are not likely to be substrates of P-gp. However, most antipsychotics act as inhibitors of P-gp, and can therefore influence plasma and brain concentrations of other substrates. No information was available for sertindole, ziprasidone or zotepine. Research in animal models demonstrated significant differences in antipsychotic brain concentration and behavior owing to both P-gp knockout and inhibition. Results in patients are less clear, as several external factors have to be accounted for. Patients with polymorphisms which decrease P-gp functionality tend to perform better in clinical settings. There is some variability in the findings concerning adverse effects, and no definitive conclusions can be drawn at this point.

Biorelevant pK(a) (37 °C) predicted from the 2D structure of the molecule and its pK(a) at 25 °C

Values of the ionization constants at 37 °C, which are scarcely reported, are more meaningful for interpreting mechanisms of cellular transport by ionizable molecules and in mechanistic dissolution studies, which are often performed at the biorelevant temperature. An equation was developed where the pK(a) values of drug-like molecules determined at 25 °C can be simply converted to values at 37 °C, without additional measurement. The differences between the values, ΔpK(a)=pK(a)³⁷-pK(a)²⁵, were linearly fitted to a function of pK(a)²⁵ and the standard entropy of ionization, ΔS°, where the latter term was approximated by the five Abraham linear free energy solvation descriptors using multiple linear regression. The Abraham descriptors (H-bond donor and acceptor strengths, dipolar solute-solvent interactions potential, the pi- and n-electrons dispersion force, and molar volume) were determined from the 2-dimensional structure of the molecules. A total of 143 mostly drug-like molecules (207 pK(a) values at 25 °C and at 37 °C) were chosen for the study. The pK(a) values of many were determined here for the first time. Included were 34 weak acids, 85 weak bases, and 24 amphoteric compounds (6 ordinary ampholytes, 18 zwitterions).

In vitro primary human and animal cell-based blood-brain barrier models as a screening tool in drug discovery

Brain penetration is characterized by its extent and rate and is influenced by drug physicochemical properties, plasma exposure, plasma and brain protein binding and BBB permeability. This raises questions related to physiology, interspecies differences and in vitro/in vivo extrapolation. We herein discuss the use of in vitro human and animal BBB model as a tool to improve CNS compound selection. These cell-based BBB models are characterized by low paracellular permeation, well-developed tight junctions and functional efflux transporters. A study of twenty drugs shows similar compound ranking between rat and human models although with a 2-fold higher permeability in rat. cLogP < 5, PSA < 120 Å, MW < 450 were confirmed as essential for CNS drugs. An in vitro/in vivo correlation in rat (R² = 0.67; P = 2 × 10⁻⁴) was highlighted when in vitro permeability and efflux were considered together with plasma exposure and free fraction. The cell-based BBB model is suitable to optimize CNS-drug selection, to study interspecies differences and then to support human brain exposure prediction.

How well can in vitro brain microcapillary endothelial cell models predict rodent in vivo blood-brain barrier permeability?

The object of the study was to improve the blood-brain barrier (BBB) permeability in vitro-invivo correlations (IVIVC) between in vitro brain microcapillary endothelial cell (BMEC) models and the well-tested rodent in situ brain perfusion technique. Porcine, bovine, rat, mouse, and human in vitro BMEC apparent permeability values, P(e), (14 studies from several laboratories: 229 P(e), 60 compounds) were analyzed by a novel biophysical model encoded in a weighted nonlinear regression procedure to determine the aqueous boundary layer (ABL) thickness and the paracellular parameters: porosity-pathlength (dual-pore model), pore radius, and water channel electrostatic potential. The refined parameters were then used to transform the P(e) values into the transendothelial permeability (P(c)) values. Porcine BMEC mono-culture models showed tight junctions comparable to those reported in several Caco-2 studies. Bovine cultures were somewhat leakier. In the human primary cultured cell and the hCMEC/D3 cell line data, IVIVC based on P(e) values has r(2) = 0.14. With transformed permeability values, r(2) = 0.58. Comparable improvements were found in the other species data. By using the in vitro transendothelial P(c) values in place of the apparent P(e) values, IVIVC can be dramatically improved.

Selective extraction of emerging contaminants from water samples by dispersive liquid-liquid microextraction using functionalized ionic liquids

Functionalized ionic liquids containing the tris(pentafluoroethyl)trifluorophosphate (FAP) anion were used as extraction solvents in dispersive liquid-liquid microextraction (DLLME) for the extraction of 14 emerging contaminants from water samples. The extraction efficiencies and selectivities were compared to those of an in situ IL DLLME method which uses an in situ metathesis reaction to exchange 1-butyl-3-methylimidazolium chloride (BMIM-Cl) to 1-butyl-3-methylimidazolium bis[(trifluoromethyl)sulfonyl]imide (BMIM-NTf(2)). Compounds containing tertiary amine functionality were extracted with high selectivity and sensitivity by the 1-(6-amino-hexyl)-1-methylpyrrolidinium tris(pentafluoroethyl)trifluorophosphate (HNH(2)MPL-FAP) IL compared to other FAP-based ILs and the BMIM-NTf(2) IL. On the other hand, polar or acidic compounds without amine groups exhibited higher enrichment factors using the BMIM-NTf(2) IL. The detection limits for the studied analytes varied from 0.1 to 55.1 μg/L using the traditional IL DLLME method with the HNH(2)MPL-FAP IL as extraction solvent, and from 0.1 to 55.8 μg/L using in situ IL DLLME method with BMIM-Cl+LiNTf(2) as extraction solvent. A 93-fold decrease in the detection limit of caffeine was observed when using the HNH(2)MPL-FAP IL compared to that obtained using in situ IL DLLME method. Real water samples including tap water and creek water were analyzed with both IL DLLME methods and yielded recoveries ranging from 91% to 110%.

A new in situ brain perfusion flow correction method for lipophilic drugs based on the pH-dependent Crone-Renkin equation

PURPOSE

To determine the flow-corrected luminal permeability, P(c), of lipophilic drugs measured by the in situ brain perfusion method under circumstances where the traditional Crone-Renkin equation (CRE) method, using diazepam as a flow marker, often fails.

METHODS

The pH-dependent rate of brain penetration of five lipophilic drugs (amitriptyline, atomoxetine, imipramine, indomethacin, maprotiline, sertraline), as well as of atenolol and antipyrine, were measured in Sprague-Dawley rats. A new pH-dependent CRE was derived and applied to remove the hydrodynamic component of effective permeability, P(e), to produce P(c) values.

RESULTS

It was shown by the analysis of the in situ data in the pH 6.5-8.5 interval for the lipophilic bases that the average vascular flow F(pf) = 0.036 mL∙g(-1)∙s(-1), centered in a "flow-limit window" (FLW) bounded by P (e) (min)  = 170 and P (e) (max)  = 776 (10(-6) cm∙s(-1) units). It was shown that the traditional CRE is expected not to work for half of the molecules in the FLW and is expected to underestimate (up to 64-fold) the other half of the molecules.

CONCLUSION

The new pH-CRE flow correction method applied to lipophilic ionizable drugs, based on the pH partition hypothesis, can overcome the limitations of the traditional CRE.

Physicochemical selectivity of the BBB microenvironment governing passive diffusion--matching with a porcine brain lipid extract artificial membrane permeability model

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 q(2) = 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.

Coexistence of passive and carrier-mediated processes in drug transport

The permeability of biological membranes is one of the most important determinants of the pharmacokinetic processes of a drug. Although it is often accepted that many drug substances are transported across biological membranes by passive transcellular diffusion, a recent hypothesis speculated that carrier-mediated mechanisms might account for the majority of membrane drug transport processes in biological systems. Based on evidence of the physicochemical characteristics and of in vitro and in vivo findings for marketed drugs, as well as results from real-life discovery and development projects, we present the view that both passive transcellular processes and carrier-mediated processes coexist and contribute to drug transport activities across biological membranes.

Evaluation of various PAMPA models to identify the most discriminating method for the prediction of BBB permeability

The Parallel Artificial Membrane Permeability Assay (PAMPA) has been successfully introduced into the pharmaceutical industry to allow useful predictions of passive oral absorption. Over the last 5 years, researchers have modified the PAMPA such that it can also evaluate passive blood-brain barrier (BBB) permeability. This paper compares the permeability of 19 structurally diverse, commercially available drugs assessed in four different PAMPA models: (1) a PAMPA-BLM (black lipid membrane) model, (2) a PAMPA-DS (Double Sink) model, (3) a PAMPA-BBB model and (4) a PAMPA-BBB-UWL (unstirred water layer) model in order to find the most discriminating method for the prediction of BBB permeability. Both the PAMPA-BBB model and the PAMPA-BLM model accurately identified compounds which pass the BBB (BBB+) and those which poorly penetrate the BBB (BBB-). For these models, BBB+ and BBB- classification ranges, in terms of permeability values, could be defined, offering the opportunity to validate the paradigm with in vivo data. The PAMPA models were subsequently applied to a set of 14 structurally diverse internal J&J candidates with known log (brain/blood concentration) (LogBB) values. Based on these LogBB values, BBB classifications were established (BBB+: LogBB0 >or=; BBB-: LogBB<0). PAMPA-BLM resulted in three false positive identifications, while PAMPA-BBB misclassified only one compound. Additionally, a Caco-2 assay was performed to determine the efflux ratio of all compounds in the test set. The false positive that occurred in both models was shown to be related to an increased efflux ratio. Both the PAMPA-BLM and the PAMPA-BBB models can be used to predict BBB permeability of compounds in combination with an assay that provides p-gp efflux data, such as the Caco-2 assay.