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

Personalized Dosing of Medicines for Children: A Primer on Pediatric Pharmacometrics for Clinicians

The widespread use of drugs for unapproved purposes remains common in children, primarily attributable to practical, ethical, and financial constraints associated with pediatric drug research. Pharmacometrics, the scientific discipline that involves the application of mathematical models to understand and quantify drug effects, holds promise in advancing pediatric pharmacotherapy by expediting drug development, extending applications, and personalizing dosing. In this review, we delineate the principles of pharmacometrics, and explore its clinical applications and prospects. The fundamental aspect of any pharmacometric analysis lies in the selection of appropriate methods for quantifying pharmacokinetics and pharmacodynamics. Population pharmacokinetic modeling is a data-driven method ('top-down' approach) to approximate population-level pharmacokinetic parameters, while identifying factors contributing to inter-individual variability. Model-informed precision dosing is increasingly used to leverage population pharmacokinetic models and patient data, to formulate individualized dosing recommendations. Physiologically based pharmacokinetic models integrate physicochemical drug properties with biological parameters ('bottom-up approach'), and is particularly valuable in situations with limited clinical data, such as early drug development, assessing drug-drug interactions, or adapting dosing for patients with specific comorbidities. The effective implementation of these complex models hinges on strong collaboration between clinicians and pharmacometricians, given the pivotal role of data availability. Promising advancements aimed at improving data availability encompass innovative techniques such as opportunistic sampling, minimally invasive sampling approaches, microdialysis, and in vitro investigations. Additionally, ongoing research efforts to enhance measurement instruments for evaluating pharmacodynamics responses, including biomarkers and clinical scoring systems, are expected to significantly bolster our capacity to understand drug effects in children.

Predictions of Bedaquiline Central Nervous System Exposure in Patients with Tuberculosis Meningitis Using Physiologically based Pharmacokinetic Modeling

BACKGROUND AND OBJECTIVE

The use of bedaquiline as a treatment option for drug-resistant tuberculosis meningitis (TBM) is of interest to address the increased prevalence of resistance to first-line antibiotics. To this end, we describe a whole-body physiologically based pharmacokinetic (PBPK) model for bedaquiline to predict central nervous system (CNS) exposure.

METHODS

A whole-body PBPK model was developed for bedaquiline and its metabolite, M2. The model included compartments for brain and cerebrospinal fluid (CSF). Model predictions were evaluated by comparison to plasma PK time profiles following different dosing regimens and sparse CSF concentrations data from patients. Simulations were then conducted to compare CNS and lung exposures to plasma exposure at clinically relevant dosing schedules.

RESULTS

The model appropriately described the observed plasma and CSF bedaquiline and M2 concentrations from patients with pulmonary tuberculosis (TB). The model predicted a high impact of tissue binding on target site drug concentrations in CNS. Predicted unbound exposures within brain interstitial exposures were comparable with unbound vascular plasma and unbound lung exposures. However, unbound brain intracellular exposures were predicted to be 7% of unbound vascular plasma and unbound lung intracellular exposures.

CONCLUSIONS

The whole-body PBPK model for bedaquiline and M2 predicted unbound concentrations in brain to be significantly lower than the unbound concentrations in the lung at clinically relevant doses. Our findings suggest that bedaquiline may result in relatively inferior efficacy against drug-resistant TBM when compared with efficacy against drug-resistant pulmonary TB.

Quantification of meropenem in serum and cerebrospinal fluid in children with bacterial meningitis with augmented renal clearance by UPLC-MS/MS

Meropenem is an ultrabroad-spectrum antimicrobial agent that is often recommended for the treatment of bacterial meningitis (BM) in children. However, a subtherapeutic phenomenon occurred in BM children complicated with augmented renal clearance (ARC) at the recommended dose of meropenem. To support its pharmacokinetics, a sensitive, fast and robust ultra-liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) method was developed to measure meropenem concentrations in serum and cerebrospinal fluid (CSF). The method involved protein precipitation, and samples were diluted with a large proportion of water to eliminate solvent effects. The separation of samples was performed on a Waters Acquity™ BEH C18 column (2.1 × 50 mm i.d., 1.7 μm) with a gradient profile. The mobile phases were formic acid-water (1:1000, v/v) and acetonitrile. The linear range was good, with a concentration range of 0.100-100 μg/mL for serum and 0.0400-20.0 μg/mL for CSF. The intra-day and inter-day precisions were less than 8.0%, and the intra-day and inter-day accuracies varied -6.6% from 6.5% for the both serum and CSF. The selectivity, carry-over, dilution integrity, matrix effect, recovery and stability were validated according to international guidelines. The developed UPLC-MS/MS method successfully determined the meropenem concentrations in the serum and CSF of children with BM complicated with ARC. The results indicated that under the recommended dosing regimen (40 mg/kg every 8 h), the time to reach the effective treatment target of 50%T > MIC was only approximately 3 h and lower CSF concentrations of meropenem were observed in children with BM with ARC.

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.

Development of a physiologically based toxicokinetic model for lead in pregnant women: The role of bone tissue in the maternal and fetal internal exposure

Epidemiological studies have shown associations between prenatal exposure to lead (Pb) and neurodevelopmental effects in young children. Prenatal exposure is generally characterized by measuring the concentration in the umbilical cord at delivery or in the maternal blood during pregnancy. To assess internal Pb exposure during prenatal life, we developed a pregnancy physiologically based pharmacokinetic (p-PBPK) model that to simulates Pb levels in blood and target tissues in the fetus, especially during critical periods for brain development. An existing Pb PBPK model was adapted to pregnant women and fetuses. Using data from literature, both the additional maternal bone remodeling, that causes Pb release into the blood, and the Pb placental transfers were estimated by Bayesian inference. Additional maternal bone remodeling was estimated to start at 21.6 weeks. Placental transfers were estimated between 4.6 and 283 L.day-1 at delivery with high interindividual variability. Once calibrated, the p-PBPK model was used to simulate fetal exposure to Pb. Internal fetal exposure greatly varies over the pregnancy with two peaks of Pb levels in blood and brain at the end of the 1st and 3rd trimesters. Sensitivity analysis shows that the fetal blood lead levels are affected by the maternal burden of bone Pb via maternal bone remodeling and by fetal bone formation at different pregnancy stages. Coupling the p-PBPK model with an effect model such as an adverse outcome pathway could help to predict the effects on children's neurodevelopment.

Physiologically-Based Pharmacokinetic Modelling to Predict the Pharmacokinetics and Pharmacodynamics of Linezolid in Adults and Children with Tuberculous Meningitis

Linezolid is used off-label for treatment of central nervous system infections. However, its pharmacokinetics and target attainment in cranial cerebrospinal fluid (CSF) in tuberculous meningitis patients is unknown. This study aimed to predict linezolid cranial CSF concentrations and assess attainment of pharmacodynamic (PD) thresholds (AUC:MIC of >119) in plasma and cranial CSF of adults and children with tuberculous meningitis. A physiologically based pharmacokinetic (PBPK) model was developed to predict linezolid cranial CSF profiles based on reported plasma concentrations. Simulated steady-state PK curves in plasma and cranial CSF after linezolid doses of 300 mg BID, 600 mg BID, and 1200 mg QD in adults resulted in geometric mean AUC:MIC ratios in plasma of 118, 281, and 262 and mean cranial CSF AUC:MIC ratios of 74, 181, and 166, respectively. In children using ~10 mg/kg BID linezolid, AUC:MIC values at steady-state in plasma and cranial CSF were 202 and 135, respectively. Our model predicts that 1200 mg per day in adults, either 600 mg BID or 1200 mg QD, results in reasonable (87%) target attainment in cranial CSF. Target attainment in our simulated paediatric population was moderate (56% in cranial CSF). Our PBPK model can support linezolid dose optimization efforts by simulating target attainment close to the site of TBM disease.

Efficacy and Safety of NSAIDs in Infants: A Comprehensive Review of the Literature of the Past 20 Years

Non-steroidal anti-inflammatory drugs (NSAIDs) are commonly used in infants, children, and adolescents worldwide; however, despite sufficient evidence of the beneficial effects of NSAIDs in children and adolescents, there is a lack of comprehensive data in infants. The present review summarizes the current knowledge on the safety and efficacy of various NSAIDs used in infants for which data are available, and includes ibuprofen, dexibuprofen, ketoprofen, flurbiprofen, naproxen, diclofenac, ketorolac, indomethacin, niflumic acid, meloxicam, celecoxib, parecoxib, rofecoxib, acetylsalicylic acid, and nimesulide. The efficacy of NSAIDs has been documented for a variety of conditions, such as fever and pain. NSAIDs are also the main pillars of anti-inflammatory treatment, such as in pediatric inflammatory rheumatic diseases. Limited data are available on the safety of most NSAIDs in infants. Adverse drug reactions may be renal, gastrointestinal, hematological, or immunologic. Since NSAIDs are among the most frequently used drugs in the pediatric population, safety and efficacy studies can be performed as part of normal clinical routine, even in young infants. Available data sources, such as (electronic) medical records, should be used for safety and efficacy analyses. On a larger scale, existing data sources, e.g. adverse drug reaction programs/networks, spontaneous national reporting systems, and electronic medical records should be assessed with child-specific methods in order to detect safety signals pertinent to certain pediatric age groups or disease entities. To improve the safety of NSAIDs in infants, treatment needs to be initiated with the lowest age-appropriate or weight-based dose. Duration of treatment and amount of drug used should be regularly evaluated and maximum dose limits and other recommendations by the manufacturer or expert committees should be followed. Treatment for non-chronic conditions such as fever and acute (postoperative) pain should be kept as short as possible. Patients with chronic conditions should be regularly monitored for possible adverse effects of NSAIDs.

Physiologically based pharmacokinetic (PBPK) modeling of flurbiprofen in different CYP2C9 genotypes

The aim of this study was to establish the physiologically based pharmacokinetic (PBPK) model of flurbiprofen related to CYP2C9 genetic polymorphism and describe the pharmacokinetics of flurbiprofen in different CYP2C9 genotypes. PK-Sim® software was used for the model development and validation. A total of 16 clinical pharmacokinetic data for flurbiprofen in different CYP2C9 genotypes, dose regimens, and age groups were used for the PBPK modeling. Turnover number (k_cat) of CYP2C9 values were optimized to capture the observed profiles in different CYP2C9 genotypes. In the simulation, predicted fraction metabolized by CYP2C9, fraction excreted to urine, bioavailability, and volume of distribution were similar to previously reported values. Predicted plasma concentration-time profiles in different CYP2C9 genotypes were visually similar to the observed profiles. Predicted AUC_inf in CYP2C9*1/*2, CYP2C9*1/*3, and CYP2C9*3/*3 genotypes were 1.44-, 2.05-, and 3.67-fold higher than the CYP2C9*1/*1 genotype. The ranges of fold errors for AUC_inf, C_max, and t_1/2 were 0.84-1.00, 0.61-1.22, and 0.74-0.94 in development and 0.59-0.98, 0.52-0.97, and 0.61-1.52 in validation, respectively, which were within the acceptance criterion. Thus, the PBPK model was successfully established and described the pharmacokinetics of flurbiprofen in different CYP2C9 genotypes, dose regimens, and age groups. The present model could guide the decision-making of tailored drug administration strategy by predicting the pharmacokinetics of flurbiprofen in various clinical scenarios.

A Permeability- and Perfusion-based PBPK model for Improved Prediction of Concentration-time Profiles

To improve predictions of concentration‐time (C‐t) profiles of drugs, a new physiologically based pharmacokinetic modeling framework (termed ‘PermQ’) has been developed. This model includes permeability into and out of capillaries, cell membranes, and intracellular lipids. New modeling components include (i) lumping of tissues into compartments based on both blood flow and capillary permeability, and (ii) parameterizing clearances in and out of membranes with apparent permeability and membrane partitioning values. Novel observations include the need for a shallow distribution compartment particularly for bases. C‐t profiles were modeled for 24 drugs (7 acidic, 5 neutral, and 12 basic) using the same experimental inputs for three different models: Rodgers and Rowland (RR), a perfusion‐limited membrane‐based model (K_p,mem), and PermQ. K_p,mem and PermQ can be directly compared since both models have identical tissue partition coefficient parameters. For the 24 molecules used for model development, errors in V_ss and t_1/2 were reduced by 37% and 43%, respectively, with the PermQ model. Errors in C‐t profiles were reduced (increased EOC) by 43%. The improvement was generally greater for bases than for acids and neutrals. Predictions were improved for all 3 models with the use of parameters optimized for the PermQ model. For five drugs in a test set, similar results were observed. These results suggest that prediction of C‐t profiles can be improved by including capillary and cellular permeability components for all tissues.

Efficacy of Vancomycin and Meropenem in Central Nervous System Infections in Children and Adults: Current Update

The current antimicrobial therapy of bacterial infections of the central nervous system (CNS) in adults and pediatric patients is faced with many pitfalls as the drugs have to reach necessary levels in serum and cross the blood-brain barrier. Furthermore, several studies report that different factors such as the structure of the antimicrobial agent, the severity of disease, or the degree of inflammation play a significant role. Despite the available attempts to establish pharmacokinetic (PK) modeling to improve the required dosing regimen for adults and pediatric patients, conclusive recommendations for the best therapeutic strategies are still lacking. For instance, bacterial meningitis, the most common CNS infections, and ventriculitis, a severe complication of meningitis, are still associated with 10% and 30% mortality, respectively. Several studies report on the use of vancomycin and meropenem to manage meningitis and ventriculitis; therefore, this review aims to shed light on the current knowledge about their use in adults and pediatric patients. Consequently, studies published from 2015 until mid-July 2021 are included, and data about the study population, levels of drugs in serum and cerebrospinal fluid (CSF), and measured PK data in serum and CSF are provided. The overall aim is to provide the readers a recent reference that summarizes the pitfalls and success of the current therapy and emphasizes the importance of performing more studies to improve the clinical outcome of the current therapeutical approach.

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.

Physiologically Based Pharmacokinetic Models Are Effective Support for Pediatric Drug Development

Pediatric drug development faces many difficulties. Traditionally, pediatric drug doses are simply calculated linearly based on the body weight, age, and body surface area of adults. Due to the ontogeny of children, this simple linear scaling may lead to drug overdose in pediatric patients. The physiologically based pharmacokinetic (PBPK) model, as a mathematical model, contributes to the research and development of pediatric drugs. An example of a PBPK model guiding drug dose selection in pediatrics has emerged and has been approved by the relevant regulatory agencies. In this review, we discuss the principle of the PBPK model, emphasize the necessity of establishing a pediatric PBPK model, introduce the absorption, distribution, metabolism, and excretion of the pediatric PBPK model, and understand the various applications and related prospects of the pediatric PBPK model.

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.

Differences in P-glycoprotein activity in human and rodent blood-brain barrier assessed by mechanistic modelling

Variation in the efficacy and safety of central nervous system drugs between humans and rodents can be explained by physiological differences between species. An important factor could be P-glycoprotein (Pgp) activity in the blood–brain barrier (BBB), as BBB expression of this drug efflux transporter is reportedly lower in humans compared to mouse and rat and subject to an age-dependent increase. This might complicate animal to human extrapolation of brain drug disposition and toxicity, especially in children. In this study, the potential species-specific effect of BBB Pgp activity on brain drug exposure was investigated. An age-dependent brain PBPK model was used to predict cerebrospinal fluid and brain mass concentrations of Pgp substrate drugs. For digoxin, verapamil and quinidine, in vitro kinetic data on their transport by Pgp were derived from literature and used to scale to in vivo parameters. In addition, age-specific digoxin transport was simulated for children with a postnatal age between 25 and 81 days. BBB Pgp activity in the model was optimized using measured CSF data for the Pgp substrates ivermectin, indinavir, vincristine, docetaxel, paclitaxel, olanzapine and citalopram, as no useful in vitro data were available. Inclusion of Pgp activity in the model resulted in optimized predictions of their brain concentration. Total brain-to-plasma AUC values (Kp,brain) in the simulations without Pgp were divided by the Kp,brain values with Pgp. Kp ratios ranged from 1 to 45 for the substrates investigated. Comparison of human with rodent Kp,brain ratios indicated ≥ twofold lower values in human for digoxin, verapamil, indinavir, paclitaxel and citalopram and ≥ twofold higher values for vincristine. In conclusion, BBB Pgp activity appears species-specific. An age-dependent PBPK model-based approach could be useful to extrapolate animal data to human adult and paediatric predictions by taking into account species-specific and developmental BBB Pgp expression.

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.

Ampicillin Pharmacokinetics During First Week of Life in Preterm and Term Neonates

BACKGROUND AND AIMS

Ampicillin is 1 of the most commonly used antibiotics for treatment of early onset sepsis, but its pharmacokinetics (PK) is poorly characterized. We aimed to define the dose of ampicillin for late preterm and term neonates by evaluating its PK in serum, cerebrospinal (CSF), and epithelial lining fluid.

METHODS

A prospective study included neonates receiving ampicillin for suspected or proven early onset sepsis and pneumonia. PK samples were collected at steady state, at predose and 5 minutes, 1 hour, 3 hours, 8 hours, and 12 hours after ampicillin 3-minute infusion. Ampicillin concentrations were measured by ultra-high-performance liquid chromatography. Noncompartmental anaysis (NCA) and population pharmacokinetic (pop-PK) modeling were performed and probability of therapeutic target attainment was simulated.

RESULTS

In 14 neonates (GA of 32-42 wks; mean BW 2873 g), PK parameters (mean ± SD) in NCA were the following: half-life 7.21 ± 7.97 hours; volume of distribution (Vd) 1.07 ± 0.51 L; clearance (CL) 0.20 ± 0.13 L/h; 24-hour area under the concentration-time curve 348.92 ± 114.86 mg*h/L. In pop-PK analysis, a 2-compartmental model described the data most adequately with the final parameter estimates of CL 15.15 (CV 40.47%) L/h/70kg; central Vd 24.87 (CV 37.91%) L/70kg; intercompartmental CL 0.39 (CV 868.56) L/h and peripheral Vd 1.039 (CV 69.32%) L. Peutic target attainment simulations demonstrated that a dosage of 50 mg/kg q 12 hours attained 100% fT > MIC 0.25 mg/L, group B streptococcal breakpoint.

CONCLUSIONS

We recommend ampicillin dosage 50 mg/kg q 12 hours for neonates with gestational age ≥32 weeks during the first week of life.

Overcoming the shortcomings of the extended-clearance concept: a framework for developing a physiologically-based pharmacokinetic (PBPK) model to select drug candidates involving transporter-mediated clearance

Introduction:Human pharmacokinetic (PK) prediction can be a significant challenge to drug candidates undergoing transporter-mediated clearance, when only animal data and in vitro human parameters are available in the drug discovery stage.Areas covered:The extended clearance concept (ECC) that incorporates the processes of hepatic uptake, passive diffusion, metabolism and biliary secretion has been adapted to determine the rate-determining process of hepatic clearance and drug-drug interactions (DDIs). However, since the ECC is derived from the well-stirred model and does not consider the liver as a drug distribution organ to reflect the time-dependent variation of drug concentrations between the liver and plasma, it can be misused for compound selection in drug discovery.Expert opinion:The PBPK model consists of a set of differential equations of drug mass balance, and can overcome the shortcomings of the ECC in predicting human PK. The predictability, relevance and reliability of the model and the scaling factors for IVIVE must be validated using either the measured liver concentrations or DDI data with known transporter inhibitors, or both, in monkeys. A human PBPK model that incorporates in vitro human data and SFs obtained from the validated monkey PBPK model can be used for compound selection in the drug discovery phase.

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.

Preparation of solid dispersion systems for enhanced dissolution of poorly water soluble diacerein: In-vitro evaluation, optimization and physiologically based pharmacokinetic modeling

Diacerein (DCN), a BCS II compound, suffers from poor aqueous solubility and limited bioavailability. Solid dispersion systems (SD) of DCN were prepared by solvent evaporation, using hydrophilic polymers. In-vitro dissolution studies were performed and dissolution parameters were evaluated. I-Optimal factorial design was employed to study the effect of formulation variables (drug:polymer ratio and polymer type) on the measured responses including; drug content (DC) (%), dissolution efficiency at 15 min (DE _{(15 min)}%) and 60 min (DE _{(60 min)}%) and mean dissolution time (MDT) (min). The optimized SD was selected, prepared and evaluated, allowing 10.83 and 3.42 fold increase in DE _{(15 min)}%, DE _{(60 min)}%, respectively and 6.07 decrease in MDT, compared to plain drug. DSC, XRD analysis and SEM micrographs confirmed complete amorphization of DCN within the optimized SD. Physiologically based pharmacokinetic (PBPK) modeling was employed to predict PK parameters of DCN in middle aged healthy adults and geriatrics. Simcyp^® software established in-vivo plasma concentration time curves of the optimized SD, compared to plain DCN. Relative bioavailability of the optimized SD compared to plain drug was 229.52% and 262.02% in healthy adults and geriatrics, respectively. Our study reports the utility of PBPK modeling for formulation development of BCS II APIs, via predicting their oral bio-performance.

Innovative approaches in CNS clinical drug development: Quantitative systems pharmacology

Clinical trials involving brain disorders are notoriously difficult to set up and run. Innovative ways to develop effective prevention and treatment strategies for central nervous system (CNS) diseases are urgently needed. New approaches that are likely to renew or at least modify the paradigms used so far have been recently proposed. Quantitative systems pharmacology (QSP) uses mathematical computerized models to characterize biological systems, disease processes and CNS drug pharmacology. Integrated experimental medicine should increase the probability and predictability of success while controlling clinical trials costs. Finally, the societal perspective and patient empowerment also offer additional approaches to demonstrate the benefit of a new drug in the CNS field.

Approaches to Dose Finding in Neonates, Illustrating the Variability between Neonatal Drug Development Programs

Drug dosing in neonates should be based on integrated knowledge concerning the disease to be treated, the physiological characteristics of the neonate, and the pharmacokinetics (PK) and pharmacodynamics (PD) of a given drug. It is critically important that all sources of information be leveraged to optimize dose selection for neonates. Sources may include data from adult studies, pediatric studies, non-clinical (juvenile) animal models, in vitro studies, and in silico models. Depending on the drug development program, each of these modalities could be used to varying degrees and with varying levels of confidence to guide dosing. This paper aims to illustrate the variability between neonatal drug development programs for neonatal diseases that are similar to those seen in other populations (meropenem), neonatal diseases related but not similar to pediatric or adult populations (clopidogrel, thyroid hormone), and diseases unique to neonates (caffeine, surfactant). Extrapolation of efficacy from older children or adults to neonates is infrequently used. Even if a disease process is similar between neonates and children or adults, such as with anti-infectives, additional dosing and safety information will be necessary for labeling, recognizing that dosing in neonates is confounded by maturational PK in addition to body size.

Preclinical models to optimize treatment of tuberculous meningitis - A systematic review

Tuberculous meningitis (TBM) is the most devastating form of TB, resulting in death or neurological disability in up to 50% of patients affected. Treatment is similar to that of pulmonary TB, despite poor cerebrospinal fluid (CSF) penetration of the cornerstone anti-TB drug rifampicin. Considering TBM pathology, it is critical that optimal drug concentrations are reached in the meninges, brain and/or the surrounding CSF. These type of data are difficult to collect in TBM patients. This review aims to identify and describe a preclinical model representative for human TBM which can provide the indispensable data needed for future pharmacological characterization and prioritization of new TBM regimens in the clinical setting. We reviewed existing literature on treatment of TBM in preclinical models: only eight articles, all animal studies, could be identified. None of the animal models completely recapitulated human disease and in most of the animal studies key pharmacokinetic data were missing, making the comparison with human exposure and CNS distribution, and the study of pharmacokinetic-pharmacodynamic relationships impossible. Another 18 articles were identified using other bacteria to induce meningitis with treatment including anti-TB drugs (predominantly rifampicin, moxifloxacin and levofloxacin). Of these articles the pharmacokinetics, i.e. plasma exposure and CSF:plasma ratios, of TB drugs in meningitis could be evaluated. Exposures (except for levofloxacin) agreed with human exposures and also most CSF:plasma ratios agreed with ratios in humans. Considering the lack of an ideal preclinical pharmacological TBM model, we suggest a combination of 1. basic physicochemical drug data combined with 2. in vitro pharmacokinetic and efficacy data, 3. an animal model with adequate pharmacokinetic sampling, microdialysis or imaging of drug distribution, all as a base for 4. physiologically based pharmacokinetic (PBPK) modelling to predict response to TB drugs in treatment of TBM.

Development and Evaluation of Physiologically Based Pharmacokinetic Drug-Disease Models for Predicting Rifampicin Exposure in Tuberculosis and Cirrhosis Populations

The physiologically based pharmacokinetic (PBPK) approach facilitates the construction of novel drug–disease models by allowing incorporation of relevant pathophysiological changes. The aim of the present work was to explore and identify the differences in rifampicin pharmacokinetics (PK) after the application of its single dose in healthy and diseased populations by using PBPK drug–disease models. The Simcyp^® simulator was used as a platform for modeling and simulation. The model development process was initiated by predicting rifampicin PK in healthy population after intravenous (i.v) and oral administration. Subsequent to successful evaluation in healthy population, the pathophysiological changes in tuberculosis and cirrhosis population were incorporated into the developed model for predicting rifampicin PK in these populations. The model evaluation was performed by using visual predictive checks and the comparison of mean observed/predicted ratios (ratio_(Obs/pred)) of the PK parameters. The predicted PK parameters in the healthy population were in adequate harmony with the reported clinical data. The incorporation of pathophysiological changes in albumin concentration in the tuberculosis population revealed improved prediction of clearance. The developed PBPK drug–disease models have efficiently described rifampicin PK in tuberculosis and cirrhosis populations after administering single drug dose, as the ratio_(Obs/pred) for all the PK parameters were within a two-fold error range. The mechanistic nature of the developed PBPK models may facilitate their extension to other diseases and drugs.