Application of Physiologically-Based and Population Pharmacokinetic Modeling for Dose Finding and Confirmation During the Pediatric Development of Moxifloxacin

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.

Physiologically based pharmacokinetic modelling of semaglutide in children and adolescents with healthy and obese body weights

AIMS

To develop paediatric physiologically based pharmacokinetic modelling (PBPK) models of semaglutide to estimate the pharmacokinetic profile for subcutaneous injections in children and adolescents with healthy and obese body weights.

METHODS

Pharmacokinetic modelling and simulations of semaglutide subcutaneous injections were performed using the Transdermal Compartmental Absorption & Transit model implemented in GastroPlus v.9.5 modules. A PBPK model of semaglutide was developed and verified in the adult population, by comparing the simulated plasma exposure with the observed data, and further scaled to the paediatric populations with normal and obese body weight.

RESULTS

The semaglutide PBPK model was successfully developed in adults and scaled to the paediatric population. Our paediatric PBPK simulations indicated a significant increase in maximum plasma concentrations for the 10-14 years' paediatric population with healthy body weights, which was higher than the observed values in adults at the reference dose. Since gastrointestinal adverse events are related to increased semaglutide concentrations, peak concentrations outside the target range may represent a safety risk for this paediatric age group. Besides, paediatric PBPK models indicated that body weight was inversely related to semaglutide maximum plasma concentration, corroborating the consensus on the influence of body weight on semaglutide PK in adults.

CONCLUSION

Paediatric PBPK was successfully achieved using a top-down approach and drug-related parameters. The development of unprecedented PBPK models will support paediatric clinical therapy for applying aid-safe dosing regimens for the paediatric population in diabetes treatment.

Application of Modelling and Simulation Approaches to Predict Pharmacokinetics of Therapeutic Monoclonal Antibodies in Pediatric Population

Ethical regulations and limited paediatric participants are key challenges that contribute to a median delay of 6 years in paediatric mAb approval. To overcome these barriers, modelling and simulation methodologies have been adopted to design optimized paediatric clinical studies and reduce patient burden. The classical modelling approach in paediatric pharmacokinetic studies for regulatory submissions is to apply body weight-based or body surface area-based allometric scaling to adult PK parameters derived from a popPK model to inform the paediatric dosing regimen. However, this approach is limited in its ability to account for the rapidly changing physiology in paediatrics, especially in younger infants. To overcome this limitation, PBPK modelling, which accounts for the ontogeny of key physiological processes in paediatrics, is emerging as an alternative modelling strategy. While only a few mAb PBPK models have been published, PBPK modelling shows great promise demonstrating a similar prediction accuracy to popPK modelling in an Infliximab paediatric case study. To facilitate future PBPK studies, this review consolidated comprehensive data on the ontogeny of key physiological processes in paediatric mAb disposition. To conclude, this review discussed different use-cases for pop-PK and PBPK modelling and how they can complement each other to increase confidence in pharmacokinetic predictions.

Develop adult extrapolation to pediatrics and pediatric dose optimization based on the physiological pharmacokinetic model of azithromycin

Physiologically-based pharmacokinetic (PBPK) models are more frequently used for supporting pediatric dose selection in small-molecule drugs. Through literature research, drug parameters of azithromycin and clinical data from different studies were obtained. Through parameter optimization of the absorption and dissolution process, the adult intravenous model was extended to the adult oral model. The adult intravenous and oral PBPK models are precise to meet the AAFE<2 standard, and the pharmacokinetic parameters of the predicted values of the model are all within the mean standard deviation of the clinical observations. The values of plasma protein unbound fraction, renal clearance, and gastric juice pH between adults and pediatrics were changed by using the age-dependent pediatric organ maturity formula, and the adult model was extrapolated to the pediatric model. The final developed pediatric PBPK model was used to evaluate optimal dosing for children of different developmental ages. The relationship between the frist dose and age was as follows: 8.8 mg/kg/day from 0.5 to 2 years old, 9.2 mg/kg/day from 3 to 6 years old, 9.4 mg/kg/day from 7 to 12 years old, and 8.2 mg/kg/day from 13 to 18 years old, taken in half for 2-5 days. Simultaneously, the simulated exposures achieved with the dosing regimen proposed were comparable to adult plasma exposures for treatment of community-acquired pneumonia. A reasonable azithromycin pharmacokinetic-pharmacodynamic model for adults and pediatrics has been established, which can be demonstrated by the use of literature pediatric data to develop pediatric PBPK models, expanding the scope of this powerful modeling tool.

Assessment of Aging-Related Function Variations of P-gp Transporter in Old-Elderly Chinese CHF Patients Based on Modeling and Simulation

BACKGROUND AND OBJECTIVES

P-glycoprotein (P-gp) is one of the most intensely studied transporters owing to its broad tissue distribution and substrate specificity. Existing research suggests that the risk of systemic exposure to dabigatran etexilate (DABE) and digoxin, two P-gp probe substrates in vivo, has significantly increased in elderly patients. We applied a model-based quantitative pharmacological approach to assess aging-related P-gp changes in the Chinese old-elderly population.

METHODS

Population pharmacokinetic (PopPK) modeling was first performed using clinical pharmacokinetic data to explore the effect of age on the pharmacokinetic characteristics of dabigatran (DAB, the active principle of DABE) and digoxin in elderly Chinese patients. Corresponding physiologically based pharmacokinetic (PBPK) models were established to further explain the elevated systemic exposure to these two drugs. Eventually, standard dosing regimens of DABE and digoxin were assessed in Chinese old-elderly patients with chronic heart failure (CHF) with different stages of renal impairment.

RESULTS

PopPK analysis suggested that age as a covariate had an additional effect on the apparent clearance of these two drugs after correcting for creatinine clearance. PBPK simulation results suggested that disease-specific pathophysiological changes could explain DAB exposure in the young elderly. In the elderly population, 17.1% of elevated DAB exposure remained unexplained, and 25.5% of the reduced P-gp function associated with aging was ultimately obtained using sensitivity analysis. This value was further validated using digoxin data obtained by PBPK modeling. The simulation results suggest that CHF patients with advanced age and moderate-to-severe renal impairment require heightened vigilance for elevated exposure risk during the use of DABE and digoxin.

CONCLUSIONS

Aging might be a significant risk factor for elevated systemic exposure to DAB and digoxin by reducing P-gp-mediated efflux in the Chinese old elderly population.

Predicting the correct dose in children: Role of computational Pediatric Physiological-based pharmacokinetics modeling tools

The pharmacokinetics (PKs) and safety of medications in particular groups can be predicted using the physiologically-based pharmacokinetic (PBPK) model. Using the PBPK model may enable safe pediatric clinical trials and speed up the process of new drug research and development, especially for children, a population in which it is relatively difficult to conduct clinical trials. This review summarizes the role of pediatric PBPK (P-PBPK) modeling software in dose prediction over the past 6 years and briefly introduces the process of general P-PBPK modeling. We summarized the theories and applications of this software and discussed the application trends and future perspectives in the area. The modeling software's extensive use will undoubtedly make it easier to predict dose prediction for young patients.

A comparison of different methods for the first-in-pediatric dose selection

BACKGROUND AND AIM

To conduct a pediatric clinical trial, it is important to optimize pediatric dose as accurately as possible. This is mainly because due to ethical reasons, children cannot be given several doses to evaluate pharmacokinetics, safety, and efficacy of a drug.

METHODS

In this study, several simple methods to project a first-in-pediatric dose to initiate a clinical trial were evaluated. These methods were as follows:(1) Weight-based pediatric dose prediction (allometric scaling), (2) Salisbury rule (weight-based method), and (3) pediatric dose prediction based on predicted clearance. These methods were compared with the dose given to children in clinical practice. The methods were also compared with whole-body physiologically based pharmacokinetic (PBPK) model (n = 11). A ±30% prediction error (predicted vs. observed) was considered acceptable.

RESULTS

There were 27 drugs with 113 observations (different age groups from preterm neonates to adolescents). At least, ≤30% prediction error in pediatric dose projection was noted for more than 70% observations. The predictive performance of all the proposed methods was comparable with the whole-body PBPK.

CONCLUSIONS

The proposed methods are simple and accurate and can be developed on a spreadsheet in a very short period of time.

RELEVANCE FOR PATIENTS

The study provides an estimate of first-in-pediatric dose by simple methods to initiate pediatric clinical trials. Especially, Salisbury rule is based on body weight and is very simple and works fairly well in children >30 kg body weight and can be even used in clinical settings.

Moxifloxacin Pharmacokinetics, Cardiac Safety, and Dosing for the Treatment of Rifampicin-Resistant Tuberculosis in Children

BACKGROUND

Moxifloxacin is a recommended drug for rifampin-resistant tuberculosis (RR-TB) treatment, but there is limited pediatric pharmacokinetic and safety data, especially in young children. We characterize moxifloxacin population pharmacokinetics and QT interval prolongation and evaluate optimal dosing in children with RR-TB.

METHODS

Pharmacokinetic data were pooled from 2 observational studies in South African children with RR-TB routinely treated with oral moxifloxacin once daily. The population pharmacokinetics and Fridericia-corrected QT (QTcF)-interval prolongation were characterized in NONMEM. Pharmacokinetic simulations were performed to predict expected exposure and optimal weight-banded dosing.

RESULTS

Eighty-five children contributed pharmacokinetic data (median [range] age of 4.6 [0.8-15] years); 16 (19%) were aged <2 years, and 8 (9%) were living with human immunodeficiency virus (HIV). The median (range) moxifloxacin dose on pharmacokinetic sampling days was 11 mg/kg (6.1 to 17). Apparent clearance was 6.95 L/h for a typical 16-kg child. Stunting and HIV increased apparent clearance. Crushed or suspended tablets had faster absorption. The median (range) maximum change in QTcF after moxifloxacin administration was 16.3 (-27.7 to 61.3) ms. No child had QTcF ≥500 ms. The concentration-QTcF relationship was nonlinear, with a maximum drug effect (Emax) of 8.80 ms (interindividual variability = 9.75 ms). Clofazimine use increased Emax by 3.3-fold. Model-based simulations of moxifloxacin pharmacokinetics predicted that current dosing recommendations are too low in children.

CONCLUSIONS

Moxifloxacin doses above 10-15 mg/kg are likely required in young children to match adult exposures but require further safety assessment, especially when coadministered with other QT-prolonging agents.

Population Pharmacokinetics of Moxifloxacin in Children

BACKGROUND/OBJECTIVE

Moxifloxacin is a fluoroquinolone that is commonly used in adults, but not children. Certain clinical situations compel pediatric clinicians to use moxifloxacin, despite its potential for toxicity and limited pharmacokinetics (PK) data. Our objective was to further characterize the pharmacokinetics of moxifloxacin in children.

METHODS

We performed an opportunistic, open-label population PK study of moxifloxacin in children < 18 years of age who received moxifloxacin as part of standard care. A set of structural PK models and residual error models were explored using nonlinear mixed-effects modeling. Covariates with known biological relationships were investigated for their influence on PK parameters.

RESULTS

We obtained 43 moxifloxacin concentrations from 14 participants who received moxifloxacin intravenously (n = 8) or orally (n = 6). The dose of moxifloxacin was 10 mg/kg daily in participants ≤ 40 kg and 400 mg daily in participants > 40 kg. The population mean clearance and mean volume of distribution were 18.2 L/h and 167 L, respectively. The oral absorption was described by a first-order process. The estimated extent of oral bioavailability was highly variable (range 20-91%). Total body weight was identified as a covariate on clearance and volume of distribution, and substantially reduced the random unexplained inter-individual variability for both parameters. No participants experienced suspected serious adverse reactions related to moxifloxacin.

CONCLUSION

These data add to the existing literature to support use of moxifloxacin in children in certain situations; however, further prospective studies on the safety and efficacy of moxifloxacin are needed.

Model-based efficacy and toxicity comparisons of moxifloxacin for multi-drug-resistant tuberculosis

Background

Moxifloxacin (MOX) is used as a first-choice drug to treat multi-drug-resistant tuberculosis (MDR-TB), however, evidence-based dosing optimization should be strengthened by integrative analysis. The primary goal of this study was to evaluate MOX efficacy and toxicity using integratvie model-based approaches in MDR-TB patients.

Methods

In total, 113 MDR-TB patients from five different clinical trials were analyzed for the development of a population pharmacokinetics (PK) model. A final population PK model was merged with a previously developed lung-lesion distribution and QT prolongation model. Monte Carlo simulation was used to calculate the probability target attainment (PTA) value based on concentration. An area under the concentration-time curve (AUC)-based target was identified as the minimum inhibitory concentration (MIC) of MOX isolated from MDR-TB patients.

Results

The presence of human immunodeficiency virus (HIV) increased clearance by 32.7% and decreased the AUC by 27.4%, compared with HIV-negative MDR-TB patients. A daily dose of 800 mg or a 400 mg twice daily dose of MOX is expected to be effective in MDR-TB patients with an MIC of ≤ 0.25 µg/mL, regardless of PK differences resulting from the presence of HIV. The effect of MOX in HIV-positive MDR-TB patients tended to be decreased dramatically from 0.5 µg/mL, in contrast to the findings in HIV-negative patients. A regimen of twice-daily doses of 400 mg should be considered safer than an 800 mg once-daily dosing regimen, because of the narrow fluctuation of concentrations.

Conclusions

Our results suggest that a 400 mg twice-daily dose of MOX is an optimal dosing regimen for MDR-TB patients because it provides superior efficacy and safety.

Comparison between physiologically based pharmacokinetic and population pharmacokinetic modelling to select paediatric doses of gepotidacin in plague

Aims

To develop physiologically based pharmacokinetic (PBPK) and population pharmacokinetic (PopPK) models to predict effective doses of gepotidacin in paediatrics for the treatment of pneumonic plague (Yersinia pestis).

Methods

A gepotidacin PBPK model was constructed using a population‐based absorption, distribution, metabolism and excretion simulator, Simcyp®, with physicochemical and in vitro data, optimized with clinical data from a dose‐escalation intravenous (IV) study and a human mass balance study. A PopPK model was developed with pooled PK data from phase 1 studies with IV gepotidacin in healthy adults.

Results

For both the PopPK and PBPK models, body weight was found to be a key covariate affecting gepotidacin clearance. With PBPK, ~90% of the predicted PK for paediatrics fell between the 5th and 95th percentiles of adult values except for subjects weighing ≤5 kg. PopPK‐simulated paediatric means for C_max and AUC_(0‐τ) were similar to adult exposures across various weight brackets. The proposed dosing regimens were weight‐based for subjects ≤40 kg and fixed‐dose for subjects >40 kg. Comparison of observed and predicted exposures in adults indicated that both PBPK and PopPK models achieved similar AUC and C_max for a given dose, but the C_max predictions with PopPK were slightly higher than with PBPK. The two models differed on dose predictions in children <3 months old. The PopPK model may be suboptimal for low age groups due to the absence of maturation characterization of drug‐metabolizing enzymes involved with clearance in adults.

Conclusions

Both PBPK and PopPK approaches can reasonably predict gepotidacin exposures in children.

Predictive Performance of Physiology-Based Pharmacokinetic Dose Estimates for Pediatric Trials: Evaluation With 10 Bayer Small-Molecule Compounds in Children

Development and guidance of dosing schemes in children have been supported by physiology-based pharmacokinetic (PBPK) modeling for many years. PBPK models are built on a generic basis, where compound- and system-specific parameters are separated and can be exchanged, allowing the translation of these models from adults to children by accounting for physiological differences. Owing to these features, PBPK modeling is a valuable approach to support clinical decision making for dosing in children. In this analysis, we evaluate pediatric PBPK models for 10 small-molecule compounds that were applied to support clinical decision processes at Bayer for their predictive power in different age groups. Ratios of PBPK-predicted to observed PK parameters for the evaluated drugs in different pediatric age groups were estimated. Predictive performance was analyzed on the basis of a 2-fold error range and the bioequivalence range (ie, 0.8 ≤ predicted/observed ≤ 1.25). For all 10 compounds, all predicted-to-observed PK ratios were within a 2-fold error range (n = 27), with two-thirds of the ratios within the bioequivalence range (n = 18). The findings demonstrate that the pharmacokinetics of these compounds was successfully and adequately predicted in different pediatric age groups. This illustrates the applicability of PBPK for guiding dosing schemes in the pediatric population.

Physiologically Based Pharmacokinetic Modeling of Monoclonal Antibodies in Pediatric Populations Using PK-Sim

Physiologically based pharmacokinetic (PBPK) models are increasingly used to support pediatric dose selection for small molecule drugs. In contrast, only a few pediatric PBPK models for therapeutic antibodies have been published recently, and the knowledge on the maturation of the processes relevant for antibody pharmacokinetics (PK) is limited compared to small molecules. The aim of this study was, thus, to evaluate predictions from antibody PBPK models for children which were scaled from PBPK models for adults in order to identify respective knowledge gaps. For this, we used the generic PBPK model implemented in PK-Sim without further modifications. Focusing on general clearance and distribution mechanisms, we selected palivizumab and bevacizumab as examples for this evaluation since they show simple, linear PK which is not governed by drug-specific target mediated disposition at usual therapeutic dosages, and their PK has been studied in pediatric populations after intravenous application. The evaluation showed that the PK of palivizumab was overall reasonably well predicted, while the clearance for bevacizumab seems to be underestimated. Without implementing additional ontogeny for antibody PK-specific processes into the PBPK model, bodyweight normalized clearance increases only moderately in young children compared to adults. If growth during aging at the time of the simulation was considered, the apparent clearance is approximately 20% higher compared to simulations for which growth was not considered for newborns due to the long half-life of antibodies. To fully understand the differences and similarities in the PK of antibodies between adults and children, further research is needed. By integrating available information and data, PBPK modeling can contribute to reveal the relevance of involved processes as well as to generate and test hypothesis.