Development of a Physiologically Based Pharmacokinetic Model for the Rat Central Nervous System and Determination of an In Vitro–In Vivo Scaling Methodology for the Blood–Brain Barrier Permeability of Two Transporter Substrates, Morphine and Oxycodone

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.

Baricitinib and tofacitinib off-target profile, with a focus on Alzheimer's disease

INTRODUCTION

Janus kinase (JAK) inhibitors were recently identified as promising drug candidates for repurposing in Alzheimer's disease (AD) due to their capacity to suppress inflammation via modulation of JAK/STAT signaling pathways. Besides interaction with primary therapeutic targets, JAK inhibitor drugs frequently interact with unintended, often unknown, biological off-targets, leading to associated effects. Nevertheless, the relevance of JAK inhibitors' off-target interactions in the context of AD remains unclear.

METHODS

Putative off-targets of baricitinib and tofacitinib were predicted using a machine learning (ML) approach. After screening scientific literature, off-targets were filtered based on their relevance to AD. Targets that had not been previously identified as off-targets of baricitinib or tofacitinib were subsequently tested using biochemical or cell-based assays. From those, active concentrations were compared to bioavailable concentrations in the brain predicted by physiologically based pharmacokinetic (PBPK) modeling.

RESULTS

With the aid of ML and in vitro activity assays, we identified two enzymes previously unknown to be inhibited by baricitinib, namely casein kinase 2 subunit alpha 2 (CK2-α2) and dual leucine zipper kinase (MAP3K12), both with binding constant (K d) values of 5.8 μM. Predicted maximum concentrations of baricitinib in brain tissue using PBPK modeling range from 1.3 to 23 nM, which is two to three orders of magnitude below the corresponding binding constant.

CONCLUSION

In this study, we extended the list of baricitinib off-targets that are potentially relevant for AD progression and predicted drug distribution in the brain. The results suggest a low likelihood of successful repurposing in AD due to low brain permeability, even at the maximum recommended daily dose. While additional research is needed to evaluate the potential impact of the off-target interaction on AD, the combined approach of ML-based target prediction, in vitro confirmation, and PBPK modeling may help prioritize drugs with a high likelihood of being effectively repurposed for AD.

Highlights

This study explored JAK inhibitors' off-targets in AD using a multidisciplinary approach.We combined machine learning, in vitro tests, and PBPK modelling to predict and validate new off-target interactions of tofacitinib and baricitinib in AD.Previously unknown inhibition of two enzymes (CK2-a2 and MAP3K12) by baricitinib were confirmed using in vitro experiments.Our PBPK model indicates that baricitinib low brain permeability limits AD repurposing.The proposed multidisciplinary approach optimizes drug repurposing efforts in AD research.

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.

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.

Modeling Blood–Brain Barrier Permeability to Solutes and Drugs In Vivo

Our understanding of the pharmacokinetic principles governing the uptake of endogenous substances, xenobiotics, and biologicals across the blood–brain barrier (BBB) has advanced significantly over the past few decades. There is now a spectrum of experimental techniques available in experimental animals and humans which, together with pharmacokinetic models of low to high complexity, can be applied to describe the transport processes at the BBB of low molecular weight agents and macromolecules. This review provides an overview of the models in current use, from initial rate uptake studies over compartmental models to physiologically based models and points out the advantages and shortcomings associated with the different methods. A comprehensive pharmacokinetic profile of a compound with respect to brain exposure requires the knowledge of BBB uptake clearance, intra-brain distribution, and extent of equilibration across the BBB. The application of proper pharmacokinetic analysis and suitable models is a requirement not only in the drug development process, but in all of the studies where the brain uptake of drugs or markers is used to make statements about the function or integrity of the BBB.

IVIVE: Facilitating the Use of In Vitro Toxicity Data in Risk Assessment and Decision Making

During the past few decades, the science of toxicology has been undergoing a transformation from observational to predictive science. New approach methodologies (NAMs), including in vitro assays, in silico models, read-across, and in vitro to in vivo extrapolation (IVIVE), are being developed to reduce, refine, or replace whole animal testing, encouraging the judicious use of time and resources. Some of these methods have advanced past the exploratory research stage and are beginning to gain acceptance for the risk assessment of chemicals. A review of the recent literature reveals a burst of IVIVE publications over the past decade. In this review, we propose operational definitions for IVIVE, present literature examples for several common toxicity endpoints, and highlight their implications in decision-making processes across various federal agencies, as well as international organizations, including those in the European Union (EU). The current challenges and future needs are also summarized for IVIVE. In addition to refining and reducing the number of animals in traditional toxicity testing protocols and being used for prioritizing chemical testing, the goal to use IVIVE to facilitate the replacement of animal models can be achieved through their continued evolution and development, including a strategic plan to qualify IVIVE methods for regulatory acceptance.

Transport Turnover Rates for Human OCT2 and MATE1 Expressed in Chinese Hamster Ovary Cells

MATE1 (multidrug and toxin extruder 1) and OCT2 (organic cation transporter 2) play critical roles in organic cation excretion by the human kidney. The transporter turnover rate (TOR) is relevant to understanding both their transport mechanisms and interpreting the in vitro-in vivo extrapolation (IVIVE) required for physiologically-based pharmacokinetic (PBPK) modeling. Here, we use a quantitative western blot method to determine TORs for MATE1 and OCT2 proteins expressed in CHO cells. MATE1 and OCT2, each with a C-terminal V-5 epitope tag, were cell surface biotinylated and the amount of cell surface MATE1 and OCT2 protein was quantified by western analysis, using standard curves for the V5 epitope. Cell surface MATE1 and OCT2 protein represented 25% and 24%, respectively, of the total expression of these proteins in CHO cells. The number of cell surface transporters was ~55 fmol cm^-2 for MATE1 and ~510 fmol cm^-2 for OCT2. Dividing these values into the different J_max values for transport of MPP, metformin, and atenolol mediated by MATE1 and OCT2 resulted in calculated TOR values (±SE, n = 4) of 84.0 ± 22.0 s^-1 and 2.9 ± 0.6 s^-1; metformin, 461.0 ± 121.0 s^-1 and 12.6 ± 2.4 s^-1; atenolol, 118.0 ± 31.0 s^-1, respectively. These values are consistent with the TOR values determined for a variety of exchangers (NHEs), cotransporters (SGLTs, Lac permease), and uniporters (GLUTs, ENTs).

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.

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.

Gender-based differences in brain and plasma pharmacokinetics of letrozole in sprague-dawley rats: Application of physiologically-based pharmacokinetic modeling to gain quantitative insights

Based on the discovery that the estrogen synthase aromatase (CYP19A1) is abundantly expressed in high- grade gliomas, the aromatase inhibitor, letrozole is being investigated in pre-clinical models as a novel agent against this malignancy. Here, we investigated the systemic and brain pharmacokinetics of letrozole following single and steady state dosing in both male and female Sprague-Dawley rats. Furthermore, we employed physiologically-based pharmacokinetic (PBPK) modeling to gain quantitative insights into the blood-brain barrier penetration of this drug. Letrozole (4 mg/kg) was administered intraperitoneally daily for 5 days (for males) and 11 days (for females) and intracerebral microdialysis was performed for brain extracellular fluid (ECF) collection simultaneously with venous blood sampling. Drug levels were measured using HPLC and non-compartmental analysis was conducted employing WinNonlin®. Simcyp animal simulator was used for conducting bottom-up PBPK approach incorporating the specified multi-compartment brain model. Overall, marked gender-specific differences in the systemic and brain pharmacokinetics of letrozole were observed. Letrozole clearance was much slower in female rats resulting in markedly higher plasma and brain drug concentrations. At steady state, the plasma AUC 0-24 was 103.0 and 24.8 μg*h/ml and brain ECF AUC 0-12 was 24.0 and 4.8 μg*h/ml in female and male rats, respectively. The PBPK model simulated brain concentration profiles were in close agreement with the observed profiles. While gender-specific differences in letrozole PK are not observed in the clinical setting, these findings will guide the dose optimization during pre-clinical investigations of this compound. The PBPK model will serve as an important clinical translational tool.

Profiling and Identification of Omeprazole Metabolites in Mouse Brain and Plasma by Isotope Ratio-Monitoring Liquid Chromatography-Mass Spectrometric Method

Neuro–inflammation is known to be one of the pathogenesis for the degenerative central nervous system (CNS) disease. Recently various approaches for the treatment of brain diseases by controlling neuro-inflammation in the brain have been introduced. In this respect, there is a continuous demand for CNS drugs, which could be safer and more effective. Omeprazole, a well-known proton-pump inhibitor (PPI) is generally prescribed for the treatment of peptic ulcer. In addition to the anti-gastric acid secretion mechanism, recent studies showed that omeprazole or PPIs would likely have anti-inflammation effects in vitro and in vivo, but their effects on anti-inflammation in brain are still unknown. In this study, omeprazole and its metabolites in a mouse’s brain after various routes of administration have been explored by stable isotope ratio-patterning liquid chromatography–mass spectrometric method. First, a simple liquid chromatography–mass spectrometric (LC–MS) method was established for the quantification of omeprazole in mouse plasma and brain. After that, omeprazole and its stable isotope (D3–omeprazole) were concomitantly administered through various routes to mice in order to identify novel metabolites characteristically observed in the mouse brain and were analyzed using a different LC–MS method with information-dependent analysis (IDA) scan. With this unique approach, several new metabolites of omeprazole were identified by the mass difference between omeprazole and stable isotope in both brain and plasma samples. A total of seventeen metabolites were observed, and the observed metabolites were different from each administration route or each matrix (brain or plasma). The brain pharmacokinetic profiles and brain-to-plasma partition coefficient (Kp) were also evaluated in a satellite study. Overall, these results provide better insights to understand the CNS-related biological effects of omeprazole and its metabolites in vivo.

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.

Computational framework for predictive PBPK-PD-Tox simulations of opioids and antidotes

The primary goal of this work was to develop a computational tool to enable personalized prediction of pharmacological disposition and associated responses for opioids and antidotes. Here we present a computational framework for physiologically-based pharmacokinetic (PBPK) modeling of an opioid (morphine) and an antidote (naloxone). At present, the model is solely personalized according to an individual's mass. These PK models are integrated with a minimal pharmacodynamic model of respiratory depression induction (associated with opioid administration) and reversal (associated with antidote administration). The model was developed and validated on human data for IV administration of morphine and naloxone. The model can be further extended to consider different routes of administration, as well as to study different combinations of opioid receptor agonists and antagonists. This work provides the framework for a tool that could be used in model-based management of pain, pharmacological treatment of opioid addiction, appropriate use of antidotes for opioid overdose and evaluation of abuse deterrent formulations.

Scaling behavior of drug transport and absorption in in silico cerebral capillary networks

Drug delivery to the brain is challenging due to the presence of the blood-brain barrier. Mathematical modeling and simulation are essential tools for the deeper understanding of transport processes in the blood, across the blood-brain barrier and within the tissue. Here we present a mathematical model for drug delivery through capillary networks with increasingly complex topologies with the goal to understand the scaling behavior of model predictions on a coarse-to-fine sequence of grids. We apply our model to the delivery of L-Dopa, the primary drug used in the therapy of Parkinson’s Disease. Our model replicates observed blood flow rates and ratios between plasma and tissue concentrations. We propose an optimal network grain size for the simulation of tissue volumes of 1 cm³ that allows to make reliable predictions with reasonable computational costs.

Development of a Region-Specific Physiologically Based Pharmacokinetic Brain Model to Assess Hippocampus and Frontal Cortex Pharmacokinetics

Central nervous system drug discovery and development is hindered by the impermeable nature of the blood-brain barrier. Pharmacokinetic modeling can provide a novel approach to estimate CNS drug exposure; however, existing models do not predict temporal drug concentrations in distinct brain regions. A rat CNS physiologically based pharmacokinetic (PBPK) model was developed, incorporating brain compartments for the frontal cortex (FC), hippocampus (HC), "rest-of-brain" (ROB), and cerebrospinal fluid (CSF). Model predictions of FC and HC C_max, t_max and AUC were within 2-fold of that reported for carbamazepine and phenytoin. The inclusion of a 30% coefficient of variation on regional brain tissue volumes, to assess the uncertainty of regional brain compartments volumes on predicted concentrations, resulted in a minimal level of sensitivity of model predictions. This model was subsequently extended to predict human brain morphine concentrations, and predicted a ROB C_max of 21.7 ± 6.41 ng/mL when compared to "better" (10.1 ng/mL) or "worse" (29.8 ng/mL) brain tissue regions with a FC C_max of 62.12 ± 17.32 ng/mL and a HC C_max of 182.2 ± 51.2 ng/mL. These results indicate that this simplified regional brain PBPK model is useful for forward prediction approaches in humans for estimating regional brain drug concentrations.

Efficient brain uptake of piperine and its pharmacokinetics characterization after oral administration

1. Piperine, the major biological active component in black pepper has been associated with miscellaneous pharmacological effects, especially on central nervous system. To correlate with its neurological activity, a comprehensive pharmacokinetic profile of piperine in brain, plasma and cerebrospinal fluid after oral administration in rats was investigated in this study. 2. It was noted that piperine could efficiently penetrate and homogeneously distribute into brain with similar pharmacokinetics profiles in each region. In addition, piperine concentrations in brain and plasma were found to be comparable with brain to plasma area under curve extrapolated to infinity (AUC_0→∞) ratios of 0.95 and 1.10 for total concentration and unbound concentrations, respectively. Piperine also demonstrated high affinity toward brain tissue (98.4-98.5%) and plasma protein (96.2-97.8%) leading to a brain distribution volume of 36.32 ± 1.40 ml/g brain. Moreover, its efficient membrane permeability (P _app values of 5.41  ±  0.40 × 10^{- 5} cm/s and 4.78  ±  0.16 × 10^{- 5} cm/s for basolateral to apical and apical to basolateral transport in Caco-2 monolayer model) and limited hepatic metabolism (Cl_int of 8.15 μl/min/mg) could also contribute to its quick and high extent brain exposure. 3. In summary, this study for the first time demonstrated high brain penetration potency of piperine could be resulted from its high brain tissue affinity and membrane permeability together with its limited liver metabolism.

The Constraints, Construction, and Verification of a Strain-Specific Physiologically Based Pharmacokinetic Rat Model

The use of in vitro-in vivo extrapolation (IVIVE) techniques, mechanistically incorporated within physiologically based pharmacokinetic (PBPK) models, can harness in vitro drug data and enhance understanding of in vivo pharmacokinetics. This study's objective was to develop a user-friendly rat (250 g, male Sprague-Dawley) IVIVE-linked PBPK model. A 13-compartment PBPK model including mechanistic absorption models was developed, with required system data (anatomical, physiological, and relevant IVIVE scaling factors) collated from literature and analyzed. Overall, 178 system parameter values for the model are provided. This study also highlights gaps in available system data required for strain-specific rat PBPK model development. The model's functionality and performance were assessed using previous literature-sourced in vitro properties for diazepam, metoprolol, and midazolam. The results of simulations were compared against observed pharmacokinetic rat data. Predicted and observed concentration profiles in 10 tissues for diazepam after a single intravenous (i.v.) dose making use of either observed i.v. clearance (CL_iv) or in vitro hepatocyte intrinsic clearance (CL_int) for simulations generally led to good predictions in various tissue compartments. Overall, all i.v. plasma concentration profiles were successfully predicted. However, there were challenges in predicting oral plasma concentration profiles for metoprolol and midazolam, and the potential reasons and according solutions are discussed.

Development of a surrogate matrix for cerebral spinal fluid for liquid chromatography/mass spectrometry based analytical methods

RATIONALE

In recent years, several liquid chromatography/tandem mass spectrometry (LC/MS/MS) methods have been reported for the quantitative determination of drugs and metabolites in cerebral spinal fluid (CSF). Artificial CSF (aCSF) is often used as a surrogate for preparing calibration curves and quality control samples in these methods. However, aCSF does not accurately represent the composition of real CSF because it is missing all of the proteins and lipids, which may alter the electrospray ionization (ESI) response when performing LC/MS/MS analyses. In the current study we compared the mass spectral response of several compounds with a range of physiochemical properties in aCSF (essentially a mixture of salts and buffers), diluted plasma (ranging from 1:5 to 1:200) and real CSF to find the best surrogate for CSF in LC/MS/MS methods.

METHODS

A number of analytes from polar to non-polar, high protein binding to low protein binding, employing different sample preparation methods, were prepared in diluted plasma, actual CSF or aCSF and tested using LC/MS/MS. The analytes included cotinine and its metabolites, quetiapine, norquetiapine, chlorpromazine, efavirenz and lamivudine. The similarity of MS responses from these compounds in aCSF and diluted plasma to CSF was assessed by comparing the slopes of the calibration curves generated from using linear regression modeling.

RESULTS

For all compounds, the lowest percent difference in response ratio (0 to 17%) was observed from 1:200 diluted plasma. Our results indicated that, irrespective of the inherent physiochemical properties of the analytes or the method of sample preparation, 1:200 diluted plasma performed as the best surrogate for CSF in LC/MS/MS methods.

CONCLUSIONS

The percent difference in response ratio has been established to demonstrate how different compounds behave between CSF, aCSF and dilute plasma. Although among the compounds tested some of them showed a very similar MS response in actual and aCSF, there were analytes that demonstrated significant differences in ESI-MS signal when sprayed from these two matrices. However, even in such cases, 1:200 diluted plasma generated results with no significant difference from CSF. Therefore, we recommend that in order to develop robust and dependable bioanalytical LC/MS methods from CSF samples, it is more appropriate to prepare calibration curves and quality control samples in diluted plasma instead of aCSF. Copyright © 2016 John Wiley & Sons, Ltd.

Signaled drug delivery and transport across the blood-brain barrier

We use a mathematical model to describe the delivery of a drug to a specific region of the brain. The drug is carried by liposomes that can release their cargo by application of focused ultrasound (US). Thereupon, the drug is absorbed through the endothelial cells that line the brain capillaries and form the physiologically important blood-brain barrier (BBB). We present a compartmental model of a capillary that is able to capture the complex binding and transport processes the drug undergoes in the blood plasma and at the BBB. We apply this model to the delivery of levodopa (L-dopa, used to treat Parkinson's disease) and doxorubicin (an anticancer agent). The goal is to optimize the delivery of drug while at the same time minimizing possible side effects of the US.

Treating disorders of the neonatal central nervous system: pharmacokinetic and pharmacodynamic considerations with a focus on antiepileptics

A major consideration in the treatment of neonatal disorders is that the selected drug, dose and dosage frequency is safe, effective and appropriate for the intended patient population. Thus, a thorough knowledge of the pharmacokinetics and pharmacodynamics of the chosen drug within the patient population is essential. In paediatric and neonatal populations two additional challenges can often complicate drug treatment - the inherently greater physiological variability, and a lack of robust clinical evidence of therapeutic range. There has traditionally been an overreliance in paediatric medicine on extrapolating doses from adult values by adjusting for bodyweight or body surface area, but many other sources of variability exist which complicate the choice of dose in neonates. The lack of reliable drug dosage data in neonates has been highlighted by regulatory authorities, as only ~50% of the most commonly used paediatric medicines have been examined in a paediatric population. Moreover, there is a paucity of information on the pharmacokinetic parameters which affect drug concentrations in different body tissues, and pharmacodynamic responses to drugs in the neonate. Thus, in the present review, we draw attention to the main pharmacokinetic factors that influence the unbound brain concentration of neuroactive drugs. Moreover, the pharmacodynamic differences between neonates and adults that affect the activity of centrally-acting therapeutic agents are briefly examined, with a particular emphasis on antiepileptic drugs.

Quantitative aspects of drug permeation across in vitro and in vivo barriers

The kinetics of permeation across epithelial and endothelial cell sheets and across cell membranes is determinant for the pharmacokinetics of a drug. In vitro transport experiments with cultured cells or artificial barriers have tremendously improved the predictability of the in vivo behaviour of tested compounds. This article focuses on the parameters and calculation methods that are used to describe permeation quantitatively, with a focus on in vitro experiments and the prediction of intestinal absorption and blood-brain barrier passage. It shows under which in vitro experimental conditions standard calculations are adequate and under which conditions equations should be adapted to the experimental details. The impact of volume differences between donor and receiver compartments, pH gradients, addition of albumin, accumulation in the barrier and unidirectional transport by an efflux transporter on the results is shown in simulations. The article should make researchers aware of experimental factors that affect the outcome of a permeation experiment and how to account for this during data analysis. Finally, strategies to predict the in vivo behaviour of a compound based on the in vitro data are discussed. The goal of the article is to support researchers in choosing experimental conditions and calculation methods that deliver appropriate and reproducible results in permeation studies in vitro.

Endogenous opiates and behavior: 2013

This paper is the thirty-sixth consecutive installment of the annual review of research concerning the endogenous opioid system. It summarizes papers published during 2013 that studied the behavioral effects of molecular, pharmacological and genetic manipulation of opioid peptides, opioid receptors, opioid agonists and opioid antagonists. The particular topics that continue to be covered include the molecular-biochemical effects and neurochemical localization studies of endogenous opioids and their receptors related to behavior, and the roles of these opioid peptides and receptors in pain and analgesia; stress and social status; tolerance and dependence; learning and memory; eating and drinking; alcohol and drugs of abuse; sexual activity and hormones, pregnancy, development and endocrinology; mental illness and mood; seizures and neurologic disorders; electrical-related activity and neurophysiology; general activity and locomotion; gastrointestinal, renal and hepatic functions; cardiovascular responses; respiration and thermoregulation; and immunological responses.

Development and application of a multiroute physiologically based pharmacokinetic model for oxytetracycline in dogs and humans

Oxytetracycline (OTC) is a commonly used tetracycline antibiotic in veterinary and human medicine. To establish a quantitative model for predicting OTC plasma and tissue exposure, a permeability-limited multiroute physiologically based pharmacokinetic model was developed in dogs. The model was calibrated with plasma pharmacokinetic data in beagle dogs following single intravenous (5 mg/kg), oral (100 mg/kg), and intramuscular (20 mg/kg) administrations. The model predicted other available dog data well, including drug concentrations in the liver, kidney, and muscle after repeated exposure, and data in the mixed-breed dog. The model was extrapolated to humans and the human model adequately simulated measured plasma OTC concentrations after intravenous (7.14 mg/kg) and oral exposures (6.67 mg/kg). The dog model was applied to predict 24-h OTC area-under-the-curve after three therapeutic treatments. Results were 27.75, 51.76, and 64.17 μg/mL*h in the plasma, and 120.93, 225.64, and 279.67 μg/mL*h in the kidney for oral (100 mg/kg), intravenous (10 mg/kg), and intramuscular (20 mg/kg) administrations, respectively. This model can be used to predict plasma and tissue concentrations to aid in designing optimal therapeutic regimens with OTC in veterinary, and potentially, human medicine; and as a foundation for scaling to other tetracycline antibiotics and to other animal species. © 2014 Wiley Periodicals, Inc. and the American Pharmacists Association J Pharm Sci 104:233-243, 2015.

Rationalizing underprediction of drug clearance from enzyme and transporter kinetic data: from in vitro tools to mechanistic modeling

Over the years, there has been an increase in the number and quality of available in vitro tools for the assessment of clearance. Complexity of data analysis and modelling of corresponding in vitro data has increased in an analogous manner, in particular for the simultaneous characterization of transporter and metabolism kinetics, together with intracellular binding and passive diffusion. In the current chapter, the impact of different factors on the in vitro-in vivo extrapolation of clearance will be addressed in a stepwise manner, from the selection of the most adequate in vitro system and experimental design/condition to the corresponding modelling of data generated. The application of static or physiologically based pharmacokinetic models in the prediction of clearance will be discussed, highlighting limitations and current challenges of some of the approaches. Particular focus will be on the ability of in vitro and in silico predictive tools to overcome the trend of clearance underprediction. Improvements made as a result of inclusion of extrahepatic metabolism and consideration of transporter-metabolism interplay across different organs will be discussed.

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.

Development of a physiologically-based pharmacokinetic model of the rat central nervous system

Central nervous system (CNS) drug disposition is dictated by a drug's physicochemical properties and its ability to permeate physiological barriers. The blood-brain barrier (BBB), blood-cerebrospinal fluid barrier and centrally located drug transporter proteins influence drug disposition within the central nervous system. Attainment of adequate brain-to-plasma and cerebrospinal fluid-to-plasma partitioning is important in determining the efficacy of centrally acting therapeutics. We have developed a physiologically-based pharmacokinetic model of the rat CNS which incorporates brain interstitial fluid (ISF), choroidal epithelial and total cerebrospinal fluid (CSF) compartments and accurately predicts CNS pharmacokinetics. The model yielded reasonable predictions of unbound brain-to-plasma partition ratio (Kpuu,brain) and CSF:plasma ratio (CSF:Plasmau) using a series of in vitro permeability and unbound fraction parameters. When using in vitro permeability data obtained from L-mdr1a cells to estimate rat in vivo permeability, the model successfully predicted, to within 4-fold, Kpuu,brain and CSF:Plasmau for 81.5% of compounds simulated. The model presented allows for simultaneous simulation and analysis of both brain biophase and CSF to accurately predict CNS pharmacokinetics from preclinical drug parameters routinely available during discovery and development pathways.

Methodologies to assess drug permeation through the blood-brain barrier for pharmaceutical research

The drug discovery process for drugs that target the central nervous system suffers from a very high rate of failure due to the presence of the blood-brain barrier, which limits the entry of xenobiotics into the brain. To minimise drug failure at different stages of the drug development process, new methodologies have been developed to understand the absorption, distribution, metabolism, excretion and toxicity (ADMET) profile of drug candidates at early stages of drug development. Additionally, understanding the permeation of drug candidates is also important, particularly for drugs that target the central nervous system. During the first stages of the drug discovery process, in vitro methods that allow for the determination of permeability using high-throughput screening methods are advantageous. For example, performing the parallel artificial membrane permeability assay followed by cell-based models with interesting hits is a useful technique for identifying potential drugs. In silico models also provide interesting information but must be confirmed by in vitro models. Finally, in vivo models, such as in situ brain perfusion, should be studied to reduce a large number of drug candidates to a few lead compounds. This article reviews the different methodologies used in the drug discovery and drug development processes to determine the permeation of drug candidates through the blood-brain barrier.

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.

ITC recommendations for transporter kinetic parameter estimation and translational modeling of transport-mediated PK and DDIs in humans

This white paper provides a critical analysis of methods for estimating transporter kinetics and recommendations on proper parameter calculation in various experimental systems. Rational interpretation of transporter-knockout animal findings and application of static and dynamic physiologically based modeling approaches for prediction of human transporter-mediated pharmacokinetics and drug-drug interactions (DDIs) are presented. The objective is to provide appropriate guidance for the use of in vitro, in vivo, and modeling tools in translational transporter science.