Exploratory translational modeling approach in drug development to predict human brain pharmacokinetics and pharmacologically relevant clinical doses

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.

Investigating CNS distribution of PF-05212377, a P-glycoprotein substrate, by translation of 5-HT6 receptor occupancy from non-human primates to humans

PF-05212377 (SAM760) is a potent and selective 5-HT₆ antagonist, previously under development for the treatment of Alzheimer's disease. In vitro, PF-05212377 was determined to be a P-gp/non-BCRP human transporter substrate. Species differences were observed in the in vivo brain penetration of PF-05212377 with a ratio of the unbound concentration in brain/unbound concentration in plasma (C_bu /C_pu ) of 0.05 in rat and 0.64 in non-human primates (NHP). Based on pre-clinical evidence, brain penetration and target engagement of PF-05212377 was confirmed in NHP using positron emission tomography (PET) measured 5-HT₆ receptor occupancy (%RO). The NHP C_pu EC₅₀ of PF-05212377 was 0.31 nM (consistent with the in vitro human 5HT6 K_i : 0.32 nM). P-gp has been reported to be expressed in higher abundance at the rat BBB and in similar abundance at the BBB of non-human primates and human; brain penetration of PF-05212377 in humans was postulated to be similar to that in non-human primates. In humans, PF-05212377 demonstrated dose and concentration dependent increases in 5-HT₆ RO; maximal 5-HT6 RO of ∼80% was measured in humans at doses of ≥15 mg with an estimated unbound plasma EC₅₀ of 0.37 nM (which was similar to the in vitro human 5HT6 binding K_i 0.32 nM). In conclusion, cumulative evidence from NHP and human PET RO assessments confirmed that NHP is more appropriate than the rat for the prediction of human brain penetration of PF-05212377, a P-gp/non-BCRP substrate. Clinical trial number: NCT01258751.

The Development of a PBPK Model for Atomoxetine Using Levels in Plasma, Saliva and Brain Extracellular Fluid in Patients with Normal and Deteriorated Kidney Function

BACKGROUND

Atomoxetine is a treatment for attention-deficit hyperactivity disorder. It inhibits Norepinephrine Transporters (NET) in the brain. Renal impairment can reduce hepatic CYP2D6 activity and atomoxetine elimination which may increase its body exposure. Atomoxetine can be secreted in saliva.

OBJECTIVE

The objective of this work was to test the hypothesis that atomoxetine saliva levels (sATX) can be used to predict ATX brain Extracellular Fluid (bECF) levels and their pharmacological effects in healthy subjects and those with End-Stage Renal Disease (ESRD).

METHODS

The pharmacokinetics of atomoxetine after intravenous administration to rats with chemically induced acute and chronic renal impairments were investigated. A physiologically-based pharmacokinetic (PBPK) model was built and verified in rats using previously published measured atomoxetine levels in plasma and brain tissue. The rat PBPK model was then scaled to humans and verified using published measured atomoxetine levels in plasma, saliva, and bECF.

RESULTS

The rat PBPK model predicted the observed reduced atomoxetine clearance due to renal impairment in rats. The PBPK model predicted atomoxetine exposure in human plasma, sATX and bECF. Additionally, it predicted that ATX bECF levels needed to inhibit NET are achieved at 80 mg dose. In ESRD patients, the developed PBPK model predicted that the previously reported 65% increase in plasma exposure in these patients can be associated with a 63% increase in bECF. The PBPK simulations showed that there is a significant correlation between sATX and bECF in human.

CONCLUSION

Saliva levels can be used to predict atomoxetine pharmacological response.

In Vitro to In Vivo Extrapolation Linked to Physiologically Based Pharmacokinetic Models for Assessing the Brain Drug Disposition

Drug development for the central nervous system (CNS) is a complex endeavour with low success rates, as the structural complexity of the brain and specifically the blood-brain barrier (BBB) poses tremendous challenges. Several in vitro brain systems have been evaluated, but the ultimate use of these data in terms of translation to human brain concentration profiles remains to be fully developed. Thus, linking up in vitro-to-in vivo extrapolation (IVIVE) strategies to physiologically based pharmacokinetic (PBPK) models of brain is a useful effort that allows better prediction of drug concentrations in CNS components. Such models may overcome some known aspects of inter-species differences in CNS drug disposition. Required physiological (i.e. systems) parameters in the model are derived from quantitative values in each organ. However, due to the inability to directly measure brain concentrations in humans, compound-specific (drug) parameters are often obtained from in silico or in vitro studies. Such data are translated through IVIVE which could be also applied to preclinical in vivo observations. In such exercises, the limitations of the assays and inter-species differences should be adequately understood in order to verify these predictions with the observed concentration data. This report summarizes the state of IVIVE-PBPK-linked models and discusses shortcomings and areas of further research for better prediction of CNS drug disposition.

Understanding the brain uptake and permeability of small molecules through the BBB: A technical overview

The brain is the most important organ in our body requiring its unique microenvironment. By the virtue of its function, the blood-brain barrier poses a significant hurdle in drug delivery for the treatment of neurological diseases. There are also different theories regarding how molecules are typically effluxed from the brain. In this review, we comprehensively discuss how the different pharmacokinetic techniques used for measuring brain uptake/permeability of small molecules have evolved with time. We also discuss the advantages and disadvantages associated with these different techniques as well as the importance to utilize the right method to properly assess CNS exposure to drug molecules. Even though very strong advances have been made we still have a long way to go to ensure a reduction in failures in central nervous system drug development programs.

Lumbar cerebrospinal fluid-to-brain extracellular fluid surrogacy is context-specific: insights from LeiCNS-PK3.0 simulations

Predicting brain pharmacokinetics is critical for central nervous system (CNS) drug development yet difficult due to ethical restrictions of human brain sampling. CNS pharmacokinetic (PK) profiles are often altered in CNS diseases due to disease-specific pathophysiology. We previously published a comprehensive CNS physiologically-based PK (PBPK) model that predicted the PK profiles of small drugs at brain and cerebrospinal fluid compartments. Here, we improved this model with brain non-specific binding and pH effect on drug ionization and passive transport. We refer to this improved model as Leiden CNS PBPK predictor V3.0 (LeiCNS-PK3.0). LeiCNS-PK3.0 predicted the unbound drug concentrations of brain ECF and CSF compartments in rats and humans with less than two-fold error. We then applied LeiCNS-PK3.0 to study the effect of altered cerebrospinal fluid (CSF) dynamics, CSF volume and flow, on brain extracellular fluid (ECF) pharmacokinetics. The effect of altered CSF dynamics was simulated using LeiCNS-PK3.0 for six drugs and the resulting drug exposure at brain ECF and lumbar CSF were compared. Simulation results showed that altered CSF dynamics changed the CSF PK profiles, but not the brain ECF profiles, irrespective of the drug's physicochemical properties. Our analysis supports the notion that lumbar CSF drug concentration is not an accurate surrogate of brain ECF, particularly in CNS diseases. Systems approaches account for multiple levels of CNS complexity and are better suited to predict brain PK.

Harnessing cerebrospinal fluid circulation for drug delivery to brain tissues

Initially thought to be useful only to reach tissues in the immediate vicinity of the CSF circulatory system, CSF circulation is now increasingly viewed as a viable pathway to deliver certain therapeutics deeper into brain tissues. There is emerging evidence that this goal is achievable in the case of large therapeutic proteins, provided conditions are met that are described herein. We show how fluid dynamic modeling helps predict infusion rate and duration to overcome high CSF turnover. We posit that despite model limitations and controversies, fluid dynamic models, pharmacokinetic models, preclinical testing, and a qualitative understanding of the glymphatic system circulation can be used to estimate drug penetration in brain tissues. Lastly, in addition to highlighting landmark scientific and medical literature, we provide practical advice on formulation development, device selection, and pharmacokinetic modeling. Our review of clinical studies suggests a growing interest for intra-CSF delivery, particularly for targeted proteins.

Comparison of In Vitro Stereoselective Metabolism of Bupropion in Human, Monkey, Rat, and Mouse Liver Microsomes

BACKGROUND AND OBJECTIVES

Bupropion is an atypical antidepressant and smoking cessation aid associated with wide intersubject variability. This study compared the formation kinetics of three phase I metabolites (hydroxybupropion, threohydrobupropion, and erythrohydrobupropion) in human, marmoset, rat, and mouse liver microsomes. The objective was to establish suitability and limitations  for subsequent use of nonclinical species to model bupropion central nervous system (CNS) disposition in humans.

METHODS

Hepatic microsomal incubations were conducted separately for the R- and S-bupropion enantiomers, and the formation of enantiomer-specific metabolites was determined using LC-MS/MS. Intrinsic formation clearance (CL_int) of metabolites across the four species was determined from the formation rate versus substrate concentration relationship.

RESULTS

The total clearance of S-bupropion was higher than that of R-bupropion in monkey and human liver microsomes. The contribution of hydroxybupropion to the total racemic bupropion clearance was 38%, 62%, 17%, and 96% in human, monkey, rat, and mouse, respectively.  In the same species order, threohydrobupropion contributed 53%, 23%, 17%, and 3%, and erythrohydrobupropion contributed 9%, 14%, 66%, and 1.3%, respectively, to racemic bupropion clearance.

CONCLUSION

The results demonstrate that phase I metabolism in monkeys best approximates that observed in humans, and support the preferred use of this species to investigate possible pharmacokinetic factors that influence the CNS disposition of bupropion and contribute to its high intersubject variability.

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.

Atomoxetine: A Review of Its Pharmacokinetics and Pharmacogenomics Relative to Drug Disposition

Atomoxetine is a selective norepinephrine (NE) reuptake inhibitor approved for the treatment of attention-deficit/hyperactivity disorder (ADHD) in children (≥6 years of age), adolescents, and adults. Its metabolism and disposition are fairly complex, and primarily governed by cytochrome P450 (CYP) 2D6 (CYP2D6), whose protein expression varies substantially from person to person, and by race and ethnicity because of genetic polymorphism. These differences can be substantial, resulting in 8-10-fold differences in atomoxetine exposure between CYP2D6 poor metabolizers and extensive metabolizers. In this review, we have attempted to revisit and analyze all published clinical pharmacokinetic data on atomoxetine inclusive of public access documents from the new drug application submitted to the United States Food and Drug Administration (FDA). The present review focuses on atomoxetine metabolism, disposition, and genetic polymorphisms of CYP2D6 as they specifically relate to atomoxetine, and provides an in-depth discussion of the fundamental pharmacokinetics of the drug including its absorption, distribution, metabolism, and excretion in pediatric and adult populations. Further, a summary of relationships between genetic variants of CYP2D6 and to some degree, CYP2C19, are provided with respect to atomoxetine plasma concentrations, central nervous system (CNS) pharmacokinetics, and associated clinical implications for pharmacotherapy. Lastly, dosage adjustments based on pharmacokinetic principles are discussed.

Development of a Rat Plasma and Brain Extracellular Fluid Pharmacokinetic Model for Bupropion and Hydroxybupropion Based on Microdialysis Sampling, and Application to Predict Human Brain Concentrations

Administration of bupropion [(±)-2-(tert-butylamino)-1-(3-chlorophenyl)propan-1-one] and its preformed active metabolite, hydroxybupropion [(±)-1-(3-chlorophenyl)-2-[(1-hydroxy-2-methyl-2-propanyl)amino]-1-propanone], to rats with measurement of unbound concentrations by quantitative microdialysis sampling of plasma and brain extracellular fluid was used to develop a compartmental pharmacokinetics model to describe the blood-brain barrier transport of both substances. The population model revealed rapid equilibration of both entities across the blood-brain barrier, with resultant steady-state brain extracellular fluid/plasma unbound concentration ratio estimates of 1.9 and 1.7 for bupropion and hydroxybupropion, respectively, which is thus indicative of a net uptake asymmetry. An overshoot of the brain extracellular fluid/plasma unbound concentration ratio at early time points was observed with bupropion; this was modeled as a time-dependent uptake clearance of the drug across the blood-brain barrier. Translation of the model was used to predict bupropion and hydroxybupropion exposure in human brain extracellular fluid after twice-daily administration of 150 mg bupropion. Predicted concentrations indicate that preferential inhibition of the dopamine and norepinephrine transporters by the metabolite, with little to no contribution by bupropion, would be expected at this therapeutic dose. Therefore, these results extend nuclear imaging studies on dopamine transporter occupancy and suggest that inhibition of both transporters contributes significantly to bupropion's therapeutic efficacy.

Antidepressants Impact Connexin 43 Channel Functions in Astrocytes

Glial cells, and in particular astrocytes, are crucial to maintain neuronal microenvironment by regulating energy metabolism, neurotransmitter uptake, gliotransmission, and synaptic development. Moreover, a typical feature of astrocytes is their high expression level of connexins, a family of membrane proteins that form gap junction channels allowing intercellular exchanges and hemichannels that provide release and uptake pathways for neuroactive molecules. Interestingly, several studies have revealed unexpected changes in astrocytes from depressive patients and rodent models of depressive-like behavior. Moreover, changes in the expression level of the astroglial connexin 43 (Cx43) have been reported in a depressive context. On the other hand, antidepressive drugs have also been shown to impact the expression of this connexin in astrocytes. However, so far there is little information concerning the functional consequence of these changes, i.e., the status of gap junctional communication and hemichannel activity in astrocytes exposed to antidepressants. In the present work we focused our attention on the action of seven antidepressants from four different therapeutic classes and tested their effects on Cx43 expression and on the two connexin-based channels functions studied in cultured astrocytes. We here report that when used at non-toxic and clinically relevant concentrations they have no effects on Cx43 expression but differential effects on Cx43 gap junction channels. Moreover, all tested antidepressants inhibit Cx43 hemichannel with different efficiency depending on their therapeutic classe. By studying the impact of antidepressants on the functional status of astroglial connexin channels, contributing to dynamic neuroglial interactions, our observations should help to better understand the mechanism by which these drugs provide their effect in the brain.

Comparing translational population-PBPK modelling of brain microdialysis with bottom-up prediction of brain-to-plasma distribution in rat and human

The prediction of brain extracellular fluid (ECF) concentrations in human is a potentially valuable asset during drug development as it can provide the pharmacokinetic input for pharmacokinetic-pharmacodynamic models. This study aimed to compare two translational modelling approaches that can be applied at the preclinical stage of development in order to simulate human brain ECF concentrations. A population-PBPK model of the central nervous system was developed based on brain microdialysis data, and the model parameters were translated to their corresponding human values to simulate ECF and brain tissue concentration profiles. In parallel, the PBPK modelling software Simcyp was used to simulate human brain tissue concentrations, via the bottom-up prediction of brain tissue distribution using two different sets of mechanistic tissue composition-based equations. The population-PBPK and bottom-up approaches gave similar predictions of total brain concentrations in both rat and human, while only the population-PBPK model was capable of accurately simulating the rat ECF concentrations. The choice of PBPK model must therefore depend on the purpose of the modelling exercise, the in vitro and in vivo data available and knowledge of the mechanisms governing the membrane permeability and distribution of the drug.

Prediction of brain clozapine and norclozapine concentrations in humans from a scaled pharmacokinetic model for rat brain and plasma pharmacokinetics

BACKGROUND

Clozapine is highly effective in treatment-resistant schizophrenia, although, there remains significant variability in the response to this drug. To better understand this variability, the objective of this study was to predict brain extracellular fluid (ECF) concentrations and receptor occupancy of clozapine and norclozapine in human central nervous system by translating plasma and brain ECF pharmacokinetic (PK) relationships in the rat and coupling these with known human disposition of clozapine in the plasma.

METHODS

Unbound concentrations of clozapine and norclozapine were measured in rat brain ECF using quantitative microdialysis after subcutaneous administration of a 10 mg/kg single dose of clozapine or norclozapine. These data were linked with plasma concentrations obtained in the same rats to develop a plasma-brain ECF compartmental model. Parameters describing brain ECF disposition were then allometrically scaled and linked with published human plasma PK to predict human ECF concentrations. Subsequently, prediction of human receptor occupancy at several CNS receptors was based on an effect model that related the predicted ECF concentrations to published concentration-driven receptor occupancy parameters.

RESULTS

A one compartment model with first order absorption and elimination best described clozapine and norclozapine plasma concentrations in rats. A delay in the transfer of clozapine and norclozapine from plasma to the brain ECF compartment was captured using a transit compartment model approach. Human clozapine and norclozapine concentrations in brain ECF were simulated, and from these the median percentage of receptor occupancy of dopamine-2, serotonin-2A, muscarinic-1, alpha-1 adrenergic, alpha-2 adrenergic and histamine-1 for clozapine, and dopamine-2 for norclozapine were consistent with values reported in the literature.

CONCLUSIONS

A PK model that relates clozapine and norclozapine disposition in rat plasma and brain, including blood-brain barrier transport, was developed. Using allometry and published human plasma PK, the model was successfully translated to predict clozapine and norclozapine concentrations and accordant receptor occupancy of both agents in human brain. These predicted exposure and occupancy measures at several receptors that bind clozapine may be employed to extend our understanding of clozapine's complex behavioral effects in humans.

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

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

Use of translational pharmacodynamic biomarkers in early-phase clinical studies for schizophrenia

Schizophrenia is a severe mental disorder characterized by cognitive deficits, and positive and negative symptoms. The development of effective pharmacological compounds for the treatment of schizophrenia has proven challenging and costly, with many compounds failing during clinical trials. Many failures occur due to disease heterogeneity and lack of predictive preclinical models and biomarkers that readily translate to humans during early characterization of novel antipsychotic compounds. Traditional early-phase trials consist of single- or multiple-dose designs aimed at determining the safety and tolerability of an investigational compound in healthy volunteers. However, by incorporating a translational approach employing methodologies derived from preclinical studies, such as EEG measures and imaging, into the traditional Phase I program, critical information regarding a compound's dose-response effects on pharmacodynamic biomarkers can be acquired. Furthermore, combined with the use of patients with stable schizophrenia in early-phase clinical trials, significant 'de-risking' and more confident 'go/no-go' decisions are possible.

Physiologically based pharmacokinetic modelling of drug penetration across the blood-brain barrier--towards a mechanistic IVIVE-based approach

Predicting the penetration of drugs across the human blood-brain barrier (BBB) is a significant challenge during their development. A variety of in vitro systems representing the BBB have been described, but the optimal use of these data in terms of extrapolation to human unbound brain concentration profiles remains to be fully exploited. Physiologically based pharmacokinetic (PBPK) modelling of drug disposition in the central nervous system (CNS) currently consists of fitting preclinical in vivo data to compartmental models in order to estimate the permeability and efflux of drugs across the BBB. The increasingly popular approach of using in vitro-in vivo extrapolation (IVIVE) to generate PBPK model input parameters could provide a more mechanistic basis for the interspecies translation of preclinical models of the CNS. However, a major hurdle exists in verifying these predictions with observed data, since human brain concentrations can't be directly measured. Therefore a combination of IVIVE-based and empirical modelling approaches based on preclinical data are currently required. In this review, we summarise the existing PBPK models of the CNS in the literature, and we evaluate the current opportunities and limitations of potential IVIVE strategies for PBPK modelling of BBB penetration.

The mastermind approach to CNS drug therapy: translational prediction of human brain distribution, target site kinetics, and therapeutic effects

Despite enormous advances in CNS research, CNS disorders remain the world's leading cause of disability. This accounts for more hospitalizations and prolonged care than almost all other diseases combined, and indicates a high unmet need for good CNS drugs and drug therapies.Following dosing, not only the chemical properties of the drug and blood-brain barrier (BBB) transport, but also many other processes will ultimately determine brain target site kinetics and consequently the CNS effects. The rate and extent of all these processes are regulated dynamically, and thus condition dependent. Therefore, heterogenious conditions such as species, gender, genetic background, tissue, age, diet, disease, drug treatment etc., result in considerable inter-individual and intra-individual variation, often encountered in CNS drug therapy.For effective therapy, drugs should access the CNS "at the right place, at the right time, and at the right concentration". To improve CNS therapies and drug development, details of inter-species and inter-condition variations are needed to enable target site pharmacokinetics and associated CNS effects to be translated between species and between disease states. Specifically, such studies need to include information about unbound drug concentrations which drive the effects. To date the only technique that can obtain unbound drug concentrations in brain is microdialysis. This (minimally) invasive technique cannot be readily applied to humans, and we need to rely on translational approaches to predict human brain distribution, target site kinetics, and therapeutic effects of CNS drugs.In this review the term "Mastermind approach" is introduced, for strategic and systematic CNS drug research using advanced preclinical experimental designs and mathematical modeling. In this way, knowledge can be obtained about the contributions and variability of individual processes on the causal path between drug dosing and CNS effect in animals that can be translated to the human situation. On the basis of a few advanced preclinical microdialysis based investigations it will be shown that the "Mastermind approach" has a high potential for the prediction of human CNS drug effects.

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.

Microdialysis evaluation of clozapine and N-desmethylclozapine pharmacokinetics in rat brain

A significant barrier to realization of the full potential of clozapine as a therapeutic agent in the treatment of schizophrenia is the substantial interpatient variability that exists along the therapeutic continuum of no response-efficacious response-adverse response. Genetic polymorphisms that manifest as highly variable pharmacodynamic and pharmacokinetic measures are its expected causes. To support investigations that seek to understand these causes, the plasma and central nervous system pharmacokinetics of clozapine were determined in rats, the latter using microdialysis sampling. Results obtained with clozapine and N-desmethylclozapine, a pharmacologically active human metabolite that was administered to a separate group of animals, support a conclusion of net carrier-mediated efflux of both compounds across the blood-brain barrier. These results are supported by the replication of published findings regarding the passive transport and net efflux transport of two model compounds, escitalopram and risperidone, respectively. The results obtained with clozapine and N-desmethylclozapine are considered a first step in the development of preclinical pharmacokinetic-pharmacodynamic models that will support deeper mechanistic studies of clozapine in in vivo pharmacology, as well as the development of translational models that augment pharmacogenetic investigations that seek to improve the safety and efficacy of clozapine therapeutic intervention in the treatment of schizophrenia.

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.