Development of a physiologically based pharmacokinetic model of fostemsavir and its pivotal application to support dosing in pregnancy.

It is critical to understand the impact of significant physiological changes during pregnancy on the extent of maternal and fetal drug exposure. Fostemsavir (FTR) is a prodrug of temsavir (TMR) and is approved in combination with other antiretrovirals for multi-drug-resistant human immunodeficiency virus (HIV) infections. This physiologically based pharmacokinetic model (PBPK) study was used to estimate TMR PK in pregnant populations during each trimester of pregnancy to inform FTR dosing. A PBPK model was developed and validated for TMR using PK data collected following intravenous TMR and oral FTR dosing (immediate-release and extended-release tablets) in healthy volunteers. Predicted TMR concentration-time profiles accurately predicted the reported clinical data and variability in healthy (dense data) and pregnant (sparse data) populations. Predicted versus observed TMR geometric mean (CV%) clearance following intravenous administration was 18.01 (29) versus 17 (21) (L/h). Predicted versus observed TMR AUC0-inf (ng.h/mL) in healthy volunteers following FTR administration of the extended-release tablet were 9542 (66) versus 7339 (33). The validated TMR PBPK model was then applied to predict TMR PK in a population of pregnant individuals during each trimester. Simulations showed TMR AUC in pregnant individuals receiving FTR 600 mg twice daily was decreased by 25% and 38% in the second and third trimesters, respectively. However, TMR exposure remained within the range observed in nonpregnant adults with no need for dose adjustment. The current PBPK model can also be applied for the prediction of local tissue concentrations and drug-drug interactions in pregnancy.

Development and verification of mechanistic vaginal absorption and metabolism model to predict systemic exposure after vaginal ring and gel application.

AIMS: The current work describes the development of mechanistic vaginal absorption and metabolism model within Simcyp Simulator to predict systemic concentrations following vaginal application of ring and gel formulations. METHODS: Vaginal and cervix physiology parameters were incorporated in the model development. The study highlights the model assumptions including simulation results comparing systemic concentrations of 5 different compounds, namely, dapivirine, tenofovir, lidocaine, ethinylestradiol and etonogestrel, administered as vaginal ring or gel. Due to lack of data, the vaginal absorption parameters were calculated based on assumptions or optimized. The model uses release rate/in vitro release profiles with formulation characteristics to predict drug mass transfer across vaginal tissue into the systemic circulation. RESULTS: For lidocaine and tenofovir vaginal gel, the predicted to observed AUC0-t and Cmax ratios were well within 2-fold error limits. The average fold error (AFE) and absolute AFE indicating bias and precision of predictions range from 0.62 to 1.61. For dapivirine, the pharmacokinetic parameters are under and overpredicted in some studies due to lack of formulation composition details and relevance of release rate used in ring model. The predicted to observed AUC0-t and Cmax ratios were well within 2-fold error limits for etonogestrel and ethinylestradiol vaginal ring (AFEs and absolute AFEs from 0.84 to 1.83). CONCLUSION: The current study provides first of its kind physiologically based pharmacokinetic framework integrating physiology, population and formulation data to carry out in silico mechanistic vaginal absorption studies, with the potential for virtual bioequivalence assessment in the future.

Physiologically based pharmacokinetic modeling for development and applications of a virtual celiac disease population using felodipine as a model drug.

In celiac disease (CeD), gastrointestinal CYP3A4 abundance and morphology is affected by the severity of disease. Therefore, exposure to CYP3A4 substrates and extent of drug interactions is altered. A physiologically-based pharmacokinetic (PBPK) population for different severities of CeD was developed. Gastrointestinal physiology parameters, such as luminal pH, transit times, morphology, P-gp, and CYP3A4 expression were included in development of the CeD population. Data on physiological difference between healthy and CeD subjects were incorporated into the model as the ratio of celiac to healthy. A PBPK model was developed and verified for felodipine extended-release tablet in healthy volunteers (HVs) and then utilized to verify the CeD populations. Plasma concentration-time profile and PK parameters were predicted and compared against those observed in both groups. Sensitivity analysis was carried out on key system parameters in CeD to understand their impact on drug exposure. For felodipine, the predicted mean concentration-time profiles and 5th and 95th percentile intervals captured the observed profile and variability in the HV and CeD populations. Predicted and observed clearance was 56.9 versus 56.1 (L/h) in HVs. Predicted versus observed mean ± SD area under the curve for extended release felodipine in different severities of CeD were values of 14.5 ± 9.6 versus 14.4 ± 2.1, 14.6 ± 9.0 versus 17.2 ± 2.8, and 28.1 ± 13.5 versus 25.7 ± 5.0 (ng.h/mL), respectively. Accounting for physiology differences in a CeD population accurately predicted the PK of felodipine. The developed CeD population can be applied for determining the drug concentration of CYP3A substrates in the gut as well as for systemic levels, and for application in drug-drug interaction studies.

Multi-phase multi-layer mechanistic dermal absorption (MPML MechDermA) model to predict local and systemic exposure of drug products applied on skin.

Physiologically-based pharmacokinetic models combine knowledge about physiology, drug product properties, such as physicochemical parameters, absorption, distribution, metabolism, excretion characteristics, formulation attributes, and trial design or dosing regimen to mechanistically simulate drug pharmacokinetics (PK). The current work describes the development of a multiphase, multilayer mechanistic dermal absorption (MPML MechDermA) model within the Simcyp Simulator capable of simulating uptake and permeation of drugs through human skin following application of drug products to the skin. The model was designed to account for formulation characteristics as well as body site- and sex- population variability to predict local and systemic bioavailability. The present report outlines the structure and assumptions of the MPML MechDermA model and includes results from simulations comparing absorption at multiple body sites for two compounds, caffeine and benzoic acid, formulated as solutions. Finally, a model of the Feldene (piroxicam) topical gel, 0.5% was developed and assessed for its ability to predict both plasma and local skin concentrations when compared to in vivo PK data.

Development and application of a pediatric mechanistic kidney model.

Pediatric physiologically-based pharmacokinetic (P-PBPK) models have been used to predict age related changes in the pharmacokinetics (PKs) of renally cleared drugs mainly in relation to changes in glomerular filtration rate. With emerging data on ontogeny of renal transporters, mechanistic models of renal clearance accounting for the role of active and passive secretion should be developed and evaluated. Data on age-related physiological changes and ontogeny of renal transporters were applied into a mechanistic kidney within a P-PBPK model. Plasma concentration-time profile and PK parameters of cimetidine, ciprofloxacin, metformin, tenofovir, and zidovudine were predicted in subjects aged 1 day to 18 years. The predicted and observed plasma concentration-time profiles and PK parameters were compared. The predicted concentration-time profile means and 5th and 95th percent intervals generally captured the observed data and variability in various studies. Overall, based on drugs and age bands, predicted to observed clearance were all within two-fold and in 11 of 16 cases within 1.5-fold. Predicted to observed area under the curve (AUC) and maximum plasma concentration (Cmax ) were within two-fold in 12 of 14 and 12 of 15 cases, respectively. Predictions in neonates and early infants (up to 14 weeks postnatal age) were reasonable with 15-20 predicted PK parameters within two-fold of the observed. ciprofloxacin but not zidovudine PK predictions were sensitive to basal kidney uptake transporter ontogeny. The results indicate that a mechanistic kidney model accounting for physiology and ontogeny of renal processes and transporters can predict the PK of renally excreted drugs in children. Further data especially in neonates are required to verify the model and ontogeny profiles.

Development of a Virtual Chinese Pediatric Population Physiological Model Targeting Specific Metabolism and Kidney Elimination Pathways.

Background: Physiologically based pharmacokinetic (PBPK) modeling and simulating may be a powerful tool in predicting drug behaviors in specific populations. It is a mathematical model that relates the pharmacokinetic (PK) profile of a compound with human anatomical characteristics, physiological characteristics, and biochemical parameters. Predictions using PBPK models offer a promising way to guide drug development and can be used to optimize clinical dosing regimens. However, PK data of new drugs in the pediatric population are too limited to guide clinical therapy, which may lead to frequent adverse events or insufficient efficacy for pediatric patients, particularly in neonates and infants. Objective: The objective of this study was to establish a virtual Chinese pediatric population based on the physiological parameters of Chinese children that could be utilized in PBPK models. Methods: A Chinese pediatric PBPK model was developed in Simcyp Simulator by collecting published Chinese pediatric physiological and anthropometric data to use as system parameters. This pediatric population model was then evaluated in the Chinese pediatric population by predicting the pharmacokinetic characteristics of four probe drugs: theophylline (major CYP1A2 substrate), fentanyl (major CYP3A4 substrate), vancomycin, and ceftazidime (renal-eliminated). Results: The predicted maximum concentration (Cmax), area under the curve of concentration-time (AUC), and clearance (CL) for theophylline (CYP1A2 metabolism pathway) and fentanyl (CYP3A4 metabolism pathway) were within two folds of the observed data. For drugs mainly eliminated by renal clearance (vancomycin and ceftazidime) in the Chinese pediatric population, the ratio of prediction to observation for major PK parameters was within a 2-fold error range. Conclusion: The model is a supplement to the previous Chinese population PBPK model. We anticipate the model to be a better representative of the pediatric Chinese population for drugs PK, offering greater clinical precision for medication given to the pediatric population, ultimately advancing clinical development of pediatric drugs. We can refine this model further by collecting more physiological parameters of Chinese children.

Does "Birth" as an Event Impact Maturation Trajectory of Renal Clearance via Glomerular Filtration? Reexamining Data in Preterm and Full-Term Neonates by Avoiding the Creatinine Bias.

Glomerular filtration rate (GFR) is an important measure of renal function. Various models for its maturation have recently been compared; however, these have used markers, which are subject to different renal elimination processes. Inulin clearance data (a purer probe of GFR) collected from the literature were used to determine age-related changes in GFR aspects of renal drug excretion in pediatrics. An ontogeny model was derived using a best-fit model with various combinations of covariates such as postnatal age, gestational age at birth, and body weight. The model was applied to the prediction of systemic clearance of amikacin, gentamicin, vancomycin, and gadobutrol. During neonatal life, GFR increased as a function of both gestational age at birth and postnatal age, hence implying an impact of birth and a discrepancy in GFR for neonates with the same postmenstrual age depending on gestational age at birth (ie, neonates who were outside the womb longer had higher GFR, on average). The difference in GFR between pre-term and full-term neonates with the same postmenstrual age was negligible from beyond 1.25 years. Considering both postnatal age and gestational age at birth in GFR ontogeny models is important because postmenstrual age alone ignores the impact of birth. Most GFR models use covariates of body size in addition to age. Therefore, prediction from these models will also depend on the change in anthropometric characteristics with age. The latter may not be similar in various ethnic groups, and this makes the head-to-head comparison of models very challenging.

Potential drug-drug interactions in hospitalized pediatric patients with respiratory disorders: a retrospective review of clinically important interactions.

Background Hospitalized pediatric patients are at an increased risk of experiencing potential drug-drug interactions (pDDIs) due to polypharmacy and the unlicensed and off-label administration of drugs. The aim of this study is to characterize clinically significant pDDIs in pediatric patients hospitalized in a tertiary respiratory center. Methods A retrospective analysis of medications prescribed to pediatric patients admitted to the pediatric ward (PW) and pediatric intensive care unit (PICU) of a respiratory referral center was carried out over a six-month period. The pDDIs were identified using the Lexi-Interact database and considered as clinically relevant according to the severity rating as defined in the database. Frequency, drug classes, mechanisms, clinical managements, and risk factors were recorded for these potential interactions. Results Eight hundred and forty-five pDDIs were identified from the analysis of 176 prescriptions. Of the total pDDIs, 10.2% in PW and 14.6% in PICU were classified as clinically significant. Anti-infective agents and central nervous system drugs were the main drug classes involved in clinically significant pDDIs as object and/or precipitant drugs. A higher number of medications [odds ratio (OR): 4.8; 95% confidence interval (CI): 2.0-11.4; p < 0.001] and the existence of a nonrespiratory disease, which led to a respiratory disorder (OR: 3.8; 95% CI: 1.40-10.4; p < 0.05), were the main risk factors associated with an increased incidence of pDDIs. Conclusions A high and similar risk of pDDIs exists in pediatric patients with respiratory disorders hospitalized in PW and PICU. The patients prescribed a higher number of medications and presenting respiratory symptoms induced by a nonrespiratory disease require extra care and monitoring. Pediatricians should be educated about clinically significant DDIs for highly prescribed medications in their settings in order to take preventive measures and safeguard patient safety.

Physiologically based pharmacokinetic modelling to guide drug delivery in older people.

Older patients are generally not included in Phase 1 clinical trials despite being the population group who use the largest number of prescription medicines. Physiologically based pharmacokinetic (PBPK) modelling provides an understanding of the absorption and disposition of drugs in older patients. In this review, PBPK models used for the prediction of absorption and exposure of drugs after parenteral, oral and transdermal administration are discussed. Comparisons between predicted drug pharmacokinetics (PK) and observed PK are presented to illustrate the accuracy of the predictions by the PBPK models and their potential use in informing clinical trial design and dosage adjustments in older patients. In addition, a case of PBPK modelling of a bioequivalence study on two controlled release products is described, where PBPK predictions reproduced the study showing bioequivalence in healthy volunteers but not in older subjects with achlorhydria, indicating further utility in prospectively identifying challenges in bioequivalence studies.

Considering Age Variation When Coining Drugs as High versus Low Hepatic Extraction Ratio.

The hepatic extraction ratio (EH) is commonly considered an "inherent attribute" of drug. It determines the main physiological and biological elements of the system (patient attributes) that are most significant in interindividual variability of clearance. The EH consists of three age-dependent parameters: fraction of unbound drug in blood (fu.B), hepatic intrinsic clearance of unbound drug (CLu.int,H), and hepatic blood flow (QH). When the age-effects on these elements are not proportional, a given drug may shift from so-called high extraction status to low extraction. To demonstrate the impact of age-related changes on fu.B, CLu int,H, and QH, the EH of midazolam and two hypothetical drugs with 10-fold higher and 10-fold lower CLu.int,H than midazolam were investigated in pediatrics based on known ontogeny functions. The EH was simulated using Simcyp software, version 14. This was then complemented by a comprehensive literature survey to identify the commonly applied covariates in pediatric population pharmacokinetic (PopPK) studies. Midazolam EH decreased from 0.6 in adults to 0.02 at birth, making its clearance much more susceptible to changes in CLu.int,H and fu.B than in adults and reducing the impact of QH on clearance. The drug with 10-fold higher CLu.int,H was categorized as high extraction from 4 days old onward whereas the drug with 10-fold lower CLu.int,H remained low extraction from birth to adulthood. Approximately 50% of collected PopPK studies (n = 120) did not consider interaction between age and other covariates. Interaction between covariates and age should be considered as part of studies involving younger pediatric patients. The EH cannot be considered an inherent drug property without considering the effect of age.

A re-evaluation and validation of ontogeny functions for cytochrome P450 1A2 and 3A4 based on in vivo data.

BACKGROUND AND OBJECTIVES: Current cytochrome P450 (CYP) 1A2 and 3A4 ontogeny profiles, which are derived mainly from in vitro studies and incorporated in paediatric physiologically based pharmacokinetic models, have been reported to under-predict the in vivo clearances of some model substrates in neonates and infants. METHOD: We report ontogeny functions for these enzymes as paediatric to adult relative intrinsic clearance per mg of hepatic microsomal protein, based on the deconvolution of in vivo pharmacokinetic data and by accounting for the impact of known clinical condition on hepatic unbound intrinsic clearance for caffeine and theophylline as markers of CYP1A2 activity and for midazolam as a marker of CYP3A4 activity. RESULTS: The function for CYP1A2 describes an increase in relative intrinsic metabolic clearance from birth to 3 years followed by a decrease to adult values. The function for CYP3A4 describes a continuous rise in relative intrinsic metabolic clearance, reaching the adult value at about 1.3 years of age. The new models were validated by showing improved predictions of the systemic clearances of ropivacaine (major CYP1A2 substrate; minor CYP3A4 substrate) and alfentanil (major CYP3A4 substrate) compared with those using a previous ontogeny function based on in vitro data (alfentanil: mean squared prediction error 3.0 vs. 6.8; ropivacaine: mean squared prediction error 2.3 vs.14.2). CONCLUSIONS: When implementing enzyme ontogeny functions, it is important to consider potential confounding factors (e.g. disease) that may affect the physiological conditions of the patient and, hence, the prediction of net in vivo clearance.

Precision criteria to derive sample size when designing pediatric pharmacokinetic studies: which measure of variability should be used?

A new approach for calculation of sample size in pediatric clinical pharmacokinetic studies was suggested based on desired precision for a pharmacokinetic parameter of interest. The estimate of variability for sample size calculations could be obtained from different sources. It is not known whether these sources constantly show higher/lower variability across compounds and age groups. We obtained estimates of variability for clearance, volume of distribution and area under the plasma concentration-time curve for 5 drugs from adult/pediatric classic clinical pharmacokinetic studies, and physiologically based pharmacokinetics (PBPK) combined with in vitro-in vivo extrapolation. Estimates were applied to the proposal methodology for non-compartmental analysis. Sample size was different for each drug based on various estimates of variability from different pharmacokinetic parameters and depending on the age. Overall, there was no consistent discrepancy in sample size calculated according to the source of variability. A conservative approach should be taken when using "precision based methodology" knowing that various sources of initial estimates of variability will not lead to similar sample size calculations. Although PBPK simulations could be used for estimating variability, further work is required to investigate the best approach to estimate variability of pharmacokinetic parameters in pediatric populations and hence sample size calculations.

Do children have the same vulnerability to metabolic drug­drug interactions as adults? A critical analysis of the literature.

Many drug­drug interactions (DDIs) in the pediatric population are managed based on data generated in adults. However, due to developmental changes in elimination pathways from birth to adolesence, and variable weight­adjusted dose of interacting drugs, the assumption of DDIs being similar in adults and pediatrics might not be correct. This study compares the magnitude of reported DDIs in pediatric and adult populations. A systematic literature review was undertaken to identify reports of DDIs in pediatric subjects. A total of 145 reports of DDIs were identified over the age range of birth to 20 years. The magnitude of DDIs for 24 drug pairs from 31 different pediatric studies could be assessed and compared with those in adults where corresponding data existed. The magnitude of the DDI, as measured by a relevant parameter (e.g., AUC, CL) in the presence and absence of inhibitor,were higher (>1.25­fold), similar (0.8­ to 1.25­fold) or lower (<0.8­fold) than the corresponding ratio in adults in 10, 15, and 8 cases respectively. An age­related trend in the magnitude of DDIs could not be established. However, the study highlighted the clear paucity of the data in children younger than 2 years. Care should be exercised when applying the knowledge of DDIs from adults to children younger than 2 years of age.

Age related changes in fractional elimination pathways for drugs: assessing the impact of variable ontogeny on metabolic drug-drug interactions.

The magnitude of any metabolic drug-drug interactions (DDIs) depends on fractional importance of inhibited pathway which may not necessarily be the same in young children when compared to adults. The ontogeny pattern of cytochrome P450 (CYP) enzymes (CYPs 1A2, 2B6, 2C8, 2C9, 2C18/19, 2D6, 2E1, 3A4) and renal function were analyzed systematically. Bootstrap methodology was used to account for variability, and to define the age range over which statistical differences existed between each pair of specific pathways. A number of DDIs were simulated (Simcyp Pediatric v12) for virtual compounds to highlight effects of age on fractional elimination and consequent magnitude of DDI. For a theoretical drug metabolized 50% by each of CYP2D6 and CYP3A4 pathways at birth, co-administration of ketoconazole (3 mg/kg) resulted in a 1.65-fold difference between inhibited versus uninhibited AUC compared to 2.4-fold in 1 year olds and 3.2-fold in adults. Conversely, neonates could be more sensitive to DDI than adults in certain scenarios. Thus, extrapolation from adult data may not be applicable across all pediatric age groups. The use of pediatric physiologically based pharmacokinetic (p-PBPK) models may offer an interim solution to uncovering potential periods of vulnerability to DDI where there are no existing clinical data derived from children.