How to measure drug transport across the blood-brain barrier

Quantitative PET imaging and modeling of molecular blood-brain barrier permeability

Blood-brain barrier (BBB) disruption is involved in the pathogenesis and progression of many neurological and systemic diseases. Non-invasive assessment of BBB permeability in humans has mainly been performed with dynamic contrast-enhanced magnetic resonance imaging, evaluating the BBB as a structural barrier. Here, we developed a novel non-invasive positron emission tomography (PET) method in humans to measure the BBB permeability of molecular radiotracers that cross the BBB through different transport mechanisms. Our method uses high-temporal resolution dynamic imaging and kinetic modeling to jointly estimate cerebral blood flow and tracer-specific BBB transport rate from a single dynamic PET scan and measure the molecular permeability-surface area (PS) product of the radiotracer. We show our method can resolve BBB PS across three PET radiotracers with greatly differing permeabilities, measure reductions in BBB PS of 18F-fluorodeoxyglucose (FDG) in healthy aging, and demonstrate a possible brain-body association between decreased FDG BBB PS in patients with metabolic dysfunction-associated steatotic liver inflammation. Our method opens new directions to efficiently study the molecular permeability of the human BBB in vivo using the large catalogue of available molecular PET tracers.

Increased Permeability of the Blood-Brain Barrier in a Diabetic Mouse Model (Leprdb/db Mice)

Type 2 Diabetes Mellitus (T2DM) is linked to multiple complications, including cognitive impairment, and the prevalence of memory-related neurodegenerative diseases is higher in T2DM patients. One possible theory is the alteration of the microvascular and macrovascular environment of the blood-brain barrier (BBB). In this study, we employed different approaches, including RT-PCR, functional pharmacokinetic studies using sodium fluorescein (NaFL), and confocal microscopy, to characterize the functional and molecular integrity of the BBB in a T2DM animal model, leptin receptor-deficient mutant mice (Leprdb/db mice). As a result, VCAM-1, ICAM-1, MMP-9, and S100b (BBB-related markers) dysregulation was observed in the Leprdb/db animal model compared to littermate wild-type mice. The brain concentration of sodium fluorescein (NaFL) increased significantly in Leprdb/db untreated mice compared to insulin-treated mice. Therefore, the permeability of NaFL was higher in Leprdb/db control mice than in all remaining groups. Identifying the factors that increase the BBB in Leprdb/db mice will provide a better understanding of the BBB microvasculature and present previously undescribed findings of T2DM-related brain illnesses, filling knowledge gaps in this emerging field of research.

Concurrent Optimizations of Efficacy and Blood-Brain Barrier Permeability in New Macrocyclic LRRK2 Inhibitors for Potential Parkinson's Disease Therapeutics

The elevated activity of leucine-rich repeat kinase 2 (LRRK2) is implicated in the pathogenesis of Parkinson's disease (PD). The quest for effective LRRK2 inhibitors has been impeded by the formidable challenge of crossing the blood-brain barrier (BBB). We leveraged structure-based de novo design and developed robust three-dimensional quantitative structure-activity relationship (3D-QSAR) models to predict BBB permeability, enhancing the likelihood of the inhibitor's brain accessibility. Our strategy involved the synthesis of macrocyclic molecules by linking the two terminal nitrogen atoms of HG-10-102-01 with an alkyl chain ranging from 2 to 4 units, laying the groundwork for innovative LRRK2 inhibitor designs. Through meticulous computational and synthetic optimization of both biochemical efficacy and BBB permeability, 9 out of 14 synthesized candidates demonstrated potent low-nanomolar inhibition and significant BBB penetration. Further assessments of in vitro and in vivo effectiveness, coupled with pharmacological profiling, highlighted 8 as the promising new lead compound for PD therapeutics.

Non-animal models for blood-brain barrier permeability evaluation of drug-like compounds

Diseases related to the central nervous system (CNS) are major health concerns and have serious social and economic impacts. Developing new drugs for CNS-related disorders presents a major challenge as it actively involves delivering drugs into the CNS. Therefore, it is imperative to develop in silico methodologies to reliably identify potential lead compounds that can penetrate the blood-brain barrier (BBB) and help to thoroughly understand the role of different physicochemical properties fundamental to the BBB permeation of molecules. In this study, we have analysed the chemical space of the CNS drugs and compared it to the non-CNS-approved drugs. Additionally, we have collected a feature selection dataset from Muehlbacher et al. (J Comput Aided Mol Des 25(12):1095-1106, 2011. 10.1007/s10822-011-9478-1) and an in-house dataset. This information was utilised to design a molecular fingerprint that was used to train machine learning (ML) models. The best-performing models reported in this study achieved accuracies of 0.997 and 0.98, sensitivities of 1.0 and 0.992, specificities of 0.971 and 0.962, MCCs of 0.984 and 0.958, and ROC-AUCs of 0.997 and 0.999 on an imbalanced and a balanced dataset, respectively. They demonstrated overall good accuracies and sensitivities in the blind validation dataset. The reported models can be applied for fast and early screening drug-like molecules with BBB potential. Furthermore, the bbbPythoN package can be used by the research community to both produce the BBB-specific molecular fingerprints and employ the models mentioned earlier for BBB-permeability prediction.

Interspecies Brain PBPK Modeling Platform to Predict Passive Transport through the Blood-Brain Barrier and Assess Target Site Disposition

The high failure rate of central nervous system (CNS) drugs is partly associated with an insufficient understanding of target site exposure. Blood-brain barrier (BBB) permeability evaluation tools are needed to explore drugs' ability to access the CNS. An outstanding aspect of physiologically based pharmacokinetic (PBPK) models is the integration of knowledge on drug-specific and system-specific characteristics, allowing the identification of the relevant factors involved in target site distribution. We aimed to qualify a PBPK platform model to be used as a tool to predict CNS concentrations when significant transporter activity is absent and human data are sparse or unavailable. Data from the literature on the plasma and CNS of rats and humans regarding acetaminophen, oxycodone, lacosamide, ibuprofen, and levetiracetam were collected. Human BBB permeability values were extrapolated from rats using inter-species differences in BBB surface area. The percentage of predicted AUC and Cmax within the 1.25-fold criterion was 85% and 100% for rats and humans, respectively, with an overall GMFE of <1.25 in all cases. This work demonstrated the successful application of the PBPK platform for predicting human CNS concentrations of drugs passively crossing the BBB. Future applications include the selection of promising CNS drug candidates and the evaluation of new posologies for existing drugs.

Modeling the Blood-Brain Barrier Permeability of Potential Heterocyclic Drugs via Biomimetic IAM Chromatography Technique Combined with QSAR Methodology

Penetration through the blood-brain barrier (BBB) is desirable in the case of potential pharmaceuticals acting on the central nervous system (CNS), but is undesirable in the case of drug candidates acting on the peripheral nervous system because it may cause CNS side effects. Therefore, modeling of the permeability across the blood-brain barrier (i.e., the logarithm of the brain to blood concentration ratio, log BB) of potential pharmaceuticals should be performed as early as possible in the preclinical phase of drug development. Biomimetic chromatography with immobilized artificial membrane (IAM) and the quantitative structure-activity relationship (QSAR) methodology were successful in modeling the blood-brain barrier permeability of 126 drug candidates, whose experimentally-derived lipophilicity indices and computationally-derived molecular descriptors (such as molecular weight (MW), number of rotatable bonds (NRB), number of hydrogen bond donors (HBD), number of hydrogen bond acceptors (HBA), topological polar surface area (TPSA), and polarizability (α)) varied by class. The QSARs model established by multiple linear regression showed a positive effect of the lipophilicity (log kw, IAM) and molecular weight of the compound, and a negative effect of the number of hydrogen bond donors and acceptors, on the log BB values. The model has been cross-validated, and all statistics indicate that it is very good and has high predictive ability. The simplicity of the developed model, and its usefulness in screening studies of novel drug candidates that are able to cross the BBB by passive diffusion, are emphasized.

Practical solutions for including sex as a biological variable (SABV) in preclinical neuropsychopharmacological research

Recently, many funding agencies have released guidelines on the importance of considering sex as a biological variable (SABV) as an experimental factor, aiming to address sex differences and avoid possible sex biases to enhance the reproducibility and translational relevance of preclinical research. In neuroscience and pharmacology, the female sex is often omitted from experimental designs, with researchers generalizing male-driven outcomes to both sexes, risking a biased or limited understanding of disease mechanisms and thus potentially ineffective therapeutics. Herein, we describe key methodological aspects that should be considered when sex is factored into in vitro and in vivo experiments and provide practical knowledge for researchers to incorporate SABV into preclinical research. Both age and sex significantly influence biological and behavioral processes due to critical changes at different timepoints of development for males and females and due to hormonal fluctuations across the rodent lifespan. We show that including both sexes does not require larger sample sizes, and even if sex is included as an independent variable in the study design, a moderate increase in sample size is sufficient. Moreover, the importance of tracking hormone levels in both sexes and the differentiation between sex differences and sex-related strategy in behaviors are explained. Finally, the lack of robust data on how biological sex influences the pharmacokinetic (PK), pharmacodynamic (PD), or toxicological effects of various preclinically administered drugs to animals due to the exclusion of female animals is discussed, and methodological strategies to enhance the rigor and translational relevance of preclinical research are proposed.

Recent Studies of Artificial Intelligence on In Silico Drug Distribution Prediction

Drug distribution is an important process in pharmacokinetics because it has the potential to influence both the amount of medicine reaching the active sites and the effectiveness as well as safety of the drug. The main causes of 90% of drug failures in clinical development are lack of efficacy and uncontrolled toxicity. In recent years, several advances and promising developments in drug distribution property prediction have been achieved, especially in silico, which helped to drastically reduce the time and expense of screening undesired drug candidates. In this study, we provide comprehensive knowledge of drug distribution background, influencing factors, and artificial intelligence-based distribution property prediction models from 2019 to the present. Additionally, we gathered and analyzed public databases and datasets commonly utilized by the scientific community for distribution prediction. The distribution property prediction performance of five large ADMET prediction tools is mentioned as a benchmark for future research. On this basis, we also offer future challenges in drug distribution prediction and research directions. We hope that this review will provide researchers with helpful insight into distribution prediction, thus facilitating the development of innovative approaches for drug discovery.

The development and function of the brain barriers - an overlooked consideration for chemical toxicity

It is well known that the adult brain is protected from some infections and toxic molecules by the blood-brain and the blood-cerebrospinal fluid barriers. Contrary to the immense data collected in other fields, it is deeply entrenched in environmental toxicology that xenobiotics easily permeate the developing brain because these barriers are either absent or non-functional in the fetus and newborn. Here we review the cellular and physiological makeup of the brain barrier systems in multiple species, and discuss decades of experiments that show they possess functionality during embryogenesis. We next present case studies of two chemical classes, perfluoroalkyl substances (PFAS) and bisphenols, and discuss their potential to bypass the brain barriers. While there is evidence to suggest these pollutants may enter the developing and/or adult brain parenchyma, many studies suffer from confounding technical variables which complicates data interpretation. In the future, a more formal consideration of brain barrier biology could not only improve understanding of chemical toxicokinetics but could assist in prioritizing environmental xenobiotics for their neurotoxicity risk.

A Historical Review of Brain Drug Delivery

The history of brain drug delivery is reviewed beginning with the first demonstration, in 1914, that a drug for syphilis, salvarsan, did not enter the brain, due to the presence of a blood-brain barrier (BBB). Owing to restricted transport across the BBB, FDA-approved drugs for the CNS have been generally limited to lipid-soluble small molecules. Drugs that do not cross the BBB can be re-engineered for transport on endogenous BBB carrier-mediated transport and receptor-mediated transport systems, which were identified during the 1970s-1980s. By the 1990s, a multitude of brain drug delivery technologies emerged, including trans-cranial delivery, CSF delivery, BBB disruption, lipid carriers, prodrugs, stem cells, exosomes, nanoparticles, gene therapy, and biologics. The advantages and limitations of each of these brain drug delivery technologies are critically reviewed.

DeePred-BBB: A Blood Brain Barrier Permeability Prediction Model With Improved Accuracy

The blood-brain barrier (BBB) is a selective and semipermeable boundary that maintains homeostasis inside the central nervous system (CNS). The BBB permeability of compounds is an important consideration during CNS-acting drug development and is difficult to formulate in a succinct manner. Clinical experiments are the most accurate method of measuring BBB permeability. However, they are time taking and labor-intensive. Therefore, numerous efforts have been made to predict the BBB permeability of compounds using computational methods. However, the accuracy of BBB permeability prediction models has always been an issue. To improve the accuracy of the BBB permeability prediction, we applied deep learning and machine learning algorithms to a dataset of 3,605 diverse compounds. Each compound was encoded with 1,917 features containing 1,444 physicochemical (1D and 2D) properties, 166 molecular access system fingerprints (MACCS), and 307 substructure fingerprints. The prediction performance metrics of the developed models were compared and analyzed. The prediction accuracy of the deep neural network (DNN), one-dimensional convolutional neural network, and convolutional neural network by transfer learning was found to be 98.07, 97.44, and 97.61%, respectively. The best performing DNN-based model was selected for the development of the “DeePred-BBB” model, which can predict the BBB permeability of compounds using their simplified molecular input line entry system (SMILES) notations. It could be useful in the screening of compounds based on their BBB permeability at the preliminary stages of drug development. The DeePred-BBB is made available at https://github.com/12rajnish/DeePred-BBB.

Nanotherapeutics and the Brain

Brain disease remains a significant health, social, and economic burden with a high failure rate of translation of therapeutics to the clinic. Nanotherapeutics have represented a promising area of technology investment to improve drug bioavailability and delivery to the brain, with several successes for nanotherapeutic use for central nervous system disease that are currently in the clinic. However, renewed and continued research on the treatment of neurological disorders is critically needed. We explore the challenges of drug delivery to the brain and the ways in which nanotherapeutics can overcome these challenges. We provide a summary and overview of general design principles that can be applied to nanotherapeutics for uptake and penetration in the brain. We next highlight remaining questions that limit the translational potential of nanotherapeutics for application in the clinic. Lastly, we provide recommendations for ongoing preclinical research to improve the overall success of nanotherapeutics against neurological disease. Expected final online publication date for the Annual Review of Chemical and Biomolecular Engineering, Volume 13 is October 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Antibody-Targeted Liposomes for Enhanced Targeting of the Blood-Brain Barrier

The blood-brain barrier (BBB) hinders therapeutic delivery to the central nervous system (CNS), thereby impeding the development of therapies for brain injury and disease. Receptor-mediated transcytosis (RMT) systems are a promising way to shuttle a targeted therapeutic into the brain. Here, we developed and evaluated an RMT antibody-targeted liposomal system. A previously identified antibody, scFv46.1, that binds to the human and murine BBB and can pass through the murine BBB by transcytosis after intravenous injection was used to decorate the surface of liposomes. Using an in vitro BBB model, we demonstrated the cellular uptake of scFv46.1-modified liposomes (46.1-Lipo). Next, the biodistribution and brain uptake capacity of 46.1-targeted liposomes were assessed after intravenous administration. Our results showed that 46.1-Lipo can lead to increased brain accumulation through targeting of the brain vasculature. Initial rate pharmacokinetic experiments and biodistribution analyses indicated that 46.1-Lipo loaded with pralidoxime exhibited a 10-fold increase in brain accumulation compared with a mock-targeted liposomal group, and this increased accumulation was brain-specific. These studies indicate the potential of this 46.1-Lipo system as a synthetic vehicle for the targeted transport of therapeutic molecules into the CNS.

A Semi-Physiological Three-Compartment Model Describes Brain Uptake Clearance and Efflux of Sucrose and Mannitol after IV Injection in Awake Mice

PURPOSE

To evaluate a three-compartmental semi-physiological model for analysis of uptake clearance and efflux from brain tissue of the hydrophilic markers sucrose and mannitol, compared to non-compartmental techniques presuming unidirectional uptake.

METHODS

Stable isotope-labeled [13C]sucrose and [13C]mannitol (10 mg/kg each) were injected as IV bolus into the tail vein of awake young adult mice. Blood and brain samples were taken after different time intervals up to 8 h. Plasma and brain concentrations were quantified by UPLC-MS/MS. Brain uptake clearance (Kin) was analyzed using either the single-time point analysis, the multiple time point graphical method, or by fitting the parameters of a three-compartmental model that allows for symmetrical exchange across the blood-brain barrier and an additional brain efflux clearance.

RESULTS

The three-compartment model was able to describe the experimental data well, yielding estimates for Kin of sucrose and mannitol of 0.068 ± 0.005 and 0.146 ± 0.020 μl.min-1.g-1, respectively, which were significantly different (p < 0.01). The separate brain efflux clearance had values of 0.693 ± 0.106 (sucrose) and 0.881 ± 0.20 (mannitol) μl.min-1.g-1, which were not statistically different. Kin values obtained by single time point and multiple time point analyses were dependent on the terminal sampling time and showed declining values for later time points.

CONCLUSIONS

Using the three-compartment model allows determination of Kin for small molecule hydrophilic markers with low blood-brain barrier permeability. It also provides, for the first time, an estimate of brain efflux after systemic administration of a marker, which likely represents bulk flow clearance from brain tissue.

In Vitro Models of the Blood-Brain Barrier

Traditional in vitro models can replicate many essential features of drug transport/permeability across the blood-brain barrier (BBB) but are not entirely projecting in vivo central nervous system (CNS) uptake. Species differences fail to translate experimental therapeutics from the research laboratory to the clinic. Improved in vitro modeling of human BBB is vital for both CNS drug discovery and delivery. High-end human BBB models fabricated by microfluidic technologies offer some solutions to this problem. BBB's complex physiological microenvironment has been established by increasing device complexity in terms of multiple cells, dynamic conditions, and 3D designs. It is now possible to predict the therapeutic effects of a candidate drug and identify new druggable targets by studying multicellular interactions using the advanced in vitro BBB models. This chapter reviews the current as well as an ideal in vitro model of the BBB.

Drug Penetration into the Central Nervous System: Pharmacokinetic Concepts and In Vitro Model Systems

Delivery of most drugs into the central nervous system (CNS) is restricted by the blood-brain barrier (BBB), which remains a significant bottleneck for development of novel CNS-targeted therapeutics or molecular tracers for neuroimaging. Consistent failure to reliably predict drug efficiency based on single measures for the rate or extent of brain penetration has led to the emergence of a more holistic framework that integrates data from various in vivo, in situ and in vitro assays to obtain a comprehensive description of drug delivery to and distribution within the brain. Coupled with ongoing development of suitable in vitro BBB models, this integrated approach promises to reduce the incidence of costly late-stage failures in CNS drug development, and could help to overcome some of the technical, economic and ethical issues associated with in vivo studies in animal models. Here, we provide an overview of BBB structure and function in vivo, and a summary of the pharmacokinetic parameters that can be used to determine and predict the rate and extent of drug penetration into the brain. We also review different in vitro models with regard to their inherent shortcomings and potential usefulness for development of fast-acting drugs or neurotracers labeled with short-lived radionuclides. In this regard, a special focus has been set on those systems that are sufficiently well established to be used in laboratories without significant bioengineering expertise.

Modeling the Effect of Binding Kinetics in Spatial Drug Distribution in the Brain

A 3-dimensional mathematical model is developed to determine the effect of drug binding kinetics on the spatial distribution of a drug within the brain. The key components, namely, transport across the blood-brain barrier (BBB), drug distribution in the brain extracellular fluid (ECF), and drug binding kinetics are coupled with the bidirectional bulk flow of the brain ECF to enhance the visualization of drug concentration in the brain. The model is developed based on the cubical volume of a brain unit, which is a union of three subdomains: the brain ECF, the BBB, and the blood plasma. The model is a set of partial differential equations and the associated initial and boundary conditions through which the drug distribution process in the mentioned subdomains is described. Effects of drug binding kinetics are investigated by varying the binding parameter values for both nonspecific and specific binding sites. All variations of binding parameter values are discussed, and the results show the improved visualization of the effect of binding kinetics in the drug distribution within the brain. For more realistic visualization, we suggest incorporating more brain components that make up the large volume of the brain tissue.

ABCB1 and ABCG2 Together Limit the Distribution of ABCB1/ABCG2 Substrates to the Human Retina and the ABCG2 Single Nucleotide Polymorphism Q141K (c.421C> A) May Lead to Increased Drug Exposure

The widely expressed and poly-specific ABC transporters breast cancer resistance protein (ABCG2) and P-glycoprotein (ABCB1) are co-localized at the blood-brain barrier (BBB) and have shown to limit the brain distribution of several clinically used ABCB1/ABCG2 substrate drugs. It is currently not known to which extent these transporters, which are also expressed at the blood-retinal barrier (BRB), may limit drug distribution to the human eye and whether the ABCG2 reduced-function single-nucleotide polymorphism (SNP) Q141K (c.421C > A) has an impact on retinal drug distribution. Ten healthy male volunteers (five subjects with the c.421CC and c.421CA genotype, respectively) underwent two consecutive positron emission tomography (PET) scans after intravenous injection of the model ABCB1/ABCG2 substrate [¹¹C]tariquidar. The second PET scan was performed with concurrent intravenous infusion of unlabelled tariquidar to inhibit ABCB1 in order to specifically reveal ABCG2 function.In response to ABCB1 inhibition with unlabelled tariquidar, ABCG2 c.421C > A genotype carriers showed significant increases (as compared to the baseline scan) in retinal radiotracer influx K₁ (+62 ± 57%, p = 0.043) and volume of distribution V_T (+86 ± 131%, p = 0.043), but no significant changes were observed in subjects with the c.421C > C genotype. Our results provide the first evidence that ABCB1 and ABCG2 may together limit the distribution of systemically administered ABCB1/ABCG2 substrate drugs to the human retina. Functional redundancy between ABCB1 and ABCG2 appears to be compromised in carriers of the c.421C > A SNP who may therefore be more susceptible to transporter-mediated drug-drug interactions at the BRB than non-carriers.

LightBBB: computational prediction model of blood-brain-barrier penetration based on LightGBM

MOTIVATION

Identification of blood-brain barrier (BBB) permeability of a compound is a major challenge in neurotherapeutic drug discovery. Conventional approaches for BBB permeability measurement are expensive, time-consuming and labor-intensive. BBB permeability is associated with diverse chemical properties of compounds. However, BBB permeability prediction models have been developed using small datasets and limited features, which are usually not practical due to their low coverage of chemical diversity of compounds. Aim of this study is to develop a BBB permeability prediction model using a large dataset for practical applications. This model can be used for facilitated compound screening in the early stage of brain drug discovery.

RESULTS

A dataset of 7162 compounds with BBB permeability (5453 BBB+ and 1709 BBB-) was compiled from the literature, where BBB+ and BBB- denote BBB-permeable and non-permeable compounds, respectively. We trained a machine learning model based on Light Gradient Boosting Machine (LightGBM) algorithm and achieved an overall accuracy of 89%, an area under the curve (AUC) of 0.93, specificity of 0.77 and sensitivity of 0.93, when 10-fold cross-validation was performed. The model was further evaluated using 74 central nerve system compounds (39 BBB+ and 35 BBB-) obtained from the literature and showed an accuracy of 90%, sensitivity of 0.85 and specificity of 0.94. Our model outperforms over existing BBB permeability prediction models.

AVAILABILITYAND IMPLEMENTATION

The prediction server is available at http://ssbio.cau.ac.kr/software/bbb.

Systematically designed chitosan-coated solid lipid nanoparticles of ferulic acid for effective management of Alzheimer's disease: A preclinical evidence

Ferulic acid (FA) is a ubiquitous natural plant bioactive with distinctive promise in neurodegenerative disorders. However, its therapeutic efficacy gets compromised owing to its poor aqueous solubility, inadequate permeability across lipophilic barriers, and extensive first-pass metabolism. The current studies, therefore, were undertaken to systematically develop chitosan-coated solid lipid nanoparticles (SLNs) using QbD paradigms for improved efficacy of FA in the management of Alzheimer's disease (AD). SLNs of FA were formulated employing Compritol as lipid and polysorbate 80 as surfactant and optimised using a 3² Central Composite Design (CCD). The optimized formulation, surface-coated with chitosan using ionic gelation, exhibited particle size of 185 nm, entrapment efficiency of 51.2 % and zeta potential of 12.4 mV. FTIR and DSC studies verified the compatibility of FA with formulation excipients, PXRD construed significant loss of drug crystallinity, while FESEM depicted existence of uniform spherical nanoparticles with little aggregation. Notable improvement in ex vivo mucoadhesion and permeation studies using goat nasal mucosa, coupled with extension in in vitro drug release, was obtained with SLNs. Substantial improvement with SLNs in cognitive ability through the reduction in escape latency time during behavioural studies, together with significant improvement in various biochemical parameters and body weight gain was observed in AD-induced rats. Histopathological images of different rat organs showed no perceptible change(s) in tissue morphology. Overall, these preclinical findings successfully demonstrate improved anti-AD efficacy, superior nasal mucoadhesion and permeation, extended drug release, improved patient compliance potential, safety and robustness of the developed lipidic nanoconstructs of FA through intranasal route.

Enrichment of the erythrocyte miR-451a in brain extracellular vesicles following impairment of the blood-brain barrier

Extracellular RNAs (exRNAs) are present in all biofluids and incorporate many types of RNAs including miRNA. To enhance their stability outside of the cell, exRNAs are bound within ribonucleoprotein complexes or packaged into extracellular vesicles (EVs). The blood-brain barrier (BBB) is a dynamic interface between the systemic circulation and the CNS and is responsible for maintaining a stable extracellular environment for CNS cells. The intent of this study was to determine if EVs and their contents are transferred from the peripheral circulation to the CNS under conditions of an impaired BBB. The BBB of mice was disrupted by unilateral intracarotid artery infusion with hyperosmolar mannitol solution. To validate barrier opening, the uptake clearance of [¹³C₁₂]-sucrose in the left forebrain (i.e. the ipsilateral, mannitol injected hemisphere) was quantified and revealed a 14-fold increase in the mannitol perfused hemisphere compared to sham treated mice. EVs were isolated from the extracellular spaces of the left forebrain following gentle tissue lysis and differential ultracentrifugation. EVs were confirmed using nanotracking analysis, electron microscopy and western blotting. qRT-PCR showed that the erythrocyte-enriched miR-451a in brain tissue EVs increased with mannitol treatment by 24-fold. Small RNA sequencing performed on the EVs isolated from the sham and mannitol treated mice showed that miR-9-5p was the most abundant miRNA contained within the brain EVs. qRT-PCR analysis of plasma EVs did not produce a statistically significant difference in the expression of the CNS-enriched miR-9-5p or miR-9-3p, suggesting that transfer of CNS EVs to the peripheral circulation did not occur under the conditions of our experiment. We demonstrate that EVs containing miR-451a, a highly abundant miRNA present within erythrocytes and erythrocyte EVs, are enhanced in the CNS upon BBB disruption.

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.

The concentration of brain homogenates with the Amicon Ultra Centrifugal filters

Accurately measuring the brain concentration of a neurotherapeutic is critical in determining its pharmacokinetic profile in vivo. Biologics are potential therapeutics for neurologic diseases and biologics fused to an antibody targeting a transcytosis receptor at the Blood-Brain Barrier, designated as antibody-biologic fusion proteins, are Blood-Brain Barrier penetrating neurotherapeutics. The use of sandwich immunosorbent assays to measure concentrations of antibody-biologic fusion proteins in brain homogenates has become increasingly popular. The raw brain homogenate contains many proteins and other macromolecules that can cause a matrix effect, potentially interfering with the limit of detection of such assays and reduce the overall sample signal. Further, the low sample loading volumes while running these assays can reduce the sample signal. Our aim was therefore to optimize the existing tissue sample preparation and processing to concentrate the sample to elevate the signal of the analyte. Here, we present a protocol for concentrating and increasing the signal of transferrin receptor antibody-biologic fusion proteins in mouse brain homogenates using the Amicon Ultra Centrifugal filters.

• The presented method uses the Amicon Ultra Centrifugal filters to concentrate mouse brain tissue homogenates.

• The concentrated brain tissue homogenates are then assayed using standard sandwich enzyme-linked immunosorbent assay (ELISA) protocols.

• This method improves upon the traditional brain homogenization procedure and ELISA measurements for antibody-biologic fusion proteins by effectively concentrating brain tissue homogenates.

Natural based piperine derivatives as potent monoamine oxidase inhibitors: an in silico ADMET analysis and molecular docking studies

Neurodegenerative disorders follow numerous pathological ways concerning overexpression of monoamine oxidase and formation of reactive oxygen species. The computational design of the piperine derivatives has given the significant MAO inhibitors with considerable antioxidant potential. Molecular docking provided the mechanistic insight of the compounds within the hMAO active site. In the current study we have prepared a series of compounds related to piperine and investigated them through monoamine oxidase A and B assay and evaluated the free radical scavenging activity. The synthesized compounds were analyzed by using in silico techniques within the active site of MAO and the ADMET properties were also calculated. The results obtained in this study indicated the interesting therapeutic potential of some compounds such as 7and 17c as most promising hMAO-A inhibitors whereas compounds 15, 5 and 17b were found as hMAO-B inhibitors. Moreover, we assessed the antioxidant potential of the piperine analogues and compounds 5, 17b, and 7 showed very modest antioxidant activity against DPPH and H2O2 radicals. The outcome of the study indicating that the piperine related derivatives are found as considerable MAO inhibitors and antioxidants. Moreover, the SAR structure activity relationships are depicting the structural features required for the MAO inhibition. In case of MAO activity, good correlations were found among the calculated and experimental results.

Treatment of Alzheimer's Disease and Blood-Brain Barrier Drug Delivery

Despite the enormity of the societal and health burdens caused by Alzheimer's disease (AD), there have been no FDA approvals for new therapeutics for AD since 2003. This profound lack of progress in treatment of AD is due to dual problems, both related to the blood-brain barrier (BBB). First, 98% of small molecule drugs do not cross the BBB, and ~100% of biologic drugs do not cross the BBB, so BBB drug delivery technology is needed in AD drug development. Second, the pharmaceutical industry has not developed BBB drug delivery technology, which would enable industry to invent new therapeutics for AD that actually penetrate into brain parenchyma from blood. In 2020, less than 1% of all AD drug development projects use a BBB drug delivery technology. The pathogenesis of AD involves chronic neuro-inflammation, the progressive deposition of insoluble amyloid-beta or tau aggregates, and neural degeneration. New drugs that both attack these multiple sites in AD, and that have been coupled with BBB drug delivery technology, can lead to new and effective treatments of this serious disorder.

Regional Differences in Penetration of the Protein Stabilizer Trimethoprim (TMP) in the Rat Central Nervous System

Regulating gene expression at the protein level is becoming increasingly important for answering basic questions in neurobiology. Several techniques using destabilizing domains (DD) on transgenes, which can be activated or deactivated by specific drugs, have been developed to achieve this goal. A DD from bacterial dihydrofolate reductase bound and stabilized by trimethoprim (TMP) represents such a tool. To control transgenic protein levels in the brain, the DD-regulating drugs need to have sufficient penetration into the central nervous system (CNS). Yet, very limited information is available on TMP pharmacokinetics in the CNS following systemic injection. Here, we performed a pharmacokinetic study on the penetration of TMP into different CNS compartments in the rat. We used mass spectrometry to measure TMP concentrations in serum, cerebrospinal fluid (CSF) and tissue samples of different CNS regions upon intraperitoneal TMP injection. We show that TMP quickly (within 10 min) penetrates from serum to CSF through the blood-CSF barrier. TMP also shows quick penetration into brain tissue but concentrations were an order of magnitude lower compared to serum or CSF. TMP concentration in spinal cord was lower than in any other analyzed CNS area. Nevertheless, effective levels of TMP to stabilize DDs can be reached in the CNS with half-lives around 2 h. These data show that TMP has good and fast penetration properties into the CNS and is therefore a valuable ligand for precisely controlling protein expression in the CNS in rodents.

A face-to-face comparison of claudin-5 transduced human brain endothelial (hCMEC/D3) cells with porcine brain endothelial cells as blood-brain barrier models for drug transport studies

BACKGROUND

Predictive in vitro models of the human blood-brain barrier (BBB) are essential in early drug discovery and development. Among available immortalized human brain capillary endothelial cell lines (BCECs), the hCMEC/D3 cell line has become the most widely used in vitro BBB model. However, monolayers of hCMEC/D3 cells form only moderately restrictive barriers, most likely because the major tight junction protein, claudin-5, is markedly downregulated. Thus, hCMEC/D3 monolayers cannot be used for vectorial drug transport experiments, which is a major disadvantage of this model.

METHODS

Here we transduced hCMEC/D3 cells with a claudin-5 plasmid and compared the characteristics of these cells with those of hCMEC/D3 wildtype cells and primary cultured porcine BCECs.

RESULTS

The claudin-5 transduced hCMEC/D3 exhibited expression levels (and junctional localization) of claudin-5 similar to those of primary cultured porcine BCECs. The transduced cells exhibited increased TEER values (211 Ω cm²) and reduced paracellular mannitol permeability (8.06%/h), indicating improved BBB properties; however, the barrier properties of porcine BCECs (TEER 1650 Ω cm²; mannitol permeability 3.95%/h) were not reached. Hence, vectorial transport of a selective P-glycoprotein substrate (N-desmethyl-loperamide) was not observed in claudin-5 transduced hCMEC/D3 (or wildtype) cells, whereas such drug transport occurred in porcine BCECs.

CONCLUSIONS

The claudin-5 transduced hCMEC/D3 cells provide a tool to studying the contribution of claudin-5 to barrier tightness and how this can be further enhanced by additional transfections or other manipulations of this widely used in vitro model of the BBB.

Challenges and Strategies for Quantification of Drugs in the Brain: Current Scenario and Future Advancement

The site of action of centrally acting drugs lies inside the brain and therefore, needs to reach the brain to exert their therapeutic efficacy. Discovery and development process of such types of drugs demands their quantification in brain to establish the dose, study pharmacokinetics, pharmacodynamics, and optimize the overall efficacy. Moreover, some drugs of other categories also have potential to cross blood-brain barrier resulting in various adverse events by acting centrally. However, the collection of a matrix to analyze the amount of drugs present in brain is highly challenging. In this review, we have summarized different bioanalytical strategies to quantitate drugs inside the brain. A detailed discussion on various in vivo and in vitro techniques for monitoring drugs inside the brain has been incorporated. In addition, various sampling techniques have been discussed in brief with case studies. Therefore, this review can guide the researcher to choose appropriate bioanalytical techniques for analyzing drugs in brain depending upon the specific need and quantification threshold considering the commonly associated difficulties of the methods.

The Influence of Palmatine Isolated from Berberis sibirica Radix on Pentylenetetrazole-Induced Seizures in Zebrafish

Palmatine (PALM) and berberine (BERB) are widely identified isoquinoline alkaloids among the representatives of the Berberidaceae botanical family. The antiseizure activity of BERB was shown previously in experimental epilepsy models. We assessed the effect of PALM in a pentylenetetrazole (PTZ)-induced seizure assay in zebrafish, with BERB as an active reference compound. Both alkaloids were isolated from the methanolic root extract of Berberis sibirica by counter-current chromatography, and their ability to cross the blood–brain barrier was determined via quantitative structure–activity relationship assay. PALM exerted antiseizure activity, as confirmed by electroencephalographic analysis, and decreased c-fos and bdnf levels in PTZ-treated larvae. In a behavioral assay, PALM dose-dependently decreased PTZ-induced hyperlocomotion. The combination of PALM and BERB in ED₁₆ doses revealed hyperadditive activity towards PTZ-induced hyperlocomotion. Notably, we have indicated that both alkaloids may exert their anticonvulsant activity through different mechanisms of action. Additionally, the combination of both alkaloids in a 1:2.17 ratio (PALM: BERB) mimicked the activity of the pure extract, which indicates that these two active compounds are responsible for its anticonvulsive activity. In conclusion, our study reveals for the first time the anticonvulsant activity of PALM and suggests the combination of PALM and BERB may have higher therapeutic value than separate usage of these compounds.

An Affibody Molecule Is Actively Transported into the Cerebrospinal Fluid via Binding to the Transferrin Receptor

The use of biotherapeutics for the treatment of diseases of the central nervous system (CNS) is typically impeded by insufficient transport across the blood-brain barrier. Here, we investigate a strategy to potentially increase the uptake into the CNS of an affibody molecule (ZSYM73) via binding to the transferrin receptor (TfR). ZSYM73 binds monomeric amyloid beta, a peptide involved in Alzheimer's disease pathogenesis, with subnanomolar affinity. We generated a tri-specific fusion protein by genetically linking a single-chain variable fragment of the TfR-binding antibody 8D3 and an albumin-binding domain to the affibody molecule ZSYM73. Simultaneous tri-specific target engagement was confirmed in a biosensor experiment and the affinity for murine TfR was determined to 5 nM. Blockable binding to TfR on endothelial cells was demonstrated using flow cytometry and in a preclinical study we observed increased uptake of the tri-specific fusion protein into the cerebrospinal fluid 24 h after injection.

Predicting the Blood-Brain Barrier Permeability of New Drug-Like Compounds via HPLC with Various Stationary Phases

The permeation of the blood-brain barrier is a very important consideration for new drug candidate molecules. In this research, the reversed-phase liquid chromatography with different columns (Purosphere RP-18e, IAM.PC.DD2 and Cosmosil Cholester) was used to predict the penetration of the blood-brain barrier by 65 newly-synthesized drug-like compounds. The linear free energy relationships (LFERs) model (log BB = c + eE + sS + aA + bB + vV) was established for a training set of 23 congeneric biologically active azole compounds with known experimental log BB (BB = C_blood/C_brain) values (R² = 0.9039). The reliability and predictive potency of the model were confirmed by leave-one-out cross validation as well as leave-50%-out cross validation. Multiple linear regression (MLR) was used to develop the quantitative structure-activity relationships (QSARs) to predict the log BB values of compounds that were tested, taking into account the chromatographic lipophilicity (log k_w), polarizability and topological polar surface area. The excellent statistics of the developed MLR equations (R² > 0.8 for all columns) showed that it is possible to use the HPLC technique and retention data to produce reliable blood-brain barrier permeability models and to predict the log BB values of our pharmaceutically important molecules.

Organ-On-A-Chip in vitro Models of the Brain and the Blood-Brain Barrier and Their Value to Study the Microbiota-Gut-Brain Axis in Neurodegeneration

We are accumulating evidence that intestinal microflora, collectively named gut microbiota, can alter brain pathophysiology, but researchers have just begun to discover the mechanisms of this bidirectional connection (often referred to as microbiota-gut-brain axis, MGBA). The most noticeable hypothesis for a pathological action of gut microbiota on the brain is based on microbial release of soluble neurotransmitters, hormones, immune molecules and neuroactive metabolites, but this complex scenario requires reliable and controllable tools for its causal demonstration. Thanks to three-dimensional (3D) cultures and microfluidics, engineered in vitro models could improve the scientific knowledge in this field, also from a therapeutic perspective. This review briefly retraces the main discoveries linking the activity of gut microbiota to prevalent brain neurodegenerative disorders, and then provides a deep insight into the state-of-the-art for in vitro modeling of the brain and the blood-brain barrier (BBB), two key players of the MGBA. Several brain and BBB microfluidic devices have already been developed to implement organ-on-a-chip solutions, but some limitations still exist. Future developments of organ-on-a-chip tools to model the MGBA will require an interdisciplinary approach and the synergy with cutting-edge technologies (for instance, bioprinting) to achieve multi-organ platforms and support basic research, also for the development of new therapies against neurodegenerative diseases.

ABC Transporters at the Blood-Brain Interfaces, Their Study Models, and Drug Delivery Implications in Gliomas

Drug delivery into the brain is regulated by the blood-brain interfaces. The blood-brain barrier (BBB), the blood-cerebrospinal fluid barrier (BCSFB), and the blood-arachnoid barrier (BAB) regulate the exchange of substances between the blood and brain parenchyma. These selective barriers present a high impermeability to most substances, with the selective transport of nutrients and transporters preventing the entry and accumulation of possibly toxic molecules, comprising many therapeutic drugs. Transporters of the ATP-binding cassette (ABC) superfamily have an important role in drug delivery, because they extrude a broad molecular diversity of xenobiotics, including several anticancer drugs, preventing their entry into the brain. Gliomas are the most common primary tumors diagnosed in adults, which are often characterized by a poor prognosis, notably in the case of high-grade gliomas. Therapeutic treatments frequently fail due to the difficulty of delivering drugs through the brain barriers, adding to diverse mechanisms developed by the cancer, including the overexpression or expression de novo of ABC transporters in tumoral cells and/or in the endothelial cells forming the blood-brain tumor barrier (BBTB). Many models have been developed to study the phenotype, molecular characteristics, and function of the blood-brain interfaces as well as to evaluate drug permeability into the brain. These include in vitro, in vivo, and in silico models, which together can help us to better understand their implication in drug resistance and to develop new therapeutics or delivery strategies to improve the treatment of pathologies of the central nervous system (CNS). In this review, we present the principal characteristics of the blood-brain interfaces; then, we focus on the ABC transporters present on them and their implication in drug delivery; next, we present some of the most important models used for the study of drug transport; finally, we summarize the implication of ABC transporters in glioma and the BBTB in drug resistance and the strategies to improve the delivery of CNS anticancer drugs.

Disease-directed engineering for physiology-driven treatment interventions in neurological disorders

Neurological disease is killing us. While there have long been attempts to develop therapies for both acute and chronic neurological diseases, no current treatments are curative. Additionally, therapeutic development for neurological disease takes 15 years and often costs several billion dollars. More than 96% of these therapies will fail in late stage clinical trials. Engineering novel treatment interventions for neurological disease can improve outcomes and quality of life for millions; however, therapeutics should be designed with the underlying physiology and pathology in mind. In this perspective, we aim to unpack the importance of, and need to understand, the physiology of neurological disease. We first dive into the normal physiological considerations that should guide experimental design, and then assess the pathophysiological factors of acute and chronic neurological disease that should direct treatment design. We provide an analysis of a nanobased therapeutic intervention that proved successful in translation due to incorporation of physiology at all stages of the research process. We also provide an opinion on the importance of keeping a high-level view to designing and administering treatment interventions. Finally, we close with an implementation strategy for applying a disease-directed engineering approach. Our assessment encourages embracing the complexity of neurological disease, as well as increasing efforts to provide system-level thinking in our development of therapeutics for neurological disease.

Physicochemical-property guided design of a highly sensitive probe to image nitrosative stress in the pathology of stroke

In vivo real-time imaging of nitrosative stress in the pathology of stroke has long been a formidable challenge due to both the presence of the blood–brain barrier (BBB) and the elusive nature of reactive nitrogen species, while this task is also informative to gain a molecular level understanding of neurovascular injury caused by nitrosative stress during the stroke episode. Herein, using a physicochemical property-guided probe design strategy in combination with the reaction-based probe design rationale, we have developed an ultrasensitive probe for imaging nitrosative stress evolved in the pathology of stroke. This probe demonstrates an almost zero background fluorescence signal but a maximum 1000-fold fluorescence enhancement in response to peroxynitrite, the nitrosative stress marker. Due to its good physicochemical properties, the probe readily penetrates the BBB after intravenous administration, and quickly accumulates in mice brain to sense local vascular injuries. After accomplishing its imaging mission, the probe is easily metabolized and therefore won't cause safety concerns. These desirable features make the probe competent for the straightforward visualization of nitrosative stress progression in stroke pathology.

A brain–blood barrier permeable probe was developed for fluorogenically sensing nitrosative stress caused by brain vascular injury.

IVIVC Assessment of Two Mouse Brain Endothelial Cell Models for Drug Screening

Since most preclinical drug permeability assays across the blood-brain barrier (BBB) are still evaluated in rodents, we compared an in vitro mouse primary endothelial cell model to the mouse b.End3 and the acellular parallel artificial membrane permeability assay (PAMPA) models for drug screening purposes. The mRNA expression of key feature membrane proteins of primary and bEnd.3 mouse brain endothelial cells were compared. Transwell^® monolayer models were further characterized in terms of tightness and integrity. The in vitro in vivo correlation (IVIVC) was obtained by the correlation of the in vitro permeability data with log BB values obtained in mice for seven drugs. The mouse primary model showed higher monolayer integrity and levels of mRNA expression of BBB tight junction (TJ) proteins and membrane transporters (MBRT), especially for the efflux transporter Pgp. The IVIVC and drug ranking underlined the superiority of the primary model (r² = 0.765) when compared to the PAMPA-BBB (r² = 0.391) and bEnd.3 cell line (r² = 0.019) models. The primary monolayer mouse model came out as a simple and reliable candidate for the prediction of drug permeability across the BBB. This model encompasses a rapid set-up, a fair reproduction of BBB tissue characteristics, and an accurate drug screening.

To Pass or Not To Pass: Predicting the Blood-Brain Barrier Permeability with the 3D-RISM-KH Molecular Solvation Theory

Predicting the ability of chemical species to cross the blood-brain barrier (BBB) is an active field of research for development and mechanistic understanding in the pharmaceutical industry. Here, we report the BBB permeability of a large data set of compounds by incorporating molecular solvation energy descriptors computed by the 3D-RISM-KH molecular solvation theory. We have been able to show, for the first time, that the computed excess chemical potential in different solvents can be successfully used to predict permeability of compounds in a binary manner (yes/no) via a minimum-descriptor-based model. Our findings successfully combine the molecular solvation theory with the machine learning approach to address one of the most daunting challenges in predictive structure-activity relationship modeling. The workflow presented in this work is simple enough to be used by nonexperts with ease.

In Vitro Blood-Brain Barrier Models for Nanomedicine: Particle-Specific Effects and Methodological Drawbacks

Predicting the therapeutic efficacy of a nanocarrier, in a rapid and cost-effective way, is pivotal for the drug delivery to the central nervous system (CNS). In this context, in vitro testing platforms, like the transwell systems, offer numerous advantages to study the passage through the blood-brain barrier (BBB), such as overcoming ethical and methodological issues of in vivo models. However, the use of different transwell filters and nanocarriers with various physical-chemical features makes it difficult to assess the nanocarrier efficacy and achieve data reproducibility. In this work, we performed a systematic study to elucidate the role of the most widely used transwell filters in affecting the passage of nanocarriers, as a function of filter pore size and density. In particular, the transport of carboxyl- and amine-modified 100 nm polystyrene nanoparticles (NPs), chosen as model nanocarriers, was quantified and compared to the behavior of Lucifer yellow (LY), a molecular marker of paracellular transport. Results indicate that the filter type affects the growth and formation of the confluent endothelial barrier, as well as the transport of NPs. Interestingly, the in situ dispersion of NPs was found to play a key role in governing their passage through the filters, both in absence and in presence of the cellular barrier. By framing the underlying nanobiointeractions, we found that particle-specific effects modulated cellular uptake and barrier intracellular distribution, eventually governing transcytosis through their interplay with "size exclusion effects" by the porous filters. This study highlights the importance of a careful evaluation of the physical-chemical profile of the tested nanocarrier along with filter parameters for a correct methodological approach to test BBB permeability in nanomedicine.

Approaches to CNS Drug Delivery with a Focus on Transporter-Mediated Transcytosis

Drug delivery to the central nervous system (CNS) conferred by brain barriers is a major obstacle in the development of effective neurotherapeutics. In this review, a classification of current approaches of clinical or investigational importance for the delivery of therapeutics to the CNS is presented. This classification includes the use of formulations administered systemically that can elicit transcytosis-mediated transport by interacting with transporters expressed by transvascular endothelial cells. Neurotherapeutics can also be delivered to the CNS by means of surgical intervention using specialized catheters or implantable reservoirs. Strategies for delivering drugs to the CNS have evolved tremendously during the last two decades, yet, some factors can affect the quality of data generated in preclinical investigation, which can hamper the extension of the applications of these strategies into clinically useful tools. Here, we disclose some of these factors and propose some solutions that may prove valuable at bridging the gap between preclinical findings and clinical trials.

Improved Classification of Blood-Brain-Barrier Drugs Using Deep Learning

Blood-Brain-Barrier (BBB) is a strict permeability barrier for maintaining the Central Nervous System (CNS) homeostasis. One of the most important conditions to judge a CNS drug is to figure out whether it has BBB permeability or not. In the past 20 years, the existing prediction approaches are usually based on the data of the physical characteristics and chemical structure of drugs. However, these methods are usually only applicable to small molecule compounds based on passive diffusion through BBB. To deal this problem, one of the most famous methods is multi-core SVM method, which is based on clinical phenotypes about Drug Side Effects and Drug Indications to predict drug penetration of BBB. This paper proposed a Deep Learning method to predict the Blood-Brain-Barrier permeability based on the clinical phenotypes data. The validation result on three datasets proved that Deep Learning method achieves better performance than the other existing methods. The average accuracy of our method reaches 0.97, AUC reaches 0.98, and the F1 score is 0.92. The results proved that Deep Learning methods can significantly improve the prediction accuracy of drug BBB permeability and it can help researchers to reduce clinical trials and find new CNS drugs.

Established and Emerging Strategies for Drug Delivery Across the Blood-Brain Barrier in Brain Cancer

Brain tumors are characterized by very high mortality and, despite the continuous research on new pharmacological interventions, little therapeutic progress has been made. One of the main obstacles to improve current treatments is represented by the impermeability of the blood vessels residing within nervous tissue as well as of the new vascular net generating from the tumor, commonly referred to as blood-brain barrier (BBB) and blood-brain tumor barrier (BBTB), respectively. In this review, we focused on established and emerging strategies to overcome the blood-brain barrier to increase drug delivery for brain cancer. To date, there are three broad strategies being investigated to cross the brain vascular wall and they are conceived to breach, bypass, and negotiate the access to the nervous tissue. In this paper, we summarized these approaches highlighting their working mechanism and their potential impact on the quality of life of the patients as well as their current status of development.

The need for mathematical modelling of spatial drug distribution within the brain

The blood brain barrier (BBB) is the main barrier that separates the blood from the brain. Because of the BBB, the drug concentration-time profile in the brain may be substantially different from that in the blood. Within the brain, the drug is subject to distributional and elimination processes: diffusion, bulk flow of the brain extracellular fluid (ECF), extra-intracellular exchange, bulk flow of the cerebrospinal fluid (CSF), binding and metabolism. Drug effects are driven by the concentration of a drug at the site of its target and by drug-target interactions. Therefore, a quantitative understanding is needed of the distribution of a drug within the brain in order to predict its effect. Mathematical models can help in the understanding of drug distribution within the brain. The aim of this review is to provide a comprehensive overview of system-specific and drug-specific properties that affect the local distribution of drugs in the brain and of currently existing mathematical models that describe local drug distribution within the brain. Furthermore, we provide an overview on which processes have been addressed in these models and which have not. Altogether, we conclude that there is a need for a more comprehensive and integrated model that fills the current gaps in predicting the local drug distribution within the brain.