Prediction of human CNS pharmacokinetics using a physiologically-based pharmacokinetic modeling approach

A comprehensive review on modeling aspects of infusion-based drug delivery in the brain

Brain disorders represent an ever-increasing health challenge worldwide. While conventional drug therapies are less effective due to the presence of the blood-brain barrier, infusion-based methods of drug delivery to the brain represent a promising option. Since these methods are mechanically controlled and involve multiple physical phases ranging from the neural and molecular scales to the brain scale, highly efficient and precise delivery procedures can significantly benefit from a comprehensive understanding of drug-brain and device-brain interactions. Behind these interactions are principles of biophysics and biomechanics that can be described and captured using mathematical models. Although biomechanics and biophysics have received considerable attention, a comprehensive mechanistic model for modeling infusion-based drug delivery in the brain has yet to be developed. Therefore, this article reviews the state-of-the-art mechanistic studies that can support the development of next-generation models for infusion-based brain drug delivery from the perspective of fluid mechanics, solid mechanics, and mathematical modeling. The supporting techniques and database are also summarized to provide further insights. Finally, the challenges are highlighted and perspectives on future research directions are provided. STATEMENT OF SIGNIFICANCE: Despite the immense potential of infusion-based drug delivery methods for bypassing the blood-brain barrier and efficiently delivering drugs to the brain, achieving optimal drug distribution remains a significant challenge. This is primarily due to our limited understanding of the complex interactions between drugs and the brain that are governed by principles of biophysics and biomechanics, and can be described using mathematical models. This article provides a comprehensive review of state-of-the-art mechanistic studies that can help to unravel the mechanism of drug transport in the brain across the scales, which underpins the development of next-generation models for infusion-based brain drug delivery. More broadly, this review will serve as a starting point for developing more effective treatments for brain diseases and mechanistic models that can be used to study other soft tissue and biomaterials.

Exploring Kp,uu,BBB values smaller than unity in remoxipride: A physiologically-based CNS model approach highlighting brain metabolism in drugs with passive blood-brain barrier transport

(AIM)

Kp,uu,BBB values are crucial indicators of drug distribution into the brain, representing the steady-state relationship between unbound concentrations in plasma and in brain extracellular fluid (brainECF). Kp,uu,BBB values < 1 are often interpreted as indicators of dominant active efflux transport processes at the blood-brain barrier (BBB). However, the potential impact of brain metabolism on this value is typically not addressed. In this study, we investigated the brain distribution of remoxipride, as a paradigm compound for passive BBB transport with yet unexplained brain elimination that was hypothesized to represent brain metabolism.

(METHODS)

The physiologically-based LeiCNS pharmacokinetic predictor (LeiCNS-PK model) was used to compare brain distribution of remoxipride with and without Michaelis-Menten kinetics at the BBB and/or brain cell organelle levels. To that end, multiple in-house (IV 0.7, 3.5, 4, 5.2, 7, 8, 14 and 16 mg kg-1) and external (IV 4 and 8 mg kg-1) rat microdialysis studies plasma and brainECF data were analysed.

(RESULTS)

The incorporation of active elimination through presumed brain metabolism of remoxipride in the LeiCNS-PK model significantly improved the prediction accuracy of experimentally observed brainECF profiles of this drug. The model integrated with brain metabolism in both barriers and organelles levels is named LeiCNS-PK3.5.

(CONCLUSION)

For drugs with Kp,uu,BBB values < 1, not only the current interpretation of dominant BBB efflux transport, but also potential brain metabolism needs to be considered, especially because these may be concentration dependent. This will improve the mechanistic understanding of the processes that determine brain PK profiles.

Mechanistic Modeling of Intrathecal Chemotherapy Pharmacokinetics in the Human Central Nervous System

PURPOSE

The pharmacokinetics of intrathecally administered antibody or small-molecule drugs in the human central nervous system (CNS) remains poorly understood. This study aimed to provide mechanistic and quantitative perspectives on the CNS pharmacokinetics of intrathecal chemotherapy, by using a physiologically based pharmacokinetic (PBPK) modeling approach.

EXPERIMENTAL DESIGN

A novel CNS PBPK model platform was developed and verified, which accounted for the human CNS general anatomy and physiologic processes governing drug distribution and disposition. The model was used to predict CNS pharmacokinetics of antibody (trastuzumab) and small-molecule drugs (methotrexate, abemaciclib, tucatinib) following intraventricular injection or intraventricular 24-hour infusion, and to assess the key determinants of drug penetration into the deep brain parenchyma.

RESULTS

Intraventricularly administered antibody and small-molecule drugs exhibited distinct temporal and spatial distribution and disposition in human CNS. Both antibody and small-molecule drugs achieved supratherapeutic or therapeutic concentrations in the cerebrospinal fluid (CSF) compartments and adjacent brain tissue. While intrathecal small-molecule drugs penetrated the deep brain parenchyma to a negligible extent, intrathecal antibodies may achieve therapeutic concentrations in the deep brain parenchyma. Intraventricular 24-hour infusion enabled prolonged CNS exposure to therapeutically relevant concentrations while avoiding excessively high and potentially neurotoxic drug concentrations.

CONCLUSIONS

CNS PBPK modeling, in line with available clinical efficacy data, confirms the therapeutic value of intrathecal chemotherapy with antibody or small-molecule drugs for treating neoplastic meningitis and warrants further clinical investigation of intrathecal antibody drugs to treat brain parenchyma tumors. Compared with intraventricular injection, intraventricular 24-hour infusion may mitigate neurotoxicity while retaining potential efficacy.

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.

Does nonlinear blood-brain barrier transport matter for (lower) morphine dosing strategies?

Morphine blood-brain barrier (BBB) transport is governed by passive diffusion, active efflux and saturable active influx. This may result in nonlinear plasma concentration-dependent brain extracellular fluid (brainECF) pharmacokinetics of morphine. In this study, we aim to evaluate the impact of nonlinear BBB transport on brainECF pharmacokinetics of morphine and its metabolites for different dosing strategies using a physiologically based pharmacokinetic simulation study. We extended the human physiologically based pharmacokinetic LeiCNS-PK3.0, model with equations for nonlinear BBB transport of morphine. Simulations for brainECF pharmacokinetics were performed for various dosing strategies: intravenous (IV), oral immediate (IR) and extended release (ER) with dose range of 0.25-150 mg and dosing frequencies of 1-6 times daily. The impact of nonlinear BBB transport on morphine CNS pharmacokinetics was evaluated by quantifying (i) the relative brainECF to plasma exposure (AUCu,brainECF/AUCu,plasma) and (ii) the impact on the peak-to-trough ratio (PTR) of concentration-time profiles in brainECF and plasma. We found that the relative morphine exposure and PTRs are dose dependent for the evaluated dose range. The highest relative morphine exposure value of 1.4 was found for once daily 0.25 mg ER and lowest of 0.1 for 6-daily 150 mg IV dosing. At lower doses the PTRs were smaller and increased with increasing dose and stabilized at higher doses independent of dosing frequency. Relative peak concentrations of morphine in relation to its metabolites changed with increasing dose. We conclude that nonlinearity of morphine BBB transport affects the relative brainECF exposure and the fluctuation of morphine and its metabolites mainly at lower dosing regimens.

Evaluation of bottom-up modeling of the blood-brain barrier to improve brain penetration prediction via physiologically based pharmacokinetic modeling

Predicting the brain penetration of drugs has been notoriously difficult; however, recently, permeability-limited brain models have been constructed. Lead optimization for central nervous system compounds often focuses on compounds that have low transporter efflux, where passive permeability could be a main driver in determining cerebrospinal fluid (CSF)/brain concentrations. The main objective of this study was to evaluate the translatability of passive permeability data generated from different in vitro systems and its impact on the prediction of human CSF/brain concentrations using physiologically-based pharmacokinetic (PBPK) modeling. In vitro data were generated using gMDCK and parallel artificial membrane permeability assay-blood-brain barrier for comparison and predictions using a quantitative structure-activity relationship model were also evaluated. PBPK modeling was then performed for seven compounds with moderate-high permeability and a range of efflux in vitro, and the CSF/brain mass concentrations and Kpuu were reasonably predicted. This work provides the first step of a promising approach using bottom-up PBPK modeling for CSF/brain penetration prediction to support lead optimization and clinical candidate selection.

Recent advances in the in vitro and in vivo methods to assess impact of P-glycoprotein and breast cancer resistance protein transporters in central nervous system drug disposition

One challenge in central nervous system (CNS) drug discovery has been ensuring the blood-brain barrier (BBB) penetration of compounds at an efficacious concentration that provides suitable safety margins for clinical investigation. Research providing for the accurate prediction of brain penetration of compounds during preclinical discovery is important to a CNS program. In the BBB, P-glycoprotein (P-gp) (ABCB1) and breast cancer resistance protein (BCRP) (ABCG2) transporters have been demonstrated to play a major role in the active efflux of endogenous compounds and xenobiotics out of the brain microvessel cells and back to the systemic circulation. In the past 10 years, there has been significant technological improvement in the sensitivity of quantitative proteomics methods, in vivo imaging, in vitro methods of organoid and microphysiological systems, as well as in silico quantitative physiological based pharmacokinetic and systems pharmacology models. Scientists continually leverage these advancements to interrogate the distribution of compounds in the CNS which may also show signals of substrate specificity of P-gp and/or BCRP. These methods have shown promise toward predicting and quantifying the unbound concentration(s) within the brain relevant for efficacy or safety. In this review, the authors have summarized the in vivo, in vitro, and proteomics advancements toward understanding the contribution of P-gp and/or BCRP in restricting the entry of compounds to the CNS of either healthy or special populations. Special emphasis has been provided on recent investigations on the application of a proteomics-informed approach to predict steady-state drug concentrations in the brain. Moreover, future perspectives regarding the role of these transporters in newer modalities are discussed.

An Overview of Physiologically-Based Pharmacokinetic Models for Forensic Science

A physiologically-based pharmacokinetic (PBPK) model represents the structural components of the body with physiologically relevant compartments connected via blood flow rates described by mathematical equations to determine drug disposition. PBPK models are used in the pharmaceutical sector for drug development, precision medicine, and the chemical industry to predict safe levels of exposure during the registration of chemical substances. However, one area of application where PBPK models have been scarcely used is forensic science. In this review, we give an overview of PBPK models successfully developed for several illicit drugs and environmental chemicals that could be applied for forensic interpretation, highlighting the gaps, uncertainties, and limitations.

A Physiologically-Based Pharmacokinetic Model of the Brain Considering Regional Lipid Variance

Modeling and simulation of the central nervous system provides a tool for understanding and predicting the distribution of small molecules throughout the brain tissue and cerebral spinal fluid (CSF), and these efforts often rely on empirical data to make predictions of distributions to move toward a better mechanistic understanding. A physiologically based pharmacokinetic model presented here incorporates multiple means of drug distribution to assemble a model for understanding potential factors that may determine the distribution of drugs across various regions of the brain, including both intra- and extracellular regions. Two classes of parameters are presented. The first concerns regional gross anatomic variability of the brain; the second concerns estimation of unbound fractions of drugs using know membrane phospholipid heterogeneity derived from regional lipid content. The model was then tested by comparing its outcomes to data from published human pharmacokinetic studies of acetaminophen, morphine, and phenytoin. The alignment of model predictions in the plasma, CSF, and tissue concentrations with the published data from studies of those three drugs suggests that the model can be a template for identifying drug localization in the brain. Clearly, knowledge of differentiated drug distribution in the brain is a requisite step in postulating pharmacodynamic and certain disease mechanisms. SIGNIFICANCE STATEMENT: This study concerns the application of heterogenous lipid distribution in brain tissue to predict regional variations in drug distribution in the brain via a mathematical model, thus expanding upon the current understanding of mechanisms of drug distribution in the central nervous system.

Investigating brain uptake of a non-targeting monoclonal antibody after intravenous and intracerebroventricular administration

Monoclonal antibodies play an important role in the treatment of various diseases. However, the development of these drugs against neurological disorders where the drug target is located in the brain is challenging and requires a good understanding of the local drug concentration in the brain. In this original research, we investigated the systemic and local pharmacokinetics in the brain of healthy rats after either intravenous (IV) or intracerebroventricular (ICV) administration of EGFRvIII-T-Cell bispecific (TCB), a bispecific monoclonal antibody. We established an experimental protocol that allows serial sampling in serum, cerebrospinal fluid (CSF) and interstitial fluid (ISF) of the prefrontal cortex in freely moving rats. For detection of drug concentration in ISF, a push-pull microdialysis technique with large pore membranes was applied. Brain uptake into CSF and ISF was characterized and quantified with a reduced brain physiologically-based pharmacokinetic model. The model allowed us to interpret the pharmacokinetic processes of brain uptake after different routes of administration. The proposed model capturing the pharmacokinetics in serum, CSF and ISF of the prefrontal cortex suggests a barrier function between the CSF and ISF that impedes free antibody transfer. This finding suggests that ICV administration may not be better suited to reach higher local drug exposure as compared to IV administration. The model enabled us to quantify the relative contribution of the blood-brain barrier (BBB) and Blood-CSF-Barrier to the uptake into the interstitial fluid of the brain. In addition, we compared the brain uptake of three monoclonal antibodies after IV dosing. In summary, the presented approach can be applied to profile compounds based on their relative uptake in the brain and provides quantitative insights into which pathways are contributing to the net exposure in the brain.

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.

Current status and future directions for a neurotoxicity hazard assessment framework that integrates in silico approaches

Neurotoxicology is the study of adverse effects on the structure or function of the developing or mature adult nervous system following exposure to chemical, biological, or physical agents. The development of more informative alternative methods to assess developmental (DNT) and adult (NT) neurotoxicity induced by xenobiotics is critically needed. The use of such alternative methods including in silico approaches that predict DNT or NT from chemical structure (e.g., statistical-based and expert rule-based systems) is ideally based on a comprehensive understanding of the relevant biological mechanisms. This paper discusses known mechanisms alongside the current state of the art in DNT/NT testing. In silico approaches available today that support the assessment of neurotoxicity based on knowledge of chemical structure are reviewed, and a conceptual framework for the integration of in silico methods with experimental information is presented. Establishing this framework is essential for the development of protocols, namely standardized approaches, to ensure that assessments of NT and DNT based on chemical structures are generated in a transparent, consistent, and defendable manner.

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.

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.

From blood to brain: blood cell-based biomimetic drug delivery systems

Brain drug delivery remains a major difficulty for several challenges including the blood-brain barrier, lesion spot targeting, and stability during circulation. Blood cells including erythrocytes, platelets, and various subpopulations of leukocytes have distinct features such as long-circulation, natural targeting, and chemotaxis. The development of biomimetic drug delivery systems based on blood cells for brain drug delivery is growing fast by using living cells, membrane coating nanotechnology, or cell membrane-derived nanovesicles. Blood cell-based vehicles are superior delivery systems for their engineering feasibility and versatile delivery ability of chemicals, proteins, and all kinds of nanoparticles. Here, we focus on advances of blood cell-based biomimetic carriers for from blood to brain drug delivery and discuss their translational challenges in the future.

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.

Comparison of Oral Loading Dose to Intravenous Acetaminophen in Children for Analgesia After Tonsillectomy and Adenoidectomy: A Randomized Clinical Trial

BACKGROUND

Acetaminophen is a frequently used adjunct analgesic in pediatric patients undergoing tonsillectomy and adenoidectomy. We compared opioid administration following preoperative intravenous (IV) or oral acetaminophen in addition to a standard multimodal regimen to test the hypothesis that 1 loading dose approach would provide superior opioid sparing effects among pediatric surgical patients undergoing tonsillectomy and adenoidectomy.

METHODS

This single-center, double-blind, double-dummy prospective randomized study was conducted in patients ages 3 to 15 years undergoing tonsillectomy and adenoidectomy with or without myringotomy and tube placement between September 2017 and July 2019. Subjects received 1 dose of either oral acetaminophen 30 mg/kg with IV placebo (oral group) or IV acetaminophen 15 mg/kg with oral placebo (IV group). Acetaminophen plasma levels were measured at 2 timepoints to evaluate safety and determine plasma levels attained by each dosing regimen. Intraoperative opioid administration and postoperative analgesia were standardized. Standardized postoperative multimodal analgesia included opioid if needed to control pain assessed by standardized validated pediatric pain scales. The primary outcome measure was total opioid administration in the first 24 hours after surgery. Continuous data were not normally distributed and were analyzed using the Wilcoxon rank sum test and the Hodges-Lehman estimator of the median difference. Clinical significance was defined as a 100 µg/kg IV morphine equivalents per day difference.

RESULTS

Sixty-six subjects were randomized into and completed the study (29 women, 37 men; age 5.9 ± 3.0 years; percentile weight for age 49.5 ± 30.2; no differences between groups). There was no opioid dose difference between oral (median 147.6; interquartile range [IQR], 119.6-193.0 µg/kg) and IV groups (median 125.4; IQR, 102.8-150.9 µg/kg; median difference 21.3; 95% confidence interval [CI] -2.5 to 44.2 µg/kg IV morphine equivalents; P = .13). No acetaminophen levels exceeded the predefined safety threshold (40 mg/L). No difference was found in the percentage of patients with severe pain: 50.0% oral group, 47.2% IV group; relative risk of severe pain in IV 0.94; 95% CI, 0.57-1.6; P = .82. Postoperative plasma acetaminophen levels were higher in oral (22; IQR, 16-28 mg/L) than IV (20; IQR, 17-22 mg/L) group (median difference 7.0; 4.0-8.0 mg/L; P = .0001).

CONCLUSIONS

Opioid-sparing effects did not differ following an oral or standard IV acetaminophen loading dose with no identified acetaminophen toxicity in pediatric patients undergoing tonsillectomy and adenoidectomy who received standardized multimodal postoperative analgesia. An oral loading dose may provide more consistent serum acetaminophen levels at lower cost compared to a standard IV dose.

Application of in vitro data in physiologically-based kinetic models for quantitative in vitro-in vivo extrapolation: A case-study for baclofen

Physiologically-based kinetic (PBK) models can simulate concentrations of chemicals in tissues over time without animal experiments. Nevertheless, in vivo data are often used to parameterise PBK models. This study aims to illustrate that a combination of kinetic and dynamic readouts from in vitro assays can be used to parameterise PBK models simulating neurologically-active concentrations of xenobiotics. Baclofen, an intrathecally administered drug to treat spasticity, was used as a proof-of-principle xenobiotic. An in vitro blood-brain barrier (BBB) model was used to determine the BBB permeability of baclofen needed to simulate plasma and cerebrospinal concentrations. Simulated baclofen concentrations in individuals and populations of adults and children generally fall within 2-fold of measured clinical study concentrations. Further, in vitro micro-electrode array recordings were used to determine the effect of baclofen on neuronal activity (cell signalling). Using quantitative in vitro-in vivo extrapolations (QIVIVE) corresponding doses of baclofen were estimated. QIVIVE showed that up to 4600 times lower intrathecal doses than oral and intravenous doses induce comparable neurological effects. Most simulated doses were in the range of administered doses. This show that PBK models predict concentrations in the central nervous system for various routes of administration accurately without the need for additional in vivo data.

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.

Translational CNS Steady-State Drug Disposition Model in Rats, Monkeys, and Humans for Quantitative Prediction of Brain-to-Plasma and Cerebrospinal Fluid-to-Plasma Unbound Concentration Ratios

Capturing unbound drug exposure in the brain is crucial to evaluate pharmacological effects for drugs acting on the central nervous system. However, to date, there are no reports of validated prediction models to determine the brain-to-plasma unbound concentration ratio (K_p,uu,brain) as well as the cerebrospinal fluid (CSF)-to-plasma unbound concentration ratio (K_p,uu,CSF) between humans and other species. Here, we developed a translational CNS steady-state drug disposition model to predict K_p,uu,brain and K_p,uu,CSF across rats, monkeys, and humans by estimating the relative activity factors (RAF) for MDR1 and BCRP in addition to scaling factors (γ and σ) using the molecular weight, logD, CSF bulk flow, and in vitro transport activities of these transporters. In this study, 68, 26, and 28 compounds were tested in the rat, monkey, and human models, respectively. Both the predicted K_p,uu,brain and K_p,uu,CSF values were within the 3-fold range of the observed values (71, 73, and 79%; 79, 88, and 78% of the compounds, respectively), indicating successful prediction of K_p,uu,brain and K_p,uu,CSF in the three species. The overall predictivity of the RAF approach is consistent with that of the relative expression factor (REF) approach. As the established model can predict K_p,uu,brain and K_p,uu,CSF using only in vitro and physicochemical data, this model would help avoid ethical issues related to animal use and improve CNS drug discovery workflow.

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.

Physiologically based pharmacokinetic/pharmacodynamic model for the prediction of morphine brain disposition and analgesia in adults and children

Morphine is a widely used opioid analgesic, which shows large differences in clinical response in children, even when aiming for equivalent plasma drug concentrations. Age-dependent brain disposition of morphine could contribute to this variability, as developmental increase in blood-brain barrier (BBB) P-glycoprotein (Pgp) expression has been reported. In addition, age-related pharmacodynamics might also explain the variability in effect. To assess the influence of these processes on morphine effectiveness, a multi-compartment brain physiologically based pharmacokinetic/pharmacodynamic (PB-PK/PD) model was developed in R (Version 3.6.2). Active Pgp-mediated morphine transport was measured in MDCKII-Pgp cells grown on transwell filters and translated by an in vitro-in vivo extrapolation approach, which included developmental Pgp expression. Passive BBB permeability of morphine and its active metabolite morphine-6-glucuronide (M6G) and their pharmacodynamic parameters were derived from experiments reported in literature. Model simulations after single dose morphine were compared with measured and published concentrations of morphine and M6G in plasma, brain extracellular fluid (ECF) and cerebrospinal fluid (CSF), as well as published drug responses in children (1 day– 16 years) and adults. Visual predictive checks indicated acceptable overlays between simulated and measured morphine and M6G concentration-time profiles and prediction errors were between 1 and -1. Incorporation of active Pgp-mediated BBB transport into the PB-PK/PD model resulted in a 1.3-fold reduced brain exposure in adults, indicating only a modest contribution on brain disposition. Analgesic effect-time profiles could be described reasonably well for older children and adults, but were largely underpredicted for neonates. In summary, an age-appropriate morphine PB-PK/PD model was developed for the prediction of brain pharmacokinetics and analgesic effects. In the neonatal population, pharmacodynamic characteristics, but not brain drug disposition, appear to be altered compared to adults and older children, which may explain the reported differences in analgesic effect.

Developmental processes in children can affect pharmacokinetics: “what the body does to the drug” as well as pharmacodynamics: “what the drug does to the body”. A typical example is morphine, of which the analgesic response is variable and particularly neonates suffer more often from respiratory depression, even when receiving doses corrected for differences in elimination. One way to mathematically incorporate developmental processes is by employing physiologically based pharmacokinetic/pharmacodynamic (PB-PK/PD) models, where physiological differences between individuals are incorporated. In this study, we developed a morphine PB-PK/PD model to predict brain drug disposition as well as analgesic response in adults and children, as both processes could potentially contribute to developmental variability in the effect of morphine. We found that age-related variation in BBB expression of the main morphine efflux transporter P-glycoprotein was not responsible for differences in brain exposure. In contrast, pharmacodynamic modelling suggested an increased sensitivity to morphine in neonates.

Morphine acts on spinal dynorphin neurons to cause itch through disinhibition

Morphine-induced itch is a very common and debilitating side effect that occurs in laboring women who receive epidural analgesia and in patients who receive spinal morphine for relief of perioperative pain. Although antihistamines are still widely prescribed for the treatment of morphine-induced itch, their use is controversial because the cellular basis for morphine-induced itch remains unclear. Here, we used animal models and show that neuraxial morphine causes itch through neurons and not mast cells. In particular, we found that spinal dynorphin (Pdyn) neurons are both necessary and sufficient for morphine-induced itch in mice. Agonism of the kappa-opioid receptor alleviated morphine-induced itch in mice and nonhuman primates. Thus, our findings not only reveal that morphine causes itch through a mechanism of disinhibition but also challenge the long-standing use of antihistamines, thereby informing the treatment of millions worldwide.

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.

CNS Penetration of Cyclophosphamide and Metabolites in Mice Bearing Group 3 Medulloblastoma and Non-Tumor Bearing Mice

PURPOSE

Cyclophosphamide is widely used to treat children with medulloblastoma; however, little is known about its brain penetration. We performed cerebral microdialysis to characterize the brain penetration of cyclophosphamide (130 mg/kg, IP) and its metabolites [4-hydroxy-cyclophosphamide (4OH-CTX) and carboxyethylphosphoramide mustard (CEPM)] in non-tumor bearing mice and mice bearing orthotopic Group 3 medulloblastoma.

METHODS

A plasma pharmacokinetic study was performed in non-tumor-bearing CD1- nude mice, and four cerebral microdialysis studies were performed in non-tumor-bearing (M1 and M3) and tumor- bearing mice (M2 and M4). Plasma samples were collected up to 6-hours post-dose, and extracellular fluid (ECF) samples were collected over 60-minute intervals for 24-hours post-dose. To stabilize and quantify 4OH-CTX, a derivatizing solution was added in blood after collection, and either directly in the microdialysis perfusate (M1 and M2) or in ECF collection tubes (M3 and M4). Plasma/ECF cyclophosphamide and CEPM, and 4OH-CTX concentrations were separately measured using different LC-MS/MS methods.

RESULTS

All plasma/ECF concentrations were described using a population-based pharmacokinetic model. Plasma exposures of cyclophosphamide, 4OH-CTX, and CEPM were similar across studies (mean AUC=112.6, 45.6, and 80.8 µmol∙hr/L). Hemorrhage was observed in brain tissue when the derivatizing solution was in perfusate compared with none when in collection tubes, which suggested potential sample contamination in studies M1 and M2. Model-derived unbound ECF to plasma partition coefficients (Kp,uu) were calculated to reflect CNS penetration of the compounds. Lower cyclophosphamide Kp,uu was obtained in tumor-bearing mice versus non-tumor bearing mice (mean 0.15 versus 0.22, p=0.019). No differences in Kp,uu were observed between these groups for 4OH- CTX and CEPM (overall mean 0.10 and 0.07).

CONCLUSIONS

Future studies will explore potential mechanisms at the brain-tumor barrier to explain lower cyclophosphamide brain penetration in tumor-bearing mice. These results will be used to further investigate exposure-response relationships in medulloblastoma xenograft models.

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.

Utility of Animal Models to Understand Human Alzheimer's Disease, Using the Mastermind Research Approach to Avoid Unnecessary Further Sacrifices of Animals

To diagnose and treat early-stage (preclinical) Alzheimer’s disease (AD) patients, we need body-fluid-based biomarkers that reflect the processes that occur in this stage, but current knowledge on associated processes is lacking. As human studies on (possible) onset and early-stage AD would be extremely expensive and time-consuming, we investigate the potential value of animal AD models to help to fill this knowledge gap. We provide a comprehensive overview of processes associated with AD pathogenesis and biomarkers, current knowledge on AD-related biomarkers derived from on human and animal brains and body fluids, comparisons of biomarkers obtained in human AD and frequently used animal AD models, and emerging body-fluid-based biomarkers. In human studies, amyloid beta (Aβ), hyperphosphorylated tau (P-tau), total tau (T-tau), neurogranin, SNAP-25, glial fibrillary acidic protein (GFAP), YKL-40, and especially neurofilament light (NfL) are frequently measured. In animal studies, the emphasis has been mostly on Aβ. Although a direct comparison between human (familial and sporadic) AD and (mostly genetic) animal AD models cannot be made, still, in brain, cerebrospinal fluid (CSF), and blood, a majority of similar trends are observed for human AD stage and animal AD model life stage. This indicates the potential value of animal AD models in understanding of the onset and early stage of AD. Moreover, animal studies can be smartly designed to provide mechanistic information on the interrelationships between the different AD processes in a longitudinal fashion and may also include the combinations of different conditions that may reflect comorbidities in human AD, according to the Mastermind Research approach.

Pharmacodynamics and pharmacokinetics in older adults

PURPOSE OF REVIEW

With the growing of the aging population, increased and new methods of anesthesia and surgery allow for surgery and other interventions in older adults.Pharmacokinetics and pharmacodynamics of drugs in older adults differ from those in younger and middle-aged adults. However, the geriatric population is frequently neglected in the context of clinical trials. The present review focuses on the consequences of multimorbidity and pharmacokinetic and pharmacodynamic alterations and their implications on anesthesia.

RECENT FINDINGS

Physiologically based pharmacokinetic and pharmacodynamic modeling may serve as an option to better understand the influence of age on drugs used for anesthesia. However, difficulties to adequately characterize geriatric patients are described.

SUMMARY

Further research of drug effects in the aging population may include physiologically based pharmacokinetic and pharmacodynamic complex models and randomized controlled trials with thoroughly conducted geriatric assessments.

The Brain Exposure Efficiency (BEE) Score

The blood-brain barrier (BBB), composed of microvascular tight junctions and glial cell sheathing, selectively controls drug permeation into the central nervous system (CNS) by either passive diffusion or active transport. Computational techniques capable of predicting molecular brain penetration are important to neurological drug design. A novel prediction algorithm, termed the Brain Exposure Efficiency Score (BEE), is presented. BEE addresses the need to incorporate the role of trans-BBB influx and efflux active transporters by considering key brain penetrance parameters, namely, steady state unbound brain to plasma ratio of drug (K_p,uu) and dose normalized unbound concentration of drug in brain (C_u,b). BEE was devised using quantitative structure-activity relationships (QSARs) and molecular modeling studies on known transporter proteins and their ligands. The developed algorithms are provided as a user-friendly open source calculator to assist in optimizing a brain penetrance strategy during the early phases of small molecule molecular therapeutic design.

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

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

CNS penetration and pharmacodynamics of the CHK1 inhibitor prexasertib in a mouse Group 3 medulloblastoma model

Prexasertib (LY2606368) is a potent and selective small molecule inhibitor of cell-cycle checkpoint CHK1 and CHK2 protein kinases and is currently under clinical evaluation for treatment of pediatric malignancies. As a candidate therapy for pediatric Group 3 medulloblastoma (G3MB), prexasertib CNS penetration was evaluated in mice using cerebral microdialysis and pharmacokinetic modeling. A plasma pharmacokinetic study with a population-based design was performed in CD1 nude mice bearing G3MB orthotopically implanted in the brain and receiving a single dose of prexasertib (10 mg/kg, subcutaneously) to characterize prexasertib disposition and to establish a limited plasma sampling model for the microdialysis studies. The microdialysis studies were performed in both non-tumor bearing mice and in mice bearing G3MB receiving 10 mg/kg prexasertib subcutaneously, for up to 24 h post-dose. Plasma and extracellular fluid (ECF) concentrations were quantified using validated LC MS/MS methods, and analyzed using a population pharmacokinetic model. Model-derived prexasertib tumor/ECF to plasma partition coefficient K_p,uu (ratio of tumor/brain ECF to unbound plasma AUC_0-24 h) was significantly greater in G3MB tumor-bearing mice (0.17 ± 0.08) compared to non-tumor bearing mice (0.09 ± 0.04, p = 0.04). A pharmacodynamic study was then performed in mice bearing G3MB (20 mg/kg, IV) to evaluate prexasertib-induced target engagement after a single dose. Phosphorylated CHK1 serine 345 (pCHK1 S345), phosphorylated Histone 2A variant (γ-H2AX), and cleaved caspase-3 were quantified in mouse G3MB tumor tissues by immunohistochemistry at different time points up to 24 h post-dose. The induction of pCHK1 S345 and γ-H2AX peaked at 2 h after the dose and was elevated above baseline for at least 6 h, reflecting relevant CHK1 inhibition and DNA damage. Cleaved caspase-3 levels increased at 24 h suggesting initiation of cell apoptosis. Adequate unbound prexasertib exposure reached the brain tumor site relative to target engagement in G3MB tumor bearing mice at a clinically relevant dosage. These results support further preclinical and clinical development of prexasertib to treat children with medulloblastoma.

Development of a physiologically-based pharmacokinetic pediatric brain model for prediction of cerebrospinal fluid drug concentrations and the influence of meningitis

Different pediatric physiologically-based pharmacokinetic (PBPK) models have been described incorporating developmental changes that influence plasma drug concentrations. Drug disposition into cerebrospinal fluid (CSF) is also subject to age-related variation and can be further influenced by brain diseases affecting blood-brain barrier integrity, like meningitis. Here, we developed a generic pediatric brain PBPK model to predict CSF concentrations of drugs that undergo passive transfer, including age-appropriate parameters. The model was validated for the analgesics paracetamol, ibuprofen, flurbiprofen and naproxen, and for a pediatric meningitis population by empirical optimization of the blood-brain barrier penetration of the antibiotic meropenem. Plasma and CSF drug concentrations derived from the literature were used to perform visual predictive checks and to calculate ratios between simulated and observed area under the concentration curves (AUCs) in order to evaluate model performance. Model-simulated concentrations were comparable to observed data over a broad age range (3 months–15 years postnatal age) for all drugs investigated. The ratios between observed and simulated AUCs (AUCo/AUCp) were within 2-fold difference both in plasma (range 0.92–1.09) and in CSF (range 0.64–1.23) indicating acceptable model performance. The model was also able to describe disease-mediated changes in neonates and young children (<3m postnatal age) related to meningitis and sepsis (range AUCo/AUCp plasma: 1.64–1.66, range AUCo/AUCp CSF: 1.43–1.73). Our model provides a new computational tool to predict CSF drug concentrations in children with and without meningitis and can be used as a template model for other compounds that passively enter the CNS.

Developmental processes in children affect pharmacokinetics and should ideally be taken into account when establishing drug dosing regimens. One way to incorporate developmental differences is by making use of physiologically-based pharmacokinetic (PBPK) models in which kinetic equations are used to describe drug disposition processes and developmental biology. With these equations the absorption of drugs into the model, the flow of drugs between different compartments (representing major organs/tissues), and excretion from the model are predicted. PBPK models can also be used to describe drug concentrations in different target tissues, which often correlate better with the clinical effects. Here, we developed a generic pediatric PBPK model of drug disposition in the cerebrospinal fluid (CSF), that was able to describe clinically measured drug concentrations of several drugs in neonates and children. The model could be useful in predicting CSF concentrations of other drugs in pediatric populations where clinical data is often sparse or absent and by this means guide first-in-child dose recommendations.

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.

Physiologically-Based Pharmacokinetic Modeling of Fluconazole Using Plasma and Cerebrospinal Fluid Samples From Preterm and Term Infants

Fluconazole is used to treat hematogenous Candida meningoencephalitis in preterm and term infants. To characterize plasma and central nervous system exposure, an adult fluconazole physiologically‐based pharmacokinetic (PBPK) model was scaled to infants, accounting for age dependencies in glomerular filtration and metabolism. The model was optimized using 760 plasma samples from 166 infants (median postmenstrual age (range) 28 weeks (24–50)) and 27 cerebrospinal fluid (CSF) samples from 22 infants (postmenstrual age 28 weeks (24–33)). Simulations evaluated achievement of the surrogate efficacy target of area under the unbound concentration‐time curve ≥ 400 mg • hour/L over the dosing interval in plasma and CSF using dosing guidelines. Average fold error of predicted concentrations was 0.73 and 1.14 for plasma and CSF, respectively. Target attainment in plasma and CSF was reached faster after incorporating a loading dose of 25 mg/kg. PBPK modeling can be useful in exploring CNS kinetics of drugs in children.

Population pharmacokinetics of oxycodone in plasma and cerebrospinal fluid after epidural and intravenous administration

Objectives: To establish the first plasma and cerebrospinal fluid (CSF) oxycodone population pharmacokinetic (PopPK) model after epidural (EPI) and intravenous (IV) oxycodone administration. Methods: The study was conducted with 30 female subjects undergoing elective gynecological surgery with epidural analgesia. A parallel single dose of EPI oxycodone with IV placebo (EPI group; n = 18) or IV oxycodone with EPI placebo (IV group; n = 12) was administered. An epidural catheter for drug administration was placed at T12/L1 and a spinal catheter for CSF sampling at L3/4. Plasma and CSF for oxycodone analysis were frequently collected. A PopPK model was built using the NONMEM software package. Results: Plasma and CSF oxycodone concentrations were evaluated using separate central plasma and CSF compartments and separate peripheral plasma and CSF compartments. Epidural space served as a depot compartment with transfer to both the plasma and CSF central compartments. The population parameters for plasma clearance and apparent distribution volumes for central and peripheral compartments for plasma and CSF were 37.4 L/h, 90.2 L, 68.9 L, 0.035 L (fixed based on literature), and 0.039 L, respectively. Conclusion: A PopPK model was developed and found to precisely and accurately describe oxycodone time-concentration data in plasma and CSF.

A translational platform PBPK model for antibody disposition in the brain

In this manuscript, we have presented the development of a novel platform physiologically-based pharmacokinetic (PBPK) model to characterize brain disposition of mAbs in the mouse, rat, monkey and human. The model accounts for known anatomy and physiology of the brain, including the presence of distinct blood-brain barrier and blood-cerebrospinal fluid (CSF) barrier. CSF and interstitial fluid turnover, and FcRn mediated transport of mAbs are accounted for. The model was first used to characterize published and in-house pharmacokinetic (PK) data on the disposition of mAbs in rat brain, including the data on PK of mAb in different regions of brain determined using microdialysis. Majority of model parameters were fixed based on literature reported values, and only 3 parameters were estimated using rat data. The rat PBPK model was translated to mouse, monkey, and human, simply by changing the values of physiological parameters corresponding to each species. The translated PBPK models were validated by a priori predicting brain PK of mAbs in all three species, and comparing predicted exposures with observed data. The platform PBPK model was able to a priori predict all the validation PK profiles reasonably well (within threefold), without estimating any parameters. As such, the platform PBPK model presented here provides an unprecedented quantitative tool for prediction of mAb PK at the site-of-action in the brain, and preclinical-to-clinical translation of mAbs being developed against central nervous system (CNS) disorders. The proposed model can be further expanded to account for target engagement, disease pathophysiology, and novel mechanisms, to support discovery and development of novel CNS targeting mAbs.

Model systems for studying the blood-brain barrier: Applications and challenges

The blood-brain barrier (BBB) poses a serious impediment to the delivery of effective therapies to the central nervous system (CNS). Over time, various model systems have been crafted and used to evaluate the complexities of the BBB, which includes an impermeable physical barrier and a series of energy-dependent efflux pumps. Models of the BBB have mainly sought to assess changes in endothelial cell permeability, the role of ATP-dependent efflux transporters in drug disposition, and alterations in communication between BBB cells and the microenvironment. In the context of disease, various animal models have been utilized to examine real time BBB drug permeability, CNS dynamic changes, and overall treatment response. In this review, we outline the use of these in vitro and in vivo blood-brain barrier model systems to study normal physiology and diseased states. These current models each have their own advantages and disadvantages for studying the response of biologic processes to physiological and pathological conditions. Additional models are needed to mimic more closely the dynamic quality of the BBB, with the goal focused on potential clinical applications.

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.

Intracellular and Intraorgan Concentrations of Small Molecule Drugs: Theory, Uncertainties in Infectious Diseases and Oncology, and Promise

The distribution of a drug within the body should be considered as involving movement of unbound drug between the various aqueous spaces of the body. At true steady state, even for a compound of restricted lipoidal permeability, unbound concentrations in all aqueous compartments (blood, extracellular, and intracellular) are considered identical, unless a compartment has a clearance/transport process. In contrast, total drug concentrations may differ greatly, reflecting binding or partitioning into constituents of each compartment. For most highly lipid permeable drugs, this uniform unbound concentration is expected to apply. However, many compounds have restricted lipoidal permeability and are subjected to transport/clearance processes causing a gradient between intracellular and extracellular unbound concentrations even at steady state. Additional concerns arise where the drug target resides in a site of limited vascularity. Many misleading assumptions about drug concentrations and access to drug targets are based on total drug. Correction, if made, is usually by measuring tissue binding, but this is limited by the lack of homogenicity of the organ or compartment. Rather than looking for technology to measure the unbound concentration it may be better to focus on designing high lipoidal permeable molecules with a high chance of achieving a uniform unbound drug concentration. It is hoped this paper will stimulate greater understanding of the path from circulation to cell interior, and thereby in part avoid or minimize the need to provide the experimentally very determining, and sometimes still questionable, answer to this problem.

The year in review: progress in brain barriers and brain fluid research in 2018

This editorial focuses on the progress made in brain barrier and brain fluid research in 2018. It highlights some recent advances in knowledge and techniques, as well as prevalent themes and controversies. Areas covered include: modeling, the brain endothelium, the neurovascular unit, the blood–CSF barrier and CSF, drug delivery, fluid movement within the brain, the impact of disease states, and heterogeneity.

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.

Advancing Predictions of Tissue and Intracellular Drug Concentrations Using In Vitro, Imaging and Physiologically Based Pharmacokinetic Modeling Approaches

This white paper examines recent progress, applications, and challenges in predicting unbound and total tissue and intra/subcellular drug concentrations using in vitro and preclinical models, imaging techniques, and physiologically based pharmacokinetic (PBPK) modeling. Published examples, regulatory submissions, and case studies illustrate the application of different types of data in drug development to support modeling and decision making for compounds with transporter-mediated disposition, and likely disconnects between tissue and systemic drug exposure. The goals of this article are to illustrate current best practices and outline practical strategies for selecting appropriate in vitro and in vivo experimental methods to estimate or predict tissue and plasma concentrations, and to use these data in the application of PBPK modeling for human pharmacokinetic (PK), efficacy, and safety assessment in drug development.

Beyond the Blood:Brain Barrier: The Importance of Central Nervous System (CNS) Pharmacokinetics for the Treatment of CNS Tumors, Including Diffuse Intrinsic Pontine Glioma

Over the past decade, we have made considerable progress in establishing diffuse intrinsic pontine glioma (DIPG) as a disease entity and developing preclinical tools to interrogate potential therapeutics. However, translation to improved clinical outcomes in children with DIPG has not yet been realized. This is in part due to difficulties encountered in delivering active drugs adequately to the tumor site. However, most preclinical evaluations gloss over the fundamental concepts of central nervous system (CNS) pharmacokinetics and requirements needed to optimize drug delivery and exposure and translate this into efficacious therapy. This article discusses not only the blood:brain barriers but additional barriers to drug delivery for CNS tumors and pharmacokinetic principles that need to be addressed and considered.

Pharmacokinetic considerations for pediatric patients receiving analgesia in the intensive care unit; targeting postoperative, ECMO and hypothermia patients

INTRODUCTION

Adequate postoperative analgesia in pediatric patients in the intensive care unit (ICU) matters, since untreated pain is associated with negative outcomes. Compared to routine postoperative patients, children undergoing hypothermia (HT) or extracorporeal membrane oxygenation (ECMO), or recovering after cardiac surgery likely display non-maturational differences in pharmacokinetics (PK) and pharmacodynamics (PD). These differences warrant additional dosing recommendations to optimize pain treatment. Areas covered: Specific populations within the ICU will be discussed with respect to expected variations in PK and PD for various analgesics. We hereby move beyond maturational changes and focus on why PK/PD may be different in children undergoing HT, ECMO or cardiac surgery. We provide a stepwise manner to develop PK-based dosing regimens using population PK approaches in these populations. Expert opinion: A one-dose to size-fits-all for analgesia is suboptimal, but for several commonly used analgesics the impact of HT, ECMO or cardiac surgery on average PK parameters in children is not yet sufficiently known. Parameters considering both maturational and non-maturational covariates are important to develop population PK-based dosing advices as part of a strategy to optimize pain treatment.