Impact of In Vitro Passive Permeability in a P-gp-transfected LLC-PK1 Model on the Prediction of the Rat and Human Unbound Brain-to-Plasma Concentration Ratio

Preclinical evaluation of targeted therapies for central nervous system metastases

The central nervous system (CNS) represents a site of sanctuary for many metastatic tumors when systemic therapies that control the primary tumor cannot effectively penetrate intracranial lesions. Non-small cell lung cancers (NSCLCs) are the most likely of all neoplasms to metastasize to the brain, with up to 60% of patients developing CNS metastases during the disease process. Targeted therapies such as tyrosine kinase inhibitors (TKIs) have helped reduce lung cancer mortality but vary considerably in their capacity to control CNS metastases. The ability of these therapies to effectively target lesions in the CNS depends on several of their pharmacokinetic properties, including blood-brain barrier permeability, affinity for efflux transporters, and binding affinity for both plasma and brain tissue. Despite the existence of numerous preclinical models with which to characterize these properties, many targeted therapies have not been rigorously tested for CNS penetration during the discovery process, whereas some made it through preclinical testing despite poor brain penetration kinetics. Several TKIs have now been engineered with the characteristics of CNS-penetrant drugs, with clinical trials proving these efforts fruitful. This Review outlines the extent and variability of preclinical evidence for the efficacy of NSCLC-targeted therapies, which have been approved by the US Food and Drug Administration (FDA) or are in development, for treating CNS metastases, and how these data correlate with clinical outcomes.

Treating Alzheimer's disease using nanoparticle-mediated drug delivery strategies/systems

The administration of promising medications for the treatment of neurodegenerative disorders (NDDs), such as Alzheimer's disease (AD), Parkinson's disease (PD), Huntington's disease (HD), and amyotrophic lateral sclerosis (ALS) is significantly hampered by the blood-brain barrier (BBB). Nanotechnology has recently come to light as a viable strategy for overcoming this obstacle and improving drug delivery to the brain. With a focus on current developments and prospects, this review article examines the use of nanoparticles to overcome the BBB constraints to improve drug therapy for AD The potential for several nanoparticle-based approaches, such as those utilizing lipid-based, polymeric, and inorganic nanoparticles, to enhance drug transport across the BBB are highlighted. To shed insight on their involvement in aiding effective drug transport to the brain, methods of nanoparticle-mediated drug delivery, such as surface modifications, functionalization, and particular targeting ligands, are also investigated. The article also discusses the most recent findings on innovative medication formulations encapsulated within nanoparticles and the therapeutic effects they have shown in both preclinical and clinical testing. This sector has difficulties and restrictions, such as the need for increased safety, scalability, and translation to clinical applications. However, the major emphasis of this review aims to provide insight and contribute to the knowledge of how nanotechnology can potentially revolutionize the worldwide treatment of NDDs, particularly AD, to enhance clinical outcomes.

Application of a new MDCKII-MDR1 cell model to measure the extent of drug distribution in vitro at equilibrium for prediction of in vivo unbound brain-to-plasma drug distribution

INTRO

Reliable estimates of drug uptake from blood to brain parenchyma are crucial in CNS drug discovery and development. While in vivo Kp,uu,brain estimates are the gold standard for investigating brain drug disposition, animal usage is a limitation to high throughput application. This study investigates an in vitro model using P-gp expressing MDCKII-MDR1 cells for predicting in vivo brain drug penetration.

METHODS

In vitro equilibrium distribution studies were conducted in apical and basolateral solutions with high protein content to estimate Kp,brain and Kp,uu,brain values. The correlation between in vitro and in vivo Kp,brain values for a set of compounds was examined.

RESULTS

We observed a good correlation between in vitro and in vivo Kp,brain values (R2 = 0.69, Slope: 1.6), indicating that the in vitro model could predict in vivo drug brain penetration. The 'unilateral (Uni-L)' in vitro setup correctly classified 5 out of 5 unrestricted compounds and 3 out of 5 restricted compounds. Possible reasons for the observed disparities for some compounds have been discussed, such as difference in transport areas between in vitro and in vivo settings and effect of pH changes.

CONCLUSION

The in vitro assay setup developed in this study holds promise for predicting in vivo drug brain penetration in CNS drug discovery. The correlation between in vitro and in vivo Kp,brain values, underscores that the model may have potential for early-stage screening. With minor refinements, this in vitro approach could reduce the reliance on in vivo experiments, accelerating the pace of CNS drug discovery and promoting a more ethical research approach.

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.

Drug clearance by aldehyde oxidase: can we avoid clinical failure?

Despite increased awareness of aldehyde oxidase (AO) as a major drug-metabolising enzyme, predicting the pharmacokinetics of its substrates remains challenging. Several drug candidates have been terminated due to high clearance, which were subsequently discovered to be AO substrates. Even retrospective extrapolation of human clearance, from models more sensitive to AO activity, often resulted in underprediction.The questions of the current work thus were: Is there an acceptable degree of in vitro AO metabolism that does not result in high in vivo human clearance? And, if so, how can this be predicted?We built an in vitro/in vivo correlation using known AO substrates, combining multiple in vitro parameters to calculate the blood metabolic clearance mediated by AO (CLb_AO). This value was compared with observed blood clearance (CLb_-obs), establishing cut-off CLb_AO values, to discriminate between low and high CLb_-obs. The model was validated using additional literature compounds, and CLb_-obs was predicted in the correct category.This simple, categorical, semi-quantitative yet multi-factorial model is readily applicable in drug discovery. Further, it is valuable for high-clearance compounds, as it predicts the CLb group, rather than an exact CLb value, for the substrates of this poorly-characterised enzyme.

Investigation of the role and quantitative impact of breast cancer resistance protein on drug distribution into brain and CSF in rats

Breast cancer resistance protein (BCRP) expressed in the blood-brain barrier plays a major role in limiting drug distribution into the central nervous system (CNS). However, functional involvement of BCRP in drug distribution into the brain and cerebrospinal fluid (CSF) remains unclear. The aim of present study was to reveal the role and quantitative impact of BCRP on CNS distribution. The brain-to-plasma unbound concentration ratio (K_p,uu,brain) and CSF-to-plasma unbound concentration ratio (K_p,uu,CSF) values of BCRP-specific substrates were determined in rats. The K_p,uu,brain values decreased, as the in vitro BCRP corrected flux ratio (CFR) increased. The K_p,uu,CSF values of BCRP-specific substrates were greater than the K_p,uu,brain values. Increase in the K_p,uu,brain values induced by co-administration of BCRP inhibitor correlated with the in vitro BCRP CFR and were greater than the increase in K_p,uu,CSF values induced by BCRP inhibitor except nebicapone. The contribution of BCRP to the brain and CSF distribution of the dual P-glycoprotein/BCRP substrates, imatinib and prazosin, was similar to that of BCRP-specific substrates. Thus, we revealed that the impact of in vivo BCRP on CNS distribution is correlated with in vitro BCRP CFR, and that BCRP limits drug distribution into the brain more strongly than into the CSF.

Successful Prediction of Human Steady-State Unbound Brain-to-Plasma Concentration Ratio of P-gp Substrates Using the Proteomics-Informed Relative Expression Factor Approach

In order to optimize central nervous system (CNS) drug development, accurate prediction of the drug's human steady-state unbound brain interstitial fluid-to-plasma concentration ratio (K_p,uu,brain ) is critical, especially for drugs that are effluxed by the multiple drug resistance transporters (e.g., P-glycoprotein, P-gp). Due to lack of good in vitro human blood-brain barrier models, we and others have advocated the use of a proteomics-informed relative expressive factor (REF) approach to predict K_p,uu,brain . Therefore, we tested the success of this approach in humans, with a focus on P-gp substrates, using brain positron emission tomography imaging data for verification. To do so, the efflux ratio (ER) of verapamil, N-desmethyl loperamide, and metoclopramide was determined in human P-gp-transfected MDCKII cells using the Transwell assay. Then, using the ER estimate, K_p,uu,brain of the drug was predicted using REF (ER approach). Alternatively, in vitro passive and P-gp-mediated intrinsic clearances (CLs) of these drugs, estimated using a five-compartmental model, were extrapolated to in vivo using REF (active CL) and brain microvascular endothelial cells protein content (passive CL). The ER approach successfully predicted K_p,uu,brain of all three drugs within twofold of observed data and within 95% confidence interval of the observed data for verapamil and N-desmethyl loperamide. Using the in vitro-to-in vivo extrapolated clearance approach, K_p,uu,brain was reasonably well predicted but not the brain unbound interstitial fluid drug concentration-time profile. Therefore, we propose that the ER approach be used to predict K_p,uu,brain of CNS candidate drugs to enhance their success in development.