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

Morphine and hydromorphone pharmacokinetics in human volunteers: population-based modelling of interindividual and opioid-related variability

BACKGROUND

Morphine and hydromorphone have differing onsets, magnitudes, and durations of effects and side-effects. Differences between opioids in their interindividual variabilities in pharmacokinetics and pharmacodynamics might influence rational drug selection. Crossover drug studies can provide more informative interindividual variability data than parallel group studies. Using data from a crossover study of i.v. morphine and hydromorphone in healthy volunteers, we tested the hypothesis that morphine and hydromorphone differ in their interindividual pharmacokinetic variability.

METHODS

Arterial opioid and metabolite concentrations from a randomised crossover study in 51 volunteers receiving a 2-h infusion of hydromorphone (0.05 or 0.1 mg kg-1 i.v.) or morphine (total 0.1 or 0.2 mg kg-1 i.v.) 1-2 weeks apart were evaluated with a three-compartmental model for parent opioid and incorporating glucuronides using population modelling (NONMEM). The primary outcome was interindividual variability in pharmacokinetics, based on the coefficient of variation (%CV) of individual model parameters, calculated as √[exp(ω2)-1]×100 where ω2 is the interindividual variability.

RESULTS

Data were analysed per drug and in a combined morphine-hydromorphone model. Both analyses indicate that interindividual variabilities for hydromorphone and morphine were comparable with %CV ranging from 9% to 31% for structural model parameters (combined analysis). Similarly, additive and relative residual errors had comparable variabilities, 20-40% and 72-87%, respectively, for morphine and hydromorphone (combined analysis).

CONCLUSIONS

Morphine and hydromorphone did not differ in a statistically significant or clinically meaningful manner in their interindividual pharmacokinetic variability. Interindividual pharmacokinetic variability does not appear a meaningful consideration in the choice between these two opioids.

PBPK-PD model for predicting morphine pharmacokinetics, CNS effects and naloxone antagonism in humans

Morphine and morphine-6-glucuronide (M6G) produce central nervous system (CNS) effects by activating mu-opioid receptors, while naloxone is used mainly for the reversal of opioid overdose, specifically for the fatal complication of respiratory depression, but also for alleviating opioid-induced side effects. In this study we developed a physiologically-based pharmacokinetic-pharmacodynamic (PBPK-PD) model to simultaneously predict pharmacokinetics and CNS effects (miosis, respiratory depression and analgesia) of morphine as well as antagonistic effects of naloxone against morphine. The pharmacokinetic and pharmacodynamic parameters were obtained from in vitro data, in silico, or animals. Pharmacokinetic and pharmacodynamic simulations were conducted using 39 and 36 clinical reports, respectively. The pharmacokinetics of morphine and M6G following oral or intravenous administration were simulated, and the PBPK-PD model was validated using clinical observations. The Emax model correlated CNS effects with free concentrations of morphine and M6G in brain parenchyma. The predicted CNS effects were compared with observations. Most clinical observations fell within the 5th-95th percentiles of simulations based on 1000 virtual individuals. Most of the simulated area under the concentration-time curve or peak concentrations also fell within 0.5-2-fold of observations. The contribution of morphine to CNS effects following intravenous or oral administration was larger than that of M6G. Pharmacokinetics and antagonistic effects of naloxone on CNS effects were also successfully predicted using the developed PBPK-PD model. In conclusion, the pharmacokinetics and pharmacodynamics of morphine and M6G, antagonistic effects of naloxone against morphine-induced CNS effects may be successfully predicted using the developed PBPK-PD model based on the parameters derived from in vitro, in silico, or animal studies.

The role of drug efflux and uptake transporters in the plasma pharmacokinetics and tissue disposition of morphine and its main metabolites

Morphine is a widely used opioid for the treatment of pain. Differences in drug transporter expression and activity may contribute to variability in morphine pharmacokinetics and response. Using appropriate mouse models, we investigated the impact of the efflux transporters ABCB1 and ABCG2 and the OATP uptake transporters on the pharmacokinetics of morphine, morphine-3-glucuronide (M3G), and M6G. Upon subcutaneous administration of morphine, its plasma exposure in Abcb1a/1b-/-;Abcg2-/--, Abcb1a/1b-/-;Abcg2-/-;Oatp1a/1b-/-;Oatp2b1-/- (Bab12), and Oatp1a/1b-/-;Oatp2b1-/- mice was similar to that found in wild-type mice. Forty minutes after dosing, morphine brain accumulation increased by 2-fold when mouse (m)Abcb1 and mAbcg2 were ablated. Relative recovery of morphine in small intestinal content was significantly reduced in all the knockout strains. In the absence of mOatp1a/1b and mOatp2b1, plasma levels of M3G were markedly increased, suggesting a lower elimination rate. Moreover, Oatp-deficient mice displayed reduced hepatic and intestinal M3G accumulation. Mouse Oatps similarly affected plasma and tissue disposition of subcutaneously administered M6G. Human OATP1B1/1B3 transporters modestly contribute to the liver accumulation of M6G. In summary, mAbcb1, in combination with mAbcg2, limits morphine brain penetration and its net intestinal absorption. Variation in ABCB1 activity due to genetic polymorphisms/mutations and/or environmental factors might, therefore, partially affect morphine tissue exposure in patients. The ablation of mOatp1a/1b increases plasma exposure and decreases the liver and small intestinal disposition of M3G and M6G. Since the contribution of human OATP1B1/1B3 to M6G liver uptake was quite modest, the risks of undesirable drug interactions or interindividual variation related to OATP activity are likely negligible.

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.

Physiologically Based Pharmacokinetic (PBPK) Model Predictions of Disease Mediated Changes in Drug Disposition in Patients with Nonalcoholic Fatty Liver Disease (NAFLD)

PURPOSE

This study was designed to verify a virtual population representing patients with nonalcoholic fatty liver disease (NAFLD) to support the implementation of a physiologically based pharmacokinetic (PBPK) modeling approach for prediction of disease-related changes in drug pharmacokinetics.

METHODS

A virtual NAFLD patient population was developed in GastroPlus (v.9.8.2) by accounting for pathophysiological changes associated with the disease and proteomics-informed alterations in the abundance of metabolizing enzymes and transporters pertinent to drug disposition. The NAFLD population model was verified using exemplar drugs where elimination is influenced predominantly by cytochrome P450 (CYP) enzymes (chlorzoxazone, caffeine, midazolam, pioglitazone) or by transporters (rosuvastatin, 11C-metformin, morphine and the glucuronide metabolite of morphine).

RESULTS

PBPK model predictions of plasma concentrations of all the selected drugs and hepatic radioactivity levels of 11C-metformin were consistent with the clinically-observed data. Importantly, the PBPK simulations using the virtual NAFLD population model provided reliable estimates of the extent of changes in key pharmacokinetic parameters for the exemplar drugs, with mean predicted ratios (NAFLD patients divided by healthy individuals) within 0.80- to 1.25-fold of the clinically-reported values, except for midazolam (prediction-fold difference of 0.72).

CONCLUSION

A virtual NAFLD population model within the PBPK framework was successfully developed with good predictive capability of estimating disease-related changes in drug pharmacokinetics. This supports the use of a PBPK modeling approach for prediction of the pharmacokinetics of new investigational or repurposed drugs in patients with NAFLD and may help inform dose adjustments for drugs commonly used to treat comorbidities in this patient population.

Physiologically Based Pharmacokinetic Modeling in Neonates: Current Status and Future Perspectives

Rational drug use in special populations is a clinical problem that doctors and pharma-cists must consider seriously. Neonates are the most physiologically immature and vulnerable to drug dosing. There is a pronounced difference in the anatomical and physiological profiles be-tween neonates and older people, affecting the absorption, distribution, metabolism, and excretion of drugs in vivo, ultimately leading to changes in drug concentration. Thus, dose adjustments in neonates are necessary to achieve adequate therapeutic concentrations and avoid drug toxicity. Over the past few decades, modeling and simulation techniques, especially physiologically based pharmacokinetic (PBPK) modeling, have been increasingly used in pediatric drug development and clinical therapy. This rigorously designed and verified model can effectively compensate for the deficiencies of clinical trials in neonates, provide a valuable reference for clinical research design, and even replace some clinical trials to predict drug plasma concentrations in newborns. This review introduces previous findings regarding age-dependent physiological changes and pathological factors affecting neonatal pharmacokinetics, along with their research means. The application of PBPK modeling in neonatal pharmacokinetic studies of various medications is also reviewed. Based on this, we propose future perspectives on neonatal PBPK modeling and hope for its broader application.

Advances in pharmacokinetic-pharmacodynamic modelling for pediatric drug development: extrapolations and exposure-response analyses

INTRODUCTION

Pharmacokinetic (PK)-Pharmacodynamic (PD) and exposure-response (E-R) modeling are critical parts of pediatric drug development. By integrating available knowledge and supportive data to support the design of future studies and pediatric dose selection, these techniques increase the efficiency of pediatric drug development and lowers the risk of exposing pediatric study participants to suboptimal or unsafe dose regimens.

AREAS COVERED

The role of PK, PK-PD and E-R modeling within pediatric drug development and pediatric dose selection is discussed. These models allow investigation of the impact of age and bodyweight on PK and PD in children, despite the often sparse data on the pediatric population. Also discussed is how E-R analyses strengthen the evidence basis to support (full or partial) extrapolation of drug efficacy from adults to children, and between different pediatric age groups.

EXPERT OPINION

Accelerated pediatric drug development and optimized pediatric dosing guidelines are expected from three future developments: (1) Increased focus on E-R modeling of currently approved drugs in children resulting in (novel) E-R modeling techniques and best practices, (2) increased use of real-world data for E-R (3) increased implementation of available population PK and E-R information in pediatric drug dosing guidelines.

Endogenous opiates and behavior: 2021

This paper is the forty-fourth consecutive installment of the annual anthological review of research concerning the endogenous opioid system, summarizing articles published during 2021 that studied the behavioral effects of molecular, pharmacological and genetic manipulation of opioid peptides and receptors as well as effects of opioid/opiate agonizts and antagonists. The review is subdivided into the following specific topics: molecular-biochemical effects and neurochemical localization studies of endogenous opioids and their receptors (1), the roles of these opioid peptides and receptors in pain and analgesia in animals (2) and humans (3), opioid-sensitive and opioid-insensitive effects of nonopioid analgesics (4), opioid peptide and receptor involvement in tolerance and dependence (5), stress and social status (6), learning and memory (7), eating and drinking (8), drug abuse and alcohol (9), sexual activity and hormones, pregnancy, development and endocrinology (10), mental illness and mood (11), seizures and neurologic disorders (12), electrical-related activity and neurophysiology (13), general activity and locomotion (14), gastrointestinal, renal and hepatic functions (15), cardiovascular responses (16), respiration and thermoregulation (17), and immunological responses (18).

Research progress of p38 as a new therapeutic target against morphine tolerance and the current status of therapy of morphine tolerance

With the development of the medical industry, new painkillers continue to appear in people's field of vision, but so far no painkiller can replace morphine. While morphine has a strong analgesic effect, it is also easy to produce pain sensitivity and tolerance. Due to the great inter-individual differences in patient responses, there are few clear instructions on how to optimise morphine administration regimens, which complicates clinicians' treatment strategies and limits the effectiveness of morphine in long-term pain therapy. P38MAPK is a key member of the MAPK family. Across recent years, it has been discovered that p38MAPK rises dramatically in a wide range of morphine tolerance animal models. Morphine tolerance can be reduced or reversed by inhibiting p38MAPK. However, the role and specific mechanism of p38MAPK are not clear. In this review, we synthesise the relevant findings, highlight the function and potential mechanism of p38MAPK in morphine tolerance, as well as the present status and efficacy of morphine tolerance therapy, and underline the future promise of p38MAPK targeted morphine tolerance treatment.

Structure-based virtual screening and molecular dynamics simulation for the identification of sphingosine kinase-2 inhibitors as potential analgesics

Neuropathic pain is due to an injury or disease of the somatosensory nervous system, which accounts for a significant economical and health burden to society. Due to poor understanding of their underlying mechanisms, the available treatments merely provide symptomatic relief and precipitates a variety of adverse effects. This suggests that there is an unmet medical need that must be addressed with effective strategies for the development of novel therapeutics. Sphingosine kinase 2 (SphK2) is an oncogenic lipid kinase that has emerged as a promising target for chronic pain and other diseases. In the present study, we have explored the structure-based virtual high-throughput screening of the Nuclei of Bioassays, Ecophysiology, and Biosynthesis of Natural Products Database (NuBBE) to identify potent natural products as inhibitors of SphK2. A molecular docking study was performed to calculate binding affinities and specificity to identify potential leads against SphK2. Initially, hits were selected by the implementation of absorption, distribution, metabolism, excretion and toxicity properties, Lipinski rule, and PAINS filters. The top-scoring hits also exhibiting an optimal ADMET profile were subjected to MM/GBSA free binding free energy calculation and molecular dynamics simulation. The results from molecular dynamics simulation revealed a stable ligand -SphK2 complex with protein and ligand RMSD within reasonable limits. Overall, we identified compounds, NuBBE_972 and NuBBE_1107 as potential inhibitors of SphK2 with optimal pharmacokinetic properties which have the potential to be developed as novel therapeutics for the management of chronic pain.Communicated by Ramaswamy H. Sarma.

Feasibility of a Pragmatic PBPK Modeling Approach: Towards Model-Informed Dosing in Pediatric Clinical Care

BACKGROUND AND OBJECTIVE

More than half of all drugs are still prescribed off-label to children. Pharmacokinetic (PK) data are needed to support off-label dosing, however for many drugs such data are either sparse or not representative. Physiologically-based pharmacokinetic (PBPK) models are increasingly used to study PK and guide dosing decisions. Building compound models to study PK requires expertise and is time-consuming. Therefore, in this paper, we studied the feasibility of predicting pediatric exposure by pragmatically combining existing compound models, developed e.g. for studies in adults, with a pediatric and preterm physiology model.

METHODS

Seven drugs, with various PK characteristics, were selected (meropenem, ceftazidime, azithromycin, propofol, midazolam, lorazepam, and caffeine) as a proof of concept. Simcyp® v20 was used to predict exposure in adults, children, and (pre)term neonates, by combining an existing compound model with relevant virtual physiology models. Predictive performance was evaluated by calculating the ratios of predicted-to-observed PK parameter values (0.5- to 2-fold acceptance range) and by visual predictive checks with prediction error values.

RESULTS

Overall, model predicted PK in infants, children and adolescents capture clinical data. Confidence in PBPK model performance was therefore considered high. Predictive performance tends to decrease when predicting PK in the (pre)term neonatal population.

CONCLUSION

Pragmatic PBPK modeling in pediatrics, based on compound models verified with adult data, is feasible. A thorough understanding of the model assumptions and limitations is required, before model-informed doses can be recommended for clinical use.

Error traps in acute pain management in children

Providing effective acute pain management to hospitalized children can help improve outcomes, decrease length of stay, and increase patient and parental satisfaction. Error traps (circumstances that lead to erroneous actions or undesirable consequences) can result in inadequately controlled pain, unnecessary side effects, and adverse events. This article highlights five error traps encountered when managing acute pain in children. They include failure to appropriately assess pain, optimally utilize regional anesthesia, select suitable systemic analgesics, identify and treat medication-related side effects, and consider patient characteristics when choosing medication or dosing route. These issues are easily addressed when the clinician is cognizant of ways to anticipate, identify, and mitigate or avoid these errors.

Clinical Implications of Altered Drug Transporter Abundance/Function and PBPK Modeling in Specific Populations: An ITC Perspective

The role of membrane transporters on pharmacokinetics (PKs), drug-drug interactions (DDIs), pharmacodynamics (PDs), and toxicity of drugs has been broadly recognized. However, our knowledge of modulation of transporter expression and/or function in the diseased patient population or specific populations, such as pediatrics or pregnancy, is still emerging. This white paper highlights recent advances in studying the changes in transporter expression and activity in various diseases (i.e., renal and hepatic impairment and cancer) and some specific populations (i.e., pediatrics and pregnancy) with the focus on clinical implications. Proposed alterations in transporter abundance and/or activity in diseased and specific populations are based on (i) quantitative transporter proteomic data and relative abundance in specific populations vs. healthy adults, (ii) clinical PKs, and emerging transporter biomarker and/or pharmacogenomic data, and (iii) physiologically-based pharmacokinetic modeling and simulation. The potential for altered PK, PD, and toxicity in these populations needs to be considered for drugs and their active metabolites in which transporter-mediated uptake/efflux is a major contributor to their absorption, distribution, and elimination pathways and/or associated DDI risk. In addition to best practices, this white paper discusses current challenges and knowledge gaps to study and quantitatively predict the effects of modulation in transporter activity in these populations, together with the perspectives from the International Transporter Consortium (ITC) on future directions.

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.

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.