CNS Viral Infections-What to Consider for Improving Drug Treatment: A Plea for Using Mathematical Modeling Approaches

Neurotropic viruses may cause meningitis, myelitis, encephalitis, or meningoencephalitis. These inflammatory conditions of the central nervous system (CNS) may have serious and devastating consequences if not treated adequately. In this review, we first summarize how neurotropic viruses can enter the CNS by (1) crossing the blood-brain barrier or blood-cerebrospinal fluid barrier; (2) invading the nose via the olfactory route; or (3) invading the peripheral nervous system. Neurotropic viruses may then enter the intracellular space of brain cells via endocytosis and/or membrane fusion. Antiviral drugs are currently used for different viral CNS infections, even though their use and dosing regimens within the CNS, with the exception of acyclovir, are minimally supported by clinical evidence. We therefore provide considerations to optimize drug treatment(s) for these neurotropic viruses. Antiviral drugs should cross the blood-brain barrier/blood cerebrospinal fluid barrier and pass the brain cellular membrane to inhibit these viruses inside the brain cells. Some antiviral drugs may also require intracellular conversion into their active metabolite(s). This illustrates the need to better understand these mechanisms because these processes dictate drug exposure within the CNS that ultimately determine the success of antiviral drugs for CNS infections. Finally, we discuss mathematical model-based approaches for optimizing antiviral treatments. Thereby emphasizing the potential of CNS physiologically based pharmacokinetic models because direct measurement of brain intracellular exposure in living humans faces ethical restrictions. Existing physiologically based pharmacokinetic models combined with in vitro pharmacokinetic/pharmacodynamic information can be used to predict drug exposure and evaluate efficacy of antiviral drugs within the CNS, to ultimately optimize the treatments of CNS viral infections.

The potential impact of CYP and UGT drug-metabolizing enzymes on brain target site drug exposure

Drug metabolism is one of the critical determinants of drug disposition throughout the body. While traditionally associated with the liver, recent research has unveiled the presence and functional significance of drug-metabolizing enzymes (DMEs) within the brain. Specifically, cytochrome P-450 enzymes (CYPs) and UDP-glucuronosyltransferases (UGTs) enzymes have emerged as key players in drug biotransformation within the central nervous system (CNS). This comprehensive review explores the cellular and subcellular distribution of CYPs and UGTs within the CNS, emphasizing regional expression and contrasting profiles between the liver and brain, humans and rats. Moreover, we discuss the impact of species and sex differences on CYPs and UGTs within the CNS. This review also provides an overview of methodologies for identifying and quantifying enzyme activities in the brain. Additionally, we present factors influencing CYPs and UGTs activities in the brain, including genetic polymorphisms, physiological variables, pathophysiological conditions, and environmental factors. Examples of CYP- and UGT-mediated drug metabolism within the brain are presented at the end, illustrating the pivotal role of these enzymes in drug therapy and potential toxicity. In conclusion, this review enhances our understanding of drug metabolism's significance in the brain, with a specific focus on CYPs and UGTs. Insights into the expression, activity, and influential factors of these enzymes within the CNS have crucial implications for drug development, the design of safe drug treatment strategies, and the comprehension of drug actions within the CNS. To that end, CNS pharmacokinetic (PK) models can be improved to further advance drug development and personalized therapy.

Using the LeiCNS-PK3.0 Physiologically-Based Pharmacokinetic Model to Predict Brain Extracellular Fluid Pharmacokinetics in Mice

INTRODUCTION

The unbound brain extracelullar fluid (brainECF) to plasma steady state partition coefficient, Kp,uu,BBB, values provide steady-state information on the extent of blood-brain barrier (BBB) transport equilibration, but not on pharmacokinetic (PK) profiles seen by the brain targets. Mouse models are frequently used to study brain PK, but this information cannot directly be used to inform on human brain PK, given the different CNS physiology of mouse and human. Physiologically based PK (PBPK) models are useful to translate PK information across species.

AIM

Use the LeiCNS-PK3.0 PBPK model, to predict brain extracellular fluid PK in mice.

METHODS

Information on mouse brain physiology was collected from literature. All available connected data on unbound plasma, brainECF PK of 10 drugs (cyclophosphamide, quinidine, erlotonib, phenobarbital, colchicine, ribociclib, topotecan, cefradroxil, prexasertib, and methotrexate) from different mouse strains were used. Dosing regimen dependent plasma PK was modelled, and Kpuu,BBB values were estimated, and provided as input into the LeiCNS-PK3.0 model to result in prediction of PK profiles in brainECF.

RESULTS

Overall, the model gave an adequate prediction of the brainECF PK profile for 7 out of the 10 drugs. For 7 drugs, the predicted versus observed brainECF data was within two-fold error limit and the other 2 drugs were within five-fold error limit.

CONCLUSION

The current version of the mouse LeiCNS-PK3.0 model seems to reasonably predict available information on brainECF from healthy mice for most drugs. This brings the translation between mouse and human brain PK one step further.

Status of Metabolomic Measurement for Insights in Alzheimer's Disease Progression-What Is Missing?

Alzheimer's disease (AD) is an aging-related neurodegenerative disease, leading to the progressive loss of memory and other cognitive functions. As there is still no cure for AD, the growth in the number of susceptible individuals represents a major emerging threat to public health. Currently, the pathogenesis and etiology of AD remain poorly understood, while no efficient treatments are available to slow down the degenerative effects of AD. Metabolomics allows the study of biochemical alterations in pathological processes which may be involved in AD progression and to discover new therapeutic targets. In this review, we summarized and analyzed the results from studies on metabolomics analysis performed in biological samples of AD subjects and AD animal models. Then this information was analyzed by using MetaboAnalyst to find the disturbed pathways among different sample types in human and animal models at different disease stages. We discuss the underlying biochemical mechanisms involved, and the extent to which they could impact the specific hallmarks of AD. Then we identify gaps and challenges and provide recommendations for future metabolomics approaches to better understand AD pathogenesis.

Biochemical reaction network topology defines dose-dependent Drug-Drug interactions

Drug combination therapy is a promising strategy to enhance the desired therapeutic effect, while reducing side effects. High-throughput pairwise drug combination screening is a commonly used method for discovering favorable drug interactions, but is time-consuming and costly. Here, we investigate the use of reaction network topology-guided design of combination therapy as a predictive in silico drug-drug interaction screening approach. We focused on three-node enzymatic networks, with general Michaelis-Menten kinetics. The results revealed that drug-drug interactions critically depend on the choice of target arrangement in a given topology, the nature of the drug, and the desired level of change in the network output. The results showed a negative correlation between antagonistic interactions and the dosage of drugs. Overall, the negative feedback loops showed the highest synergistic interactions (the lowest average combination index) and, intriguingly, required the highest drug doses compared to other topologies under the same condition.

Drug Distribution in Brain and Cerebrospinal Fluids in Relation to IC50 Values in Aging and Alzheimer's Disease, Using the Physiologically Based LeiCNS-PK3.0 Model

Background

Very little knowledge exists on the impact of Alzheimer’s disease on the CNS target site pharmacokinetics (PK).

Aim

To predict the CNS PK of cognitively healthy young and elderly and of Alzheimer’s patients using the physiologically based LeiCNS-PK3.0 model.

Methods

LeiCNS-PK3.0 was used to predict the PK profiles in brain extracellular (brain_ECF) and intracellular (brain_ICF) fluids and cerebrospinal fluid of the subarachnoid space (CSF_SAS) of donepezil, galantamine, memantine, rivastigmine, and semagacestat in young, elderly, and Alzheimer’s patients. The physiological parameters of LeiCNS-PK3.0 were adapted for aging and Alzheimer’s based on an extensive literature search. The CNS PK profiles at plateau for clinical dose regimens were related to in vitro IC₅₀ values of acetylcholinesterase, butyrylcholinesterase, N-methyl-D-aspartate, or gamma-secretase.

Results

The PK profiles of all drugs differed between the CNS compartments regarding plateau levels and fluctuation. Brain_ECF, brain_ICF and CSF_SAS PK profile relationships were different between the drugs. Aging and Alzheimer’s had little to no impact on CNS PK. Rivastigmine acetylcholinesterase IC₅₀ values were not reached. Semagacestat brain PK plateau levels were below the IC₅₀ of gamma-secretase for half of the interdose interval, unlike CSF_SAS PK profiles that were consistently above IC_50.

Conclusion

This study provides insights into the relations between CNS compartments PK profiles, including target sites. CSF_SAS PK appears to be an unreliable predictor of brain PK. Also, despite extensive changes in blood-brain barrier and brain properties in Alzheimer’s, this study shows that the impact of aging and Alzheimer’s pathology on CNS distribution of the five drugs is insignificant.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11095-022-03281-3.

Understanding the Blood-Brain Barrier and Beyond: Challenges and Opportunities for Novel CNS Therapeutics

This review addresses questions on how to accomplish successful central nervous system (CNS) drug delivery (i.e., having the right concentration at the right CNS site, at the right time), by understanding the rate and extent of blood‐brain barrier (BBB) transport and intra‐CNS distribution in relation to CNS target site(s) exposure. To this end, we need to obtain and integrate quantitative and connected data on BBB using the Combinatory Mapping Approach that includes in vivo and ex vivo animal measurements, and the physiologically based comprehensive LEICNSPK3.0 mathematical model that can translate from animals to humans. For small molecules, slow diffusional BBB transport and active influx and efflux BBB transport determine the differences between plasma and CNS pharmacokinetics. Obviously, active efflux is important for limiting CNS drug delivery. Furthermore, liposomal formulations of small molecules may to a certain extent circumvent active influx and efflux at the BBB. Interestingly, for CNS pathologies, despite all reported disease associated BBB and CNS functional changes in animals and humans, integrative studies typically show a lack of changes on CNS drug delivery for the small molecules. In contrast, the understanding of the complex vesicle‐based BBB transport modes that are important for CNS delivery of large molecules is in progress, and their BBB transport seems to be significantly affected by CNS diseases. In conclusion, today, CNS drug delivery of small drugs can be well assessed and understood by integrative approaches, although there is still quite a long way to go to understand CNS drug delivery of large molecules.

Potential Mechanisms Underlying Resistance to Dementia in Non-Demented Individuals with Alzheimer's Disease Neuropathology

Alzheimer’s disease (AD) is the most common form of dementia and typically characterized by the accumulation of amyloid-β plaques and tau tangles. Intriguingly, there also exists a group of elderly which do not develop dementia during their life, despite the AD neuropathology, the so-called non-demented individuals with AD neuropathology (NDAN). In this review, we provide extensive background on AD pathology and normal aging and discuss potential mechanisms that enable these NDAN individuals to remain cognitively intact. Studies presented in this review show that NDAN subjects are generally higher educated and have a larger cognitive reserve. Furthermore, enhanced neural hypertrophy could compensate for hippocampal and cingulate neural atrophy in NDAN individuals. On a cellular level, these individuals show increased levels of neural stem cells and ‘von Economo neurons’. Furthermore, in NDAN brains, binding of Aβ oligomers to synapses is prevented, resulting in decreased glial activation and reduced neuroinflammation. Overall, the evidence stated here strengthens the idea that some individuals are more resistant to AD pathology, or at least show an elongation of the asymptomatic state of the disease compared to others. Insights into the mechanisms underlying this resistance could provide new insight in understanding normal aging and AD itself. Further research should focus on factors and mechanisms that govern the NDAN cognitive resilience in order to find clues on novel biomarkers, targets, and better treatments of AD.

Understanding Drug Delivery to the Brain Using Liposome-Based Strategies: Studies that Provide Mechanistic Insights Are Essential

Brain drug delivery may be restricted by the blood-brain barrier (BBB), and enhancement by liposome-based drug delivery strategies has been investigated. As access to the human brain is limited, many studies have been performed in experimental animals. Whereas providing interesting data, such studies have room for improvement to provide mechanistic insight into the rate and extent of specifically BBB transport and intrabrain distribution processes that all together govern CNS target delivery of the free drug. This review shortly summarizes BBB transport and current liposome-based strategies to overcome BBB transport restrictions, with the emphasis on how to determine the individual mechanisms that all together determine the time course of free drug brain concentrations, following their administration as such, and in liposomes. Animal studies using microdialysis providing time course information on unbound drug in plasma and brain are highlighted, as these provide the mechanistic information needed to understand BBB drug transport of the drug, and the impact of a liposomal formulations of that drug on BBB transport. Overall, these studies show that brain distribution of a drug administered as liposomal formulation depends on both drug properties and liposomal formulation characteristics. In general, evidence suggests that active transporters at the BBB, either being influx or efflux transporters, are circumvented by liposomes. It is concluded that liposomal formulations may provide interesting changes in BBB transport. More mechanistic studies are needed to understand relevant mechanisms in liposomal drug delivery to the brain, providing an improved basis for its prediction in human using animal data.

Imaging Techniques in Alzheimer's Disease: A Review of Applications in Early Diagnosis and Longitudinal Monitoring

BACKGROUND

Alzheimer's disease (AD) is a progressive neurodegenerative disorder affecting many individuals worldwide with no effective treatment to date. AD is characterized by the formation of senile plaques and neurofibrillary tangles, followed by neurodegeneration, which leads to cognitive decline and eventually death.

INTRODUCTION

In AD, pathological changes occur many years before disease onset. Since disease-modifying therapies may be the most beneficial in the early stages of AD, biomarkers for the early diagnosis and longitudinal monitoring of disease progression are essential. Multiple imaging techniques with associated biomarkers are used to identify and monitor AD.

AIM

In this review, we discuss the contemporary early diagnosis and longitudinal monitoring of AD with imaging techniques regarding their diagnostic utility, benefits and limitations. Additionally, novel techniques, applications and biomarkers for AD research are assessed.

FINDINGS

Reduced hippocampal volume is a biomarker for neurodegeneration, but atrophy is not an AD-specific measure. Hypometabolism in temporoparietal regions is seen as a biomarker for AD. However, glucose uptake reflects astrocyte function rather than neuronal function. Amyloid-β (Aβ) is the earliest hallmark of AD and can be measured with positron emission tomography (PET), but Aβ accumulation stagnates as disease progresses. Therefore, Aβ may not be a suitable biomarker for monitoring disease progression. The measurement of tau accumulation with PET radiotracers exhibited promising results in both early diagnosis and longitudinal monitoring, but large-scale validation of these radiotracers is required. The implementation of new processing techniques, applications of other imaging techniques and novel biomarkers can contribute to understanding AD and finding a cure.

CONCLUSIONS

Several biomarkers are proposed for the early diagnosis and longitudinal monitoring of AD with imaging techniques, but all these biomarkers have their limitations regarding specificity, reliability and sensitivity. Future perspectives. Future research should focus on expanding the employment of imaging techniques and identifying novel biomarkers that reflect AD pathology in the earliest stages.

Impact of CNS Diseases on Drug Delivery to Brain Extracellular and Intracellular Target Sites in Human: A "WHAT-IF" Simulation Study

The blood-brain barrier (BBB) is equipped with unique physical and functional processes that control central nervous system (CNS) drug transport and the resulting concentration-time profiles (PK). In CNS diseases, the altered BBB and CNS pathophysiology may affect the CNS PK at the drug target sites in the brain extracellular fluid (brainECF) and intracellular fluid (brainICF) that may result in changes in CNS drug effects. Here, we used our human CNS physiologically-based PK model (LeiCNS-PK3.0) to investigate the impact of altered cerebral blood flow (CBF), tight junction paracellular pore radius (pararadius), brainECF volume, and pH of brainECF (pHECF) and of brainICF (pHICF) on brainECF and brainICF PK for 46 small drugs with distinct physicochemical properties. LeiCNS-PK3.0 simulations showed a drug-dependent effect of the pathophysiological changes on the rate and extent of BBB transport and on brainECF and brainICF PK. Altered pararadius, pHECF, and pHICF affected both the rate and extent of BBB drug transport, whereas changes in CBF and brainECF volume modestly affected the rate of BBB drug transport. While the focus is often on BBB paracellular and active transport processes, this study indicates that also changes in pH should be considered for their important implications on brainECF and brainICF target site PK.

A 3D brain unit model to further improve prediction of local drug distribution within the brain

The development of drugs targeting the brain still faces a high failure rate. One of the reasons is a lack of quantitative understanding of the complex processes that govern the pharmacokinetics (PK) of a drug within the brain. While a number of models on drug distribution into and within the brain is available, none of these addresses the combination of factors that affect local drug concentrations in brain extracellular fluid (brain ECF). Here, we develop a 3D brain unit model, which builds on our previous proof-of-concept 2D brain unit model, to understand the factors that govern local unbound and bound drug PK within the brain. The 3D brain unit is a cube, in which the brain capillaries surround the brain ECF. Drug concentration-time profiles are described in both a blood-plasma-domain and a brain-ECF-domain by a set of differential equations. The model includes descriptions of blood plasma PK, transport through the blood-brain barrier (BBB), by passive transport via paracellular and transcellular routes, and by active transport, and drug binding kinetics. The impact of all these factors on ultimate local brain ECF unbound and bound drug concentrations is assessed. In this article we show that all the above mentioned factors affect brain ECF PK in an interdependent manner. This indicates that for a quantitative understanding of local drug concentrations within the brain ECF, interdependencies of all transport and binding processes should be understood. To that end, the 3D brain unit model is an excellent tool, and can be used to build a larger network of 3D brain units, in which the properties for each unit can be defined independently to reflect local differences in characteristics of the brain.

The 3D Brain Unit Network Model to Study Spatial Brain Drug Exposure under Healthy and Pathological Conditions

PURPOSE

We have developed a 3D brain unit network model to understand the spatial-temporal distribution of a drug within the brain under different (normal and disease) conditions. Our main aim is to study the impact of disease-induced changes in drug transport processes on spatial drug distribution within the brain extracellular fluid (ECF).

METHODS

The 3D brain unit network consists of multiple connected single 3D brain units in which the brain capillaries surround the brain ECF. The model includes the distribution of unbound drug within blood plasma, coupled with the distribution of drug within brain ECF and incorporates brain capillaryblood flow, passive paracellular and transcellular BBB transport, active BBB transport, brain ECF diffusion, brain ECF bulk flow, and specific and nonspecific brain tissue binding. All of these processes may change under disease conditions.

RESULTS

We show that the simulated disease-induced changes in brain tissue characteristics significantly affect drug concentrations within the brain ECF.

CONCLUSIONS

We demonstrate that the 3D brain unit network model is an excellent tool to gain understanding in the interdependencies of the factors governing spatial-temporal drug concentrations within the brain ECF. Additionally, the model helps in predicting the spatial-temporal brain ECF concentrations of existing drugs, under both normal and disease conditions.

LUF7244, an allosteric modulator/activator of Kv 11.1 channels, counteracts dofetilide-induced torsades de pointes arrhythmia in the chronic atrioventricular block dog model

BACKGROUND AND PURPOSE

K_v 11.1 (hERG) channel blockade is an adverse effect of many drugs and lead compounds, associated with lethal cardiac arrhythmias. LUF7244 is a negative allosteric modulator/activator of K_v 11.1 channels that inhibits early afterdepolarizations in vitro. We tested LUF7244 for antiarrhythmic efficacy and potential proarrhythmia in a dog model.

EXPERIMENTAL APPROACH

LUF7244 was tested in vitro for (a) increasing human I_Kv11.1 and canine I_Kr and (b) decreasing dofetilide-induced action potential lengthening and early afterdepolarizations in cardiomyocytes derived from human induced pluripotent stem cells and canine isolated ventricular cardiomyocytes. In vivo, LUF7244 was given intravenously to anaesthetized dogs in sinus rhythm or with chronic atrioventricular block.

KEY RESULTS

LUF7244 (0.5-10 μM) concentration dependently increased I_Kv11.1 by inhibiting inactivation. In vitro, LUF7244 (10 μM) had no effects on I_KIR2.1 , I_Nav1.5 , I_Ca-L , and I_Ks , doubled I_Kr , shortened human and canine action potential duration by approximately 50%, and inhibited dofetilide-induced early afterdepolarizations. LUF7244 (2.5 mg·kg^-1 ·15 min^-1 ) in dogs with sinus rhythm was not proarrhythmic and shortened, non-significantly, repolarization parameters (QTc: -6.8%). In dogs with chronic atrioventricular block, LUF7244 prevented dofetilide-induced torsades de pointes arrhythmias in 5/7 animals without normalization of the QTc. Peak LUF7244 plasma levels were 1.75 ± 0.80 during sinus rhythm and 2.34 ± 1.57 μM after chronic atrioventricular block.

CONCLUSIONS AND IMPLICATIONS

LUF7244 counteracted dofetilide-induced early afterdepolarizations in vitro and torsades de pointes in vivo. Allosteric modulators/activators of K_v 11.1 channels might neutralize adverse cardiac effects of existing drugs and newly developed compounds that display QTc lengthening.

Mind the Gaps: Ontogeny of Human Brain P-gp and Its Impact on Drug Toxicity

Available data on human brain P-glycoprotein ontogeny during infancy and childhood are limited. This review discusses the current body of data relating to maturation of human brain P-glycoprotein including transporter expression levels in post-mortem human brain samples, in vivo transporter activity using probe substrates, surrogate marker endpoints, and extrapolations from animal models. Overall, the data tend to confirm that human brain P-glycoprotein activity keeps developing after birth, although with a developmental time frame that remains unclear. This knowledge gap is a concern given the critical role of brain P-glycoprotein in drug safety and efficacy, and the vulnerable nature of the pediatric population. Future research could include the measurement of brain P-glycoprotein activity across age groups using positron emission tomography or central pharmacodynamic responses. For now, caution is advised when extrapolating adult data to children aged younger than 2 years for drugs with P-glycoprotein-dependent central nervous system activity.

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.

Physiologically Based Modeling Approach to Predict Dopamine D2 Receptor Occupancy of Antipsychotics in Brain: Translation From Rat to Human

Receptor occupancy (RO) is a translational biomarker for assessing drug efficacy and safety. We aimed to apply a physiologically based pharmacokinetic (PBPK) modeling approach to predict the brain dopamine D2 RO time profiles of antipsychotics. Clozapine and risperidone were modeled together with their active metabolites, norclozapine and paliperidone, First, in PK‐Sim a rat PBPK model was developed and optimized using literature plasma PK data. Then, blood‐brain barrier parameters including the expression and efflux transport kinetics of P‐glycoprotein were optimized using literature microdialysis data on brain extracellular fluid (brainECF), which were further adapted when translating the rat PBPK model into the human PBPK model. Based on the simulated drug and metabolite concentrations in brainECF, drug‐D2 receptor binding kinetics (association and dissociation rates) were incorporated in MoBi to predict RO. From an extensive literature search, 32 plasma PK data sets (16 from rat and 16 from human studies) and 23 striatum RO data sets (13 from rat and 10 from human studies) were prepared and compared with the model predictions. The rat PBPK‐RO model adequately predicted the plasma concentrations of the parent drugs and metabolites and the RO levels. The human PBPK‐RO model also captured the plasma PK and RO levels despite the large interindividual and interstudy variability, although it tended to underestimate the plasma concentrations and RO measured at late time points after risperidone dosing. The developed human PBPK‐RO model was successfully applied to predict the plasma PK and RO changes observed after risperidone dose reduction in a clinical trial in schizophrenic patients.

Blood-Based Biomarkers of Quinpirole Pharmacology: Cluster-Based PK/PD and Metabolomics to Unravel the Underlying Dynamics in Rat Plasma and Brain

A key challenge in the development of central nervous system drugs is the availability of drug target specific blood-based biomarkers. As a new approach, we applied cluster-based pharmacokinetic/pharmacodynamic (PK/PD) analysis in brain extracellular fluid (brain_ECF ) and plasma simultaneously after 0, 0.17, and 0.86 mg/kg of the dopamine D_2/3 agonist quinpirole (QP) in rats. We measured 76 biogenic amines in plasma and brain_ECF after single and 8-day administration, to be analyzed by cluster-based PK/PD analysis. Multiple concentration-effect relations were observed with potencies ranging from 0.001-383 nM. Many biomarker responses seem to distribute over the blood-brain barrier (BBB). Effects were observed for dopamine and glutamate signaling in brain_ECF , and branched-chain amino acid metabolism and immune signaling in plasma. Altogether, we showed for the first time how cluster-based PK/PD could describe a systems-response across plasma and brain, thereby identifying potential blood-based biomarkers. This concept is envisioned to provide an important connection between drug discovery and early drug development.

Fingerprints of CNS drug effects: a plasma neuroendocrine reflection of D2 receptor activation using multi-biomarker pharmacokinetic/pharmacodynamic modelling

BACKGROUND AND PURPOSE

Because biological systems behave as networks, multi-biomarker approaches increasingly replace single biomarker approaches in drug development. To improve the mechanistic insights into CNS drug effects, a plasma neuroendocrine fingerprint was identified using multi-biomarker pharmacokinetic/pharmacodynamic (PK/PD) modelling. Short- and long-term D2 receptor activation was evaluated using quinpirole as a paradigm compound.

EXPERIMENTAL APPROACH

Rats received 0, 0.17 or 0.86 mg·kg-1 of the D2 agonist quinpirole i.v. Quinpirole concentrations in plasma and brain extracellular fluid (brainECF ), as well as plasma concentrations of 13 hormones and neuropeptides, were measured. Experiments were performed at day 1 and repeated after 7-day s.c. drug administration. PK/PD modelling was applied to identify the in vivo concentration-effect relations and neuroendocrine dynamics.

KEY RESULTS

The quinpirole pharmacokinetics were adequately described by a two-compartment model with an unbound brainECF -to-plasma concentration ratio of 5. The release of adenocorticotropic hormone (ACTH), growth hormone, prolactin and thyroid-stimulating hormone (TSH) from the pituitary was influenced. Except for ACTH, D2 receptor expression levels on the pituitary hormone-releasing cells predicted the concentration-effect relationship differences. Baseline levels (ACTH, prolactin, TSH), hormone release (ACTH) and potency (TSH) changed with treatment duration.

CONCLUSIONS AND IMPLICATIONS

The integrated multi-biomarker PK/PD approach revealed a fingerprint reflecting D2 receptor activation. This forms the conceptual basis for in vivo evaluation of on- and off-target CNS drug effects. The effect of treatment duration is highly relevant given the long-term use of D2 agonists in clinical practice. Further development towards quantitative systems pharmacology models will eventually facilitate mechanistic drug development.

In vitro and in silico analysis of the effects of D2 receptor antagonist target binding kinetics on the cellular response to fluctuating dopamine concentrations

Background and Purpose

Target binding kinetics influence the time course of the drug effect (pharmacodynamics) both (i) directly, by affecting the time course of target occupancy, driven by the pharmacokinetics of the drug, competition with endogenous ligands and target turnover, and (ii) indirectly, by affecting signal transduction and homeostatic feedback. For dopamine D₂ receptor antagonists, it has been hypothesized that fast receptor binding kinetics cause fewer side effects, because part of the dynamics of the dopaminergic system is preserved by displacement of these antagonists.

Experimental Approach

Target binding kinetics of D₂ receptor antagonists and signal transduction after dopamine and D₂ receptor antagonist exposure were measured in vitro. These data were integrated by mechanistic modelling, taking into account competitive binding of endogenous dopamine and the antagonist, the turnover of the second messenger cAMP and negative feedback by PDE turnover.

Key Results

The proposed signal transduction model successfully described the cellular cAMP response for 17 D₂ receptor antagonists with widely different binding kinetics. Simulation of the response to fluctuating dopamine concentrations revealed that a significant effect of the target binding kinetics on the dynamics of the signalling only occurs at endogenous dopamine concentration fluctuations with frequencies below 1 min⁻¹.

Conclusions and Implications

Signal transduction and feedback are important determinants of the time course of drug effects. The effect of the D₂ receptor antagonist dissociation rate constant (k_off) is limited to the maximal rate of fluctuations in dopamine signalling as determined by the dopamine k_off and the cAMP turnover.

Combining Brain Microdialysis and Translational Pharmacokinetic Modeling to Predict Drug Concentrations in Pediatric Severe Traumatic Brain Injury: The Next Step Toward Evidence-Based Pharmacotherapy?

Evidence-based analgosedation in severe pediatric traumatic brain injury (pTBI) management is lacking, and improved pharmacological understanding is needed. This starts with increased knowledge of factors controlling the pharmacokinetics (PK) of unbound drug at the target site (brain) and related drug effect(s). This prospective, descriptive study tested a pediatric physiology-based pharmacokinetic software model by comparing actual plasma and brain extracellular fluid (brain_ECF) morphine concentrations with predicted concentration-time profiles in severe pTBI patients (Glasgow Coma Scale [GCS], ≤8). Plasma and brain_ECF samples were obtained after legal guardian written consent and were collected from 8 pTBI patients (75% male; median age, 96 months [34.0-155.5]; median weight, 24 kg [14.5-55.0]) with a need for intracranial pressure monitoring (GCS, ≤8) and receiving continuous morphine infusion (10-40 μg/kg/h). Brain_ECF samples were obtained by microdialysis. Brain_ECF samples were taken from "injured" and "uninjured" regions as determined by microdialysis catheter location on computed head tomography. A previously developed physiology-based software model to predict morphine concentrations in the brain was adapted to children using pediatric physiological properties. The model predicted plasma morphine concentrations well for individual patients (97% of data points within the 90% prediction interval). In addition, predicted brain_ECF concentration-time profiles fell within a 90% prediction interval of microdialysis brain_ECF drug concentrations when sampled from an uninjured area. Prediction was less accurate in injured areas. This approach of translational physiology-based PK modeling allows prediction of morphine concentration-time profiles in uninjured brain of individual patients and opens promising avenues towards evidence-based pharmacotherapies in pTBI.

Modelling the delay between pharmacokinetics and EEG effects of morphine in rats: binding kinetic versus effect compartment models

Drug–target binding kinetics (as determined by association and dissociation rate constants, k_on and k_off) can be an important determinant of the kinetics of drug action. However, the effect compartment model is used most frequently instead of a target binding model to describe hysteresis. Here we investigate when the drug–target binding model should be used in lieu of the effect compartment model. The utility of the effect compartment (EC), the target binding kinetics (TB) and the combined effect compartment–target binding kinetics (EC–TB) model were tested on either plasma (EC_PL, TB_PL and EC–TB_PL) or brain extracellular fluid (ECF) (EC_ECF, TB_ECF and EC–TB_ECF) morphine concentrations and EEG amplitude in rats. It was also analyzed when a significant shift in the time to maximal target occupancy (Tmax_TO) with increasing dose, the discriminating feature between the TB and EC model, occurs in the TB model. All TB models assumed a linear relationship between target occupancy and drug effect on the EEG amplitude. All three model types performed similarly in describing the morphine pharmacodynamics data, although the EC model provided the best statistical result. The analysis of the shift in Tmax_TO (∆Tmax_TO) as a result of increasing dose revealed that ∆Tmax_TO is decreasing towards zero if the k_off is much smaller than the elimination rate constant or if the target concentration is larger than the initial morphine concentration. The results for the morphine PKPD modelling and the analysis of ∆Tmax_TO indicate that the EC and TB models do not necessarily lead to different drug effect versus time curves for different doses if a delay between drug concentrations and drug effect (hysteresis) is described. Drawing mechanistic conclusions from successfully fitting one of these two models should therefore be avoided. Since the TB model can be informed by in vitro measurements of k_on and k_off, a target binding model should be considered more often for mechanistic modelling purposes.

Target and Tissue Selectivity Prediction by Integrated Mechanistic Pharmacokinetic-Target Binding and Quantitative Structure Activity Modeling

Selectivity is an important attribute of effective and safe drugs, and prediction of in vivo target and tissue selectivity would likely improve drug development success rates. However, a lack of understanding of the underlying (pharmacological) mechanisms and availability of directly applicable predictive methods complicates the prediction of selectivity. We explore the value of combining physiologically based pharmacokinetic (PBPK) modeling with quantitative structure-activity relationship (QSAR) modeling to predict the influence of the target dissociation constant (K _D) and the target dissociation rate constant on target and tissue selectivity. The K _D values of CB1 ligands in the ChEMBL database are predicted by QSAR random forest (RF) modeling for the CB1 receptor and known off-targets (TRPV1, mGlu5, 5-HT1a). Of these CB1 ligands, rimonabant, CP-55940, and Δ⁸-tetrahydrocanabinol, one of the active ingredients of cannabis, were selected for simulations of target occupancy for CB1, TRPV1, mGlu5, and 5-HT1a in three brain regions, to illustrate the principles of the combined PBPK-QSAR modeling. Our combined PBPK and target binding modeling demonstrated that the optimal values of the K _D and k _off for target and tissue selectivity were dependent on target concentration and tissue distribution kinetics. Interestingly, if the target concentration is high and the perfusion of the target site is low, the optimal K _D value is often not the lowest K _D value, suggesting that optimization towards high drug-target affinity can decrease the benefit-risk ratio. The presented integrative structure-pharmacokinetic-pharmacodynamic modeling provides an improved understanding of tissue and target selectivity.

Development of a population pharmacokinetic model to predict brain distribution and dopamine D2 receptor occupancy of raclopride in non-anesthetized rat

BACKGROUND

Raclopride is a selective antagonist of the dopamine D2 receptor. It is one of the most frequently used in vivo D2 tracers (at low doses) for assessing drug-induced receptor occupancy (RO) in animals and humans. It is also commonly used as a pharmacological blocker (at high doses) to occupy the available D2 receptors and antagonize the action of dopamine or drugs on D2 in preclinical studies. The aims of this study were to comprehensively evaluate its pharmacokinetic (PK) profiles in different brain compartments and to establish a PK-RO model that could predict the brain distribution and RO of raclopride in the freely moving rat using a LC-MS based approach.

METHODS

Rats (n=24) received a 10-min IV infusion of non-radiolabeled raclopride (1.61μmol/kg, i.e. 0.56mg/kg). Plasma and the brain tissues of striatum (with high density of D2 receptors) and cerebellum (with negligible amount of D2 receptors) were collected. Additional microdialysis experiments were performed in some rats (n=7) to measure the free drug concentration in the extracellular fluid of the striatum and cerebellum. Raclopride concentrations in all samples were analyzed by LC-MS. A population PK-RO model was constructed in NONMEM to describe the concentration-time profiles in the unbound plasma, brain extracellular fluid and brain tissue compartments and to estimate the RO based on raclopride-D2 receptor binding kinetics.

RESULTS

In plasma raclopride showed a rapid distribution phase followed by a slower elimination phase. The striatum tissue concentrations were consistently higher than that of cerebellum tissue throughout the whole experimental period (10-h) due to higher non-specific tissue binding and D2 receptor binding in the striatum. Model-based simulations accurately predicted the literature data on rat plasma PK, brain tissue PK and D2 RO at different time points after intravenous or subcutaneous administration of raclopride at tracer dose (RO <10%), sub-pharmacological dose (RO 10%-30%) and pharmacological dose (RO >30%).

CONCLUSION

For the first time a predictive model that could describe the quantitative in vivo relationship between dose, PK and D2 RO of raclopride in non-anesthetized rat was established. The PK-RO model could facilitate the selection of optimal dose and dosing time when raclopride is used as tracer or as pharmacological blocker in various rat studies. The LC-MS based approach, which doses and quantifies a non-radiolabeled tracer, could be useful in evaluating the systemic disposition and brain kinetics of tracers.

Revisiting atenolol as a low passive permeability marker

BACKGROUND

Atenolol, a hydrophilic beta blocker, has been used as a model drug for studying passive permeability of biological membranes such as the blood-brain barrier (BBB) and the intestinal epithelium. However, the extent of S-atenolol (the active enantiomer) distribution in brain has never been evaluated, at equilibrium, to confirm that no transporters are involved in its transport at the BBB.

METHODS

To assess whether S-atenolol, in fact, depicts the characteristics of a low passive permeable drug at the BBB, a microdialysis study was performed in rats to monitor the unbound concentrations of S-atenolol in brain extracellular fluid (ECF) and plasma during and after intravenous infusion. A pharmacokinetic model was developed, based on the microdialysis data, to estimate the permeability clearance of S-atenolol into and out of brain. In addition, the nonspecific binding of S-atenolol in brain homogenate was evaluated using equilibrium dialysis.

RESULTS

The steady-state ratio of unbound S-atenolol concentrations in brain ECF to that in plasma (i.e., K_p,uu,brain) was 3.5% ± 0.4%, a value much less than unity. The unbound volume of distribution in brain (V_{u, brain}) of S-atenolol was also calculated as 0.69 ± 0.10 mL/g brain, indicating that S-atenolol is evenly distributed within brain parenchyma. Lastly, equilibrium dialysis showed limited nonspecific binding of S-atenolol in brain homogenate with an unbound fraction (f_u,brain) of 0.88 ± 0.07.

CONCLUSIONS

It is concluded, based on K_p,uu,brain being much smaller than unity, that S-atenolol is actively effluxed at the BBB, indicating the need to re-consider S-atenolol as a model drug for passive permeability studies of BBB transport or intestinal absorption.

From receptor binding kinetics to signal transduction; a missing link in predicting in vivo drug-action

An important question in drug discovery is how to overcome the significant challenge of high drug attrition rates due to lack of efficacy and safety. A missing link in the understanding of determinants for drug efficacy is the relation between drug-target binding kinetics and signal transduction, particularly in the physiological context of (multiple) endogenous ligands. We hypothesized that the kinetic binding parameters of both drug and endogenous ligand play a crucial role in determining cellular responses, using the NK1 receptor as a model system. We demonstrated that the binding kinetics of both antagonists (DFA and aprepitant) and endogenous agonists (NKA and SP) have significantly different effects on signal transduction profiles, i.e. potency values, in vitro efficacy values and onset rate of signal transduction. The antagonistic effects were most efficacious with slowly dissociating aprepitant and slowly associating NKA while the combination of rapidly dissociating DFA and rapidly associating SP had less significant effects on the signal transduction profiles. These results were consistent throughout different kinetic assays and cellular backgrounds. We conclude that knowledge of the relationship between in vitro drug-target binding kinetics and cellular responses is important to ultimately improve the understanding of drug efficacy in vivo.

Predicting Drug Concentration-Time Profiles in Multiple CNS Compartments Using a Comprehensive Physiologically-Based Pharmacokinetic Model

Drug development targeting the central nervous system (CNS) is challenging due to poor predictability of drug concentrations in various CNS compartments. We developed a generic physiologically based pharmacokinetic (PBPK) model for prediction of drug concentrations in physiologically relevant CNS compartments. System‐specific and drug‐specific model parameters were derived from literature and in silico predictions. The model was validated using detailed concentration‐time profiles from 10 drugs in rat plasma, brain extracellular fluid, 2 cerebrospinal fluid sites, and total brain tissue. These drugs, all small molecules, were selected to cover a wide range of physicochemical properties. The concentration‐time profiles for these drugs were adequately predicted across the CNS compartments (symmetric mean absolute percentage error for the model prediction was <91%). In conclusion, the developed PBPK model can be used to predict temporal concentration profiles of drugs in multiple relevant CNS compartments, which we consider valuable information for efficient CNS drug development.

Novel CNS drug discovery and development approach: model-based integration to predict neuro-pharmacokinetics and pharmacodynamics

INTRODUCTION

CNS drug development has been hampered by inadequate consideration of CNS pharmacokinetic (PK), pharmacodynamics (PD) and disease complexity (reductionist approach). Improvement is required via integrative model-based approaches. Areas covered: The authors summarize factors that have played a role in the high attrition rate of CNS compounds. Recent advances in CNS research and drug discovery are presented, especially with regard to assessment of relevant neuro-PK parameters. Suggestions for further improvements are also discussed. Expert opinion: Understanding time- and condition dependent interrelationships between neuro-PK and neuro-PD processes is key to predictions in different conditions. As a first screen, it is suggested to use in silico/in vitro derived molecular properties of candidate compounds and predict concentration-time profiles of compounds in multiple compartments of the human CNS, using time-course based physiology-based (PB) PK models. Then, for selected compounds, one can include in vitro drug-target binding kinetics to predict target occupancy (TO)-time profiles in humans. This will improve neuro-PD prediction. Furthermore, a pharmaco-omics approach is suggested, providing multilevel and paralleled data on systems processes from individuals in a systems-wide manner. Thus, clinical trials will be better informed, using fewer animals, while also, needing fewer individuals and samples per individual for proof of concept in humans.

A novel CCR2 antagonist inhibits atherogenesis in apoE deficient mice by achieving high receptor occupancy

CC Chemokine Receptor 2 (CCR2) and its endogenous ligand CCL2 are involved in a number of diseases, including atherosclerosis. Several CCR2 antagonists have been developed as potential therapeutic agents, however their in vivo clinical efficacy was limited. In this report, we aimed to determine whether 15a, an antagonist with a long residence time on the human CCR2, is effective in inhibiting the development of atherosclerosis in a mouse disease model. First, radioligand binding assays were performed to determine affinity and binding kinetics of 15a on murine CCR2. To assess the in vivo efficacy, western-type diet fed apoE-/- mice were treated daily with 15a or vehicle as control. Treatment with 15a reduced the amount of circulating CCR2+ monocytes and the size of the atherosclerotic plaques in both the carotid artery and the aortic root. We then showed that the long pharmacokinetic half-life of 15a combined with the high drug concentrations ensured prolonged CCR2 occupancy. These data render 15a a promising compound for drug development and confirms high receptor occupancy as a key parameter when targeting chemokine receptors.

A Generic Multi-Compartmental CNS Distribution Model Structure for 9 Drugs Allows Prediction of Human Brain Target Site Concentrations

Purpose

Predicting target site drug concentration in the brain is of key importance for the successful development of drugs acting on the central nervous system. We propose a generic mathematical model to describe the pharmacokinetics in brain compartments, and apply this model to predict human brain disposition.

Methods

A mathematical model consisting of several physiological brain compartments in the rat was developed using rich concentration-time profiles from nine structurally diverse drugs in plasma, brain extracellular fluid, and two cerebrospinal fluid compartments. The effect of active drug transporters was also accounted for. Subsequently, the model was translated to predict human concentration-time profiles for acetaminophen and morphine, by scaling or replacing system- and drug-specific parameters in the model.

Results

A common model structure was identified that adequately described the rat pharmacokinetic profiles for each of the nine drugs across brain compartments, with good precision of structural model parameters (relative standard error <37.5%). The model predicted the human concentration-time profiles in different brain compartments well (symmetric mean absolute percentage error <90%).

Conclusions

A multi-compartmental brain pharmacokinetic model was developed and its structure could adequately describe data across nine different drugs. The model could be successfully translated to predict human brain concentrations.

Electronic supplementary material

The online version of this article (doi:10.1007/s11095-016-2065-3) contains supplementary material, which is available to authorized users.

Target-Site Investigation for the Plasma Prolactin Response: Mechanism-Based Pharmacokinetic-Pharmacodynamic Analysis of Risperidone and Paliperidone in the Rat

To understand the drivers in the biological system response to dopamine D2 receptor antagonists, a mechanistic semiphysiologically based (PB) pharmacokinetic-pharmacodymanic (PKPD) model was developed to describe prolactin responses to risperidone (RIS) and its active metabolite paliperidone (PAL). We performed a microdialysis study in rats to obtain detailed plasma, brain extracellular fluid (ECF), and cerebrospinal fluid (CSF) concentrations of PAL and RIS. To assess the impact of P-glycoprotein (P-gp) functioning on brain distribution, we performed experiments in the absence or presence of the P-gp inhibitor tariquidar (TQD). PK and PKPD modeling was performed by nonlinear mixed-effect modeling. Plasma, brain ECF, and CSF PK values of RIS and PAL were well described by a 12-compartmental semi-PBPK model, including metabolic conversion of RIS to PAL. P-gp efflux functionality was identified on brain ECF for RIS and PAL and on CSF only for PAL. In the PKPD analysis, the plasma drug concentrations were more relevant than brain ECF or CSF concentrations to explain the prolactin response; the estimated EC₅₀ was in accordance with reports in the literature for both RIS and PAL. We conclude that for RIS and PAL, the plasma concentrations better explain the prolactin response than do brain ECF or CSF concentrations. This research shows that PKPD modeling is of high value to delineate the target site of drugs.

Mechanistic models enable the rational use of in vitro drug-target binding kinetics for better drug effects in patients

INTRODUCTION

Drug-target binding kinetics are major determinants of the time course of drug action for several drugs, as clearly described for the irreversible binders omeprazole and aspirin. This supports the increasing interest to incorporate newly developed high-throughput assays for drug-target binding kinetics in drug discovery. A meaningful application of in vitro drug-target binding kinetics in drug discovery requires insight into the relation between in vivo drug effect and in vitro measured drug-target binding kinetics.

AREAS COVERED

In this review, the authors discuss both the relation between in vitro and in vivo measured binding kinetics and the relation between in vivo binding kinetics, target occupancy and effect profiles.

EXPERT OPINION

More scientific evidence is required for the rational selection and development of drug-candidates on the basis of in vitro estimates of drug-target binding kinetics. To elucidate the value of in vitro binding kinetics measurements, it is necessary to obtain information on system-specific properties which influence the kinetics of target occupancy and drug effect. Mathematical integration of this information enables the identification of drug-specific properties which lead to optimal target occupancy and drug effect in patients.

Emerging Insights for Translational Pharmacokinetic and Pharmacokinetic-Pharmacodynamic Studies: Towards Prediction of Nose-to-Brain Transport in Humans

To investigate the potential added value of intranasal drug administration, preclinical studies to date have typically used the area under the curve (AUC) in brain tissue or cerebrospinal fluid (CSF) compared to plasma following intranasal and intravenous administration to calculate measures of extent like drug targeting efficiencies (%DTE) and nose-to-brain transport percentages (%DTP). However, CSF does not necessarily provide direct information on the target site concentrations, while total brain concentrations are not specific to that end either as non-specific binding is not explicitly considered. Moreover, to predict nose-to-brain transport in humans, the use of descriptive analysis of preclinical data does not suffice. Therefore, nose-to-brain research should be performed translationally and focus on preclinical studies to obtain specific information on absorption from the nose, and distinguish between the different transport routes to the brain (absorption directly from the nose to the brain, absorption from the nose into the systemic circulation, and distribution between the systemic circulation and the brain), in terms of extent as well as rate. This can be accomplished by the use of unbound concentrations obtained from plasma and brain, with subsequent advanced mathematical modeling. To that end, brain extracellular fluid (ECF) is a preferred sampling site as it represents most closely the site of action for many targets. Furthermore, differences in nose characteristics between preclinical species and humans should be considered. Finally, pharmacodynamic measurements that can be obtained in both animals and humans should be included to further improve the prediction of the pharmacokinetic-pharmacodynamic relationship of intranasally administered CNS drugs in humans.

Functions of the CB1 and CB 2 receptors in neuroprotection at the level of the blood-brain barrier

The cannabinoid (CB) receptors are the main targets of the cannabinoids, which include plant cannabinoids, endocannabinoids and synthetic cannabinoids. Over the last few years, accumulated evidence has suggested a role of the CB receptors in neuroprotection. The blood-brain barrier (BBB) is an important brain structure that is essential for neuroprotection. A link between the CB receptors and the BBB is thus likely, but this possible connection has only recently gained attention. Cannabinoids and the BBB share the same mechanisms of neuroprotection and both protect against excitotoxicity (CB1), cell death (CB1), inflammation (CB2) and oxidative stress (possibly CB independent)-all processes that also damage the BBB. Several examples of CB-mediated protection of the BBB have been found, such as inhibition of leukocyte influx and induction of amyloid beta efflux across the BBB. Moreover, the CB receptors were shown to improve BBB integrity, particularly by restoring the tightness of the tight junctions. This review demonstrated that both CB receptors are able to restore the BBB and neuroprotection, but much uncertainty about the underlying signaling cascades still exists and further investigation is needed.

Diurnal variation in P-glycoprotein-mediated transport and cerebrospinal fluid turnover in the brain

Nearly all bodily processes exhibit circadian rhythmicity. As a consequence, the pharmacokinetic and pharmacodynamic properties of a drug may also vary with time of day. The objective of this study was to investigate diurnal variation in processes that regulate drug concentrations in the brain, focusing on P-glycoprotein (P-gp). This efflux transporter limits the distribution of many drugs in the brain. To this end, the exposure to the P-gp substrate quinidine was determined in the plasma and brain tissue after intravenous administration in rats at six different time points over the 24-h period. Our results indicate that time of administration significantly affects the exposure to quinidine in the brain. Upon inhibition of P-gp, exposure to quinidine in brain tissue is constant over the 24-h period. To gain more insight into processes regulating brain concentrations, we used intracerebral microdialysis to determine the concentration of quinidine in brain extracellular fluid (ECF) and cerebrospinal fluid (CSF) after intravenous administration at two different time points. The data were analyzed by physiologically based pharmacokinetic modeling using NONMEM. The model shows that the variation is due to higher activity of P-gp-mediated transport from the deep brain compartment to the plasma compartment during the active period. Furthermore, the analysis reveals that CSF flux is higher in the resting period compared to the active period. In conclusion, we show that the exposure to a P-gp substrate in the brain depends on time of administration, thereby providing a new strategy for drug targeting to the brain.

Glutathione PEGylated liposomes: pharmacokinetics and delivery of cargo across the blood-brain barrier in rats

Partly due to poor blood–brain barrier drug penetration the treatment options for many brain diseases are limited. To safely enhance drug delivery to the brain, glutathione PEGylated liposomes (G-Technology®) were developed. In this study, in rats, we compared the pharmacokinetics and organ distribution of GSH-PEG liposomes using an autoquenched fluorescent tracer after intraperitoneal administration and intravenous administration. Although the appearance of liposomes in the circulation was much slower after intraperitoneal administration, comparable maximum levels of long circulating liposomes were found between 4 and 24 h after injection. Furthermore, 24 h after injection a similar tissue distribution was found. To investigate the effect of GSH coating on brain delivery in vitro uptake studies in rat brain endothelial cells (RBE4) and an in vivo brain microdialysis study in rats were used. Significantly more fluorescent tracer was found in RBE4 cell homogenates incubated with GSH-PEG liposomes compared to non-targeted PEG liposomes (1.8-fold, p < 0.001). In the microdialysis study 4-fold higher (p < 0.001) brain levels of fluorescent tracer were found after intravenous injection of GSH-PEG liposomes compared with PEG control liposomes. The results support further investigation into the versatility of GSH-PEG liposomes for enhanced drug delivery to the brain within a tolerable therapeutic window.

The physiological characteristics and transcytosis mechanisms of the blood-brain barrier (BBB)

The blood-brain barrier (BBB) is the vessel wall made up of specialized capillary endothelial cells, surrounded by astroglial endfeet and neurons, that govern the exchange of compounds between blood and brain. It protects the brain from harmful compounds potentially present in blood, while it is specifically designed to supply the brain with the required nutrients and to get rid of waste products. The BBB is structurally different from blood capillaries in other tissues. The BBB strictly limits the paracellular exchange of compounds by the so-called tight junctions. Moreover, the capillary endothelial cells contain metabolic enzymes that may convert a compound before entering the brain while transcellular passage across the BBB may be limited or increased by active transport systems. Thus the BBB has an important role in the relationship of the concentration-time profile of compounds in blood and those in the brain. The functionality of the BBB is dynamically regulated, depending on the given conditions. Important examples are changes in BBB functionality that may result in or are brought about by (CNS) disease conditions. All together this indicates the importance of investigations on BBB functionality and resulting transport of compounds for the design and optimization of therapeutic regimens. Thus, BBB investigation is an ever growing and dynamic field studied by pharmacologists, neuroscientists, pathologists, physiologists, and clinical practitioners. This review deals with a general introduction on the physiological characteristics of the BBB, its different transport systems, with particular emphasis on supposed transcytosis mechanisms at the BBB. Specific and detailed information on drug delivery approaches aiming at transcytosis into the brain will be dealt with in other parts of this special issue.

The impact of P-gp functionality on non-steady state relationships between CSF and brain extracellular fluid

In the development of central nervous system (CNS)-targeted drugs, the prediction of human CNS target exposure is a big challenge. Cerebrospinal fluid (CSF) concentrations have often been suggested as a ‘good enough’ surrogate for brain extracellular fluid (brain_ECF, brain target site) concentrations in humans. However, brain anatomy and physiology indicates prudence. We have applied a multiple microdialysis probe approach in rats, for continuous measurement and direct comparison of quinidine kinetics in brain_ECF, CSF, and plasma. The data obtained indicated important differences between brain_ECF and CSF kinetics, with brain_ECF kinetics being most sensitive to P-gp inhibition. To describe the data we developed a systems-based pharmacokinetic model. Our findings indicated that: (1) brain_ECF- and CSF-to-unbound plasma AUC_0–360 ratios were all over 100 %; (2) P-gp also restricts brain intracellular exposure; (3) a direct transport route of quinidine from plasma to brain cells exists; (4) P-gp-mediated efflux of quinidine at the blood–brain barrier seems to result of combined efflux enhancement and influx hindrance; (5) P-gp at the blood–CSF barrier either functions as an efflux transporter or is not functioning at all. It is concluded that in parallel obtained data on unbound brain_ECF, CSF and plasma concentrations, under dynamic conditions, is a complex but most valid approach to reveal the mechanisms underlying the relationship between brain_ECF and CSF concentrations. This relationship is significantly influenced by activity of P-gp. Therefore, information on functionality of P-gp is required for the prediction of human brain target site concentrations of P-gp substrates on the basis of human CSF concentrations.

Utility of CSF in translational neuroscience

Human cerebrospinal fluid (CSF) sampling is of high value as the only general applicable methodology to obtain information on free drug concentrations in individual human brain. As the ultimate interest is in the free drug concentration at the CNS target site, the question is what CSF concentrations may tell us in that respect. Studies have been performed in rats and other animals for which concentrations in brain extracellular fluid (brain ECF) as a target site for many drugs, have been compared to (cisterna magna) CSF concentrations, at presumed steady state conditions,. The data indicated that CSF drug concentrations provided a rather good indication of, but not a reliable measure for predicting brain ECF concentrations. Furthermore, comparing rat with human CSF concentrations, human CSF concentrations tend to be higher and display much more variability. However, this comparison of CSF concentrations cannot be a direct one, as humans probably had a disease for which CSF was collected in the first place, while the rats were healthy. In order to be able to more accurately predict human brain ECF concentrations, understanding of the complexity of the CNS in terms of intrabrain pharmacokinetic relationships and the influence of CNS disorders on brain pharmacokinetics needs to be increased. This can be achieved by expanding a currently existing preclinically derived physiologically based pharmacokinetic model for brain distribution. This model has been shown to successfully predict data obtained for human lumbar CSF concentrations of acetaminophen which renders trust in the model prediction of human brain ECF concentrations. This model should further evolute by inclusion of influences of drug properties, fluid flows, transporter functionalities and different disease conditions. Finally the model should include measures of target site engagement and CNS effects, to ultimately learn about concentrations that best predict particular target site concentrations, via human CSF concentrations.

[11C]phenytoin revisited: synthesis by [11C]CO carbonylation and first evaluation as a P-gp tracer in rats

BACKGROUND

At present, several positron emission tomography (PET) tracers are in use for imaging P-glycoprotein (P-gp) function in man. At baseline, substrate tracers such as R-[11C]verapamil display low brain concentrations with a distribution volume of around 1. [11C]phenytoin is supposed to be a weaker P-gp substrate, which may lead to higher brain concentrations at baseline. This could facilitate assessment of P-gp function when P-gp is upregulated. The purpose of this study was to synthesize [11C]phenytoin and to characterize its properties as a P-gp tracer.

METHODS

[11C]CO was used to synthesize [11C]phenytoin by rhodium-mediated carbonylation. Metabolism and, using PET, brain pharmacokinetics of [11C]phenytoin were studied in rats. Effects of P-gp function on [11C]phenytoin uptake were assessed using predosing with tariquidar.

RESULTS

[11C]phenytoin was synthesized via [11C]CO in an overall decay-corrected yield of 22 ± 4%. At 45 min after administration, 19% and 83% of radioactivity represented intact [11C]phenytoin in the plasma and brain, respectively. Compared with baseline, tariquidar predosing resulted in a 45% increase in the cerebral distribution volume of [11C]phenytoin.

CONCLUSIONS

Using [11C]CO, the radiosynthesis of [11C]phenytoin could be improved. [11C]phenytoin appeared to be a rather weak P-gp substrate.

Physiologically based pharmacokinetic modeling to investigate regional brain distribution kinetics in rats

One of the major challenges in the development of central nervous system (CNS)-targeted drugs is predicting CNS exposure in human from preclinical data. In this study, we present a methodology to investigate brain disposition in rats using a physiologically based modeling approach aiming at improving the prediction of human brain exposure. We specifically focused on quantifying regional diffusion and fluid flow processes within the brain. Acetaminophen was used as a test compound as it is not subjected to active transport processes. Microdialysis probes were implanted in striatum, for sampling brain extracellular fluid (ECF) concentrations, and in lateral ventricle (LV) and cisterna magna (CM), for sampling cerebrospinal fluid (CSF) concentrations. Serial blood samples were taken in parallel. These data, in addition to physiological parameters from literature, were used to develop a physiologically based model to describe the regional brain pharmacokinetics of acetaminophen. The concentration-time profiles of brain ECF, CSF(LV), and CSF(CM) indicate a rapid equilibrium with plasma. However, brain ECF concentrations are on average fourfold higher than CSF concentrations, with average brain-to-plasma AUC(0-240) ratios of 121%, 28%, and 35% for brain ECF, CSF(LV), and CSF(CM), respectively. It is concluded that for acetaminophen, a model compound for passive transport into, within, and out of the brain, differences exist between the brain ECF and the CSF pharmacokinetics. The physiologically based pharmacokinetic modeling approach is important, as it allowed the prediction of human brain ECF exposure on the basis of human CSF concentrations.

Systemic and direct nose-to-brain transport pharmacokinetic model for remoxipride after intravenous and intranasal administration

Intranasal (IN) administration could be an attractive mode of delivery for drugs targeting the central nervous system, potentially providing a high bioavailability because of avoidance of a hepatic first-pass effect and rapid onset of action. However, controversy remains whether a direct transport route from the nasal cavity into the brain exists. Pharmacokinetic modeling is proposed to identify the existence of direct nose-to-brain transport in a quantitative manner. The selective dopamine-D2 receptor antagonist remoxipride was administered at different dosages, in freely moving rats, by the IN and intravenous (IV) route. Plasma and brain extracellular fluid (ECF) concentration-time profiles were obtained and simultaneously analyzed using nonlinear mixed-effects modeling. Brain ECF/plasma area under the curve ratios were 0.28 and 0.19 after IN and IV administration, respectively. A multicompartment pharmacokinetic model with two absorption compartments (nose-to-systemic and nose-to-brain) was found to best describe the observed pharmacokinetic data. Absorption was described in terms of bioavailability and rate. Total bioavailability after IN administration was 89%, of which 75% was attributed to direct nose-to brain transport. Direct nose-to-brain absorption rate was slow, explaining prolonged brain ECF exposure after IN compared with IV administration. These studies explicitly provide separation and quantitation of systemic and direct nose-to-brain transport after IN administration of remoxipride in the rat. Describing remoxipride pharmacokinetics at the target site (brain ECF) in a semiphysiology-based manner would allow for better prediction of pharmacodynamic effects.

A new minimal-stress freely-moving rat model for preclinical studies on intranasal administration of CNS drugs

Purpose

To develop a new minimal-stress model for intranasal administration in freely moving rats and to evaluate in this model the brain distribution of acetaminophen following intranasal versus intravenous administration.

Methods

Male Wistar rats received one intranasal cannula, an intra-cerebral microdialysis probe, and two blood cannulas for drug administration and serial blood sampling respectively. To evaluate this novel model, the following experiments were conducted. 1) Evans Blue was administered to verify the selectivity of intranasal exposure. 2) During a 1 min infusion 10, 20, or 40 μl saline was administered intranasally or 250 µl intravenously. Corticosterone plasma concentrations over time were compared as biomarkers for stress. 3) 200 µg of the model drug acetaminophen was given in identical setup and plasma, and brain pharmacokinetics were determined.

Results

In 96% of the rats, only the targeted nasal cavity was deeply colored. Corticosterone plasma concentrations were not influenced, neither by route nor volume of administration. Pharmacokinetics of acetaminophen were identical after intravenous and intranasal administration, although the Cmax in microdialysates was reached a little earlier following intravenous administration.

Conclusion

A new minimal-stress model for intranasal administration in freely moving rats has been successfully developed and allows direct comparison with intravenous administration.

Reproducible and time-dependent modification of serum protein binding in Wistar Kyoto rats

INTRODUCTION

The theoretical basis of the influence of (alterations in) plasma protein binding on pharmacokinetics (PK) is well-established. In contrast, the impact of protein binding on pharmacodynamics has not been examined in a systematic manner. Here we present an experimental approach to modify serum protein levels and binding in the rat, in a robust, reproducible, and time-dependent manner.

METHOD

Male Wistar Kyoto rats were divided into three different groups. The control group (n=4) did not receive treatment. In the cannulation(-) group (n=6) the rats were instrumented with three permanent blood cannulas. The rats in the cannulation(+) group received in addition to the cannulation a subcutaneous injection of turpentine oil of 100 microl/100 g bodyweight. The effects were characterized in terms of 1) the time course of serum levels of albumin and alpha(1)-acid glycoprotein (AGP), and 2) the effect on the ex vivo serum protein binding of S(-)-propranolol.

RESULTS

In control rats the AGP serum concentration was stable at a value of 169+/-16 microg/ml. In the cannulation(-) group a maximum ten- to fifteen-fold increase in serum AGP concentration was observed at 48 h post surgery, followed by a gradual return back to baseline within 1 week. In the cannulation(+) group a similar concentration-time profile for AGP was found, but without a complete return to baseline within 1 week and with a much higher variability. Ex vivo, an increase in AGP serum concentration from 55 to 675 microg/ml resulted in a profound decrease in the free fraction of S(-)-propranolol from 14+/-0.6 to 1.9+/-0.3%.

CONCLUSIONS

In conclusion, through cannulation alone the serum protein levels and binding were modified in a robust, reproducible and time-dependent manner. Therefore this experimental approach is suitable for the investigation of the influence of protein binding on both pharmacokinetics and pharmacodynamics.

Toward the prediction of CNS drug-effect profiles in physiological and pathological conditions using microdialysis and mechanism-based pharmacokinetic-pharmacodynamic modeling

Our ultimate goal is to develop mechanism-based pharmacokinetic (PK)-pharmacodynamic (PD) models to characterize and to predict CNS drug responses in both physiologic and pathologic conditions. To this end, it is essential to have information on the biophase pharmacokinetics, because these may significantly differ from plasma pharmacokinetics. It is anticipated that biophase kinetics of CNS drugs are strongly influenced by transport across the blood-brain barrier (BBB). The special role of microdialysis in PK/PD modeling of CNS drugs lies in the fact that it enables the determination of free-drug concentrations as a function of time in plasma and in extracellular fluid of the brain, thereby providing important data to determine BBB transport characteristics of drugs. Also, the concentrations of (potential) extracellular biomarkers of drug effects or disease can be monitored with this technique. Here we describe our studies including microdialysis on the following: (1) the evaluation of the free drug hypothesis; (2) the role of BBB transport on the central effects of opioids; (3) changes in BBB transport and biophase equilibration of anti-epileptic drugs; and (4) the relation among neurodegeneration, BBB transport, and drug effects in Parkinson's disease progression.