Development and verification of a full physiologically-based pharmacokinetic model for sublingual buprenorphine in healthy adult volunteers that accounts for nonlinear bioavailability.

Sublingual buprenorphine is used for opioid use disorder and neonatal opioid withdrawal syndrome (NOWS). The study aimed to develop a full physiologically-based pharmacokinetic (PBPK) model that can adequately describe dose- and formulation-dependent bioavailability of buprenorphine. Simcyp (v21.0) was used for model construction. Four linear regression models (i.e. untransformed or log-transformed for dose or proportion sublingually absorbed) were explored to describe sublingual absorption of buprenorphine across dose. Published clinical trial data not used in model development were used for verification. The PBPK model's predictive performance was deemed adequate if the geometric means of ratios between predicted and observed (P/O ratios) area under the curve (AUC), peak concentration (Cmax), and time to reach Cmax (Tmax) fell within the 1.25-fold prediction error range. Sublingual buprenorphine absorption was best described by a regression model with logarithmically transformed dose. By integrating this nonlinear absorption profile, the PBPK model adequately predicted buprenorphine pharmacokinetics (PK) following administration of sublingual tablets and solution across a dose range of 2-32 mg, with geometric mean (95% confidence interval) P/O ratios for AUC and Cmax equaling 0.99 (0.86-1.12) and 1.24 (1.09-1.40), respectively, and median (5th to 95th percentile) for Tmax equaling 1.11 (0.69-1.57). A verified PBPK model was developed that adequately predicts dose- and formulation-dependent buprenorphine PK following sublingual administration. Significance Statement The PBPK model developed in this study is the first to adequately predict dose- and formulation-dependent sublingual buprenorphine pharmacokinetics. Accurate prediction was facilitated by the incorporation of a novel nonlinear absorption model. The developed model will serve as the foundation for fetomaternal PBPK modeling to predict maternal and fetal buprenorphine exposures to optimize buprenorphine treatment for neonatal opioid withdrawal syndrome (NOWS).

Predictive Performance of Physiologically Based Pharmacokinetic Modelling of Beta-Lactam Antibiotic Concentrations in Adipose, Bone, and Muscle Tissues.

Physiologically based pharmacokinetic (PBPK) models consist of compartments representing different tissues. As most models are only verified based on plasma concentrations, it is unclear how reliable associated tissue profiles are. This study aimed to assess the accuracy of PBPK-predicted beta-lactam antibiotic concentrations in different tissues and assess the impact of using effect site concentrations for evaluation of target attainment. Adipose, bone, and muscle concentrations of five beta-lactams (piperacillin, cefazolin, cefuroxime, ceftazidime, and meropenem) in healthy adults were collected from literature and compared with PBPK predictions. Model performance was evaluated with average fold errors (AFEs) and absolute AFEs (AAFEs) between predicted and observed concentrations. In total, 26 studies were included, 14 of which reported total tissue concentrations and 12 unbound interstitial fluid (uISF) concentrations. Concurrent plasma concentrations, used as baseline verification of the models, were fairly accurate (AFE: 1.14, AAFE: 1.50). Predicted total tissue concentrations were less accurate (AFE: 0.68, AAFE: 1.89). A slight trend for underprediction was observed but none of the studies had AFE or AAFE values outside threefold. Similarly, predictions of microdialysis-derived uISF concentrations were less accurate than plasma concentration predictions (AFE: 1.52, AAFE: 2.32). uISF concentrations tended to be overpredicted and two studies had AFEs and AAFEs outside threefold. Pharmacodynamic simulations in our case showed only a limited impact of using uISF concentrations instead of unbound plasma concentrations on target attainment rates. The results of this study illustrate the limitations of current PBPK models to predict tissue concentrations and the associated need for more accurate models. SIGNIFICANCE STATEMENT: Clinical inaccessibility of local effect site concentrations precipitates a need for predictive methods for the estimation of tissue concentrations. This is the first study in which the accuracy of PBPK-predicted tissue concentrations of beta-lactam antibiotics in humans were assessed. Predicted tissue concentrations were found to be less accurate than concurrent predicted plasma concentrations. When using PBPK models to predict tissue concentrations, this potential relative loss of accuracy should be acknowledged when clinical tissue concentrations are unavailable to verify predictions.

Use of Developmental Midazolam and 1-Hydroxymidazolam Data with Pediatric Physiologically Based Modeling to Assess Cytochrome P450 3A4 and Uridine Diphosphate Glucuronosyl Transferase 2B4 Ontogeny In Vivo.

Pediatric physiologically based pharmacokinetics modeling in drug development has grown in the past decade but uncertainty remains regarding ontogeny of some drug metabolizing enzymes. In this study, a midazolam and 1-hydroxymidazolam physiologically based pharmacokinetic model (PBPK) model was developed and used to define the ontogeny for hepatic cytochrome P450 (CYP) 3A4 and uridine diphosphate glucuronosyl transferase (UGT) 2B4. Data for model development and pharmacokinetic studies on intravenous midazolam in adults and pediatrics were collated from the literature. The PBPK model was verified in the adult population and then used to compare the performance of two ontogeny profiles for CYP3A4 in terms of parent drug elimination in pediatrics. Four studies also published data on the 1-hydroxymidazolam, and this was used to evaluate the known ontogeny for UGT2B4.For midazolam elimination, the Upreti CYP3A4 ontogeny performed better than Salem; mean error (bias) and mean squared error (precision) were 0.14 and 0.064 compared with 0.69 and 1.21, respectively. For 1-hydroxymidazolam elimination, the Simcyp default ontogeny of UGT2B4 appeared to perform best for studies covering the age range 0.5 to 15.7 years, while for a study in younger ages 0 to 1 years it was the Badee UGT2B4 ontogeny. In preterm neonates, overall expression of UGT appeared to be around 10% of that in adults.Identifying the optimal model of CYP3A4 ontogeny is important for the regulatory use of PBPK. The results for midazolam are conclusive but research about other CYP3A4 metabolized compounds will underpin generalizability of the CYP3A4 ontogeny. UGT2B4 ontogeny is less certain, but this study indicates the most likely scenarios. SIGNIFICANCE STATEMENT: A PBPK model for midazolam and 1-hydroxymidazolam was developed to test various ontogeny scenarios for CYP3A4 and UGT2B4. The CYP3A4 ontogeny of Upreti resulted in more accurate prediction of midazolam CL across nine clinical studies, age range birth to 18 years. 1-Hydroxy midazolam was used as a marker of UGT. The Simcyp default 'no ontogeny' profiles for UGT2B4 performed the best; however, for <1 year of age, there was some evidence of overactivity of this enzyme compared to adults.

Use of a physiologically based pharmacokinetic-pharmacodynamic model for initial dose prediction and escalation during a paediatric clinical trial.

AIMS: To build and verify a physiologically based pharmacokinetic (PBPK) model for radiprodil in adults and link this to a pharmacodynamic (PD) receptor occupancy (RO) model derived from in vitro data. Adapt this model to the paediatric population and predict starting and escalating doses in infants based on RO. Use the model to guide individualized dosing in a clinical trial in 2- to 14-month-old children with infantile spasms. METHODS: A PBPK model for radiprodil was developed to investigate the systemic exposure of the drug after oral administration in fasted and fed adults; this was then linked to RO via a PD model. The model was then expanded to include developmental physiology and ontogeny to predict escalating doses in infants that would result in a specific RO of 20, 40 and 60% based on average unbound concentration following a twice daily (b.i.d.) dosing regimen. Dose progression in the clinical trial was based on observed concentration-time data against PBPK predictions. RESULTS: For paediatric predictions, the elimination of radiprodil, based on experimental evidence, had no ontogeny. Predicted b.i.d. doses ranged from 0.04 mg/kg for 20% RO, 0.1 mg/kg for 40% RO to 0.21 mg/kg for 60% RO. For all infants recruited in the study, observed concentration-time data following the 0.04 mg/kg and subsequent doses were within the PBPK model predicted 5th and 95th percentiles. CONCLUSION: To our knowledge, this is the first time a PBPK model linked to RO has been used to guide dose selection and escalation in the live phase of a paediatric clinical trial.

Teicoplanin physiologically based pharmacokinetic modeling offers a quantitative assessment of a theoretical influence of serum albumin and renal function on its disposition.

PURPOSE: Variability in teicoplanin pharmacokinetics has been explained by multiple factors such as body weight, renal function, and serum albumin level. To improve mechanistic understanding of the causes of variability, a physiologically based pharmacokinetic (PBPK) model can be used as a systematic platform. In this study, a PBPK model of teicoplanin was developed to quantitatively assess the effects of physiological changes due to disease status using virtual populations. METHODS: Predictive performance of the models was evaluated by comparing simulated and observed concentration-time profiles of teicoplanin. Subsequently, sensitivity analyses were conducted to identify potential factors contributing to individual differences in teicoplanin PK. RESULTS: The developed PBPK model generated concentration-time profiles that were comparable to clinical observations in healthy adults, including Caucasians and Japanese, and after single-dose and multiple-dose administration. The predicted PK parameters (i.e., Cmax, AUC, clearance) were within a two-fold range of the observed data in patients with renal impairments as well as healthy adults. Changes in total and unbound teicoplanin concentrations at 72 h, after various dosing regimens (tested 4-14 mg/kg q12h for three doses as a loading dose and then 4-14 mg/kg daily as a maintenance dose), were sensitive to renal function and serum albumin concentrations. CONCLUSION: The PBPK model of teicoplanin provides mechanistic insight into the factors altering its disposition and allows assessments of the theoretical and quantitative impact of individual changes in physiological parameters on its PK even when an actual assessment with adequate sample sizes of patients is challenging.

Development of a physiologically based pharmacokinetic model for mefloquine and its application alongside a clinical effectiveness model to select an optimal dose for prevention of malaria in young Caucasian children.

AIMS: To predict the optimal chemoprophylactic dose of mefloquine in infants of 5-10 kg using physiologically based pharmacokinetic (PBPK) and clinical effectiveness models. METHODS: The PBPK model was developed in Simcyp version 14.1 and verified against clinical pharmacokinetic data in adults; the final model, accounting for developmental physiology and enzyme ontogeny was then applied in the paediatric population. The clinical effectiveness model utilized real-world chemoprophylaxis data with stratification of output by age and including infant data from the UK population. RESULTS: PBPK simulations in infant populations depend on the assumed fraction of mefloquine metabolized by CYP3A4 (0.47, 0.95) and on the associated CYP3A4 ontogeny (Salem, Upreti). However, all scenarios suggest that a dose of 62.5 mg weekly achieves or exceeds the exposure in adults following a 250 mg weekly dose and results in a minimum plasma concentration of 620 ng ml-1 , which is considered necessary to achieve 95% prophylactic efficacy. The clinical effectiveness model predicts a 96% protective efficacy from mefloquine chemoprophylaxis at 62.5 mg weekly. CONCLUSIONS: The PBPK and clinical effectiveness models are mutually supportive and suggest a prophylactic dose of 62.5 mg weekly in the Caucasian 5-10 kg infant population travelling to endemic countries. This dual approach offers a novel route to dose selection in a vulnerable population, where clinical trials would be difficult to conduct.

Can Population Modelling Principles be Used to Identify Key PBPK Parameters for Paediatric Clearance Predictions? An Innovative Application of Optimal Design Theory.

PURPOSE: Physiologically-based pharmacokinetic (PBPK) models are essential in drug development, but require parameters that are not always obtainable. We developed a methodology to investigate the feasibility and requirements for precise and accurate estimation of PBPK parameters using population modelling of clinical data and illustrate this for two key PBPK parameters for hepatic metabolic clearance, namely whole liver unbound intrinsic clearance (CLint,u,WL) and hepatic blood flow (Qh) in children. METHODS: First, structural identifiability was enabled through re-parametrization and the definition of essential trial design components. Subsequently, requirements for the trial components to yield precise estimation of the PBPK parameters and their inter-individual variability were established using a novel application of population optimal design theory. Finally, the performance of the proposed trial design was assessed using stochastic simulation and estimation. RESULTS: Precise estimation of CLint,u,WL and Qh and their inter-individual variability was found to require a trial with two drugs, of which one has an extraction ratio (ER) ≤ 0.27 and the other has an ER ≥ 0.93. The proposed clinical trial design was found to lead to precise and accurate parameter estimates and was robust to parameter uncertainty. CONCLUSION: The proposed framework can be applied to other PBPK parameters and facilitate the development of PBPK models.

Using pharmacokinetic modelling to improve prescribing practices of intravenous aminophylline in childhood asthma exacerbations.

OBJECTIVE: To evaluate physiologically based pharmacokinetic modelling (PBPK) software in paediatric asthma patients using intravenous aminophylline. METHODS: Prospective clinical audit of children receiving iv aminophylline (July 2014 to June 2016), and in-silico modelling using Simcyp software. RESULTS: Thirty-eight admissions (25 children) were included. Children with aminophylline levels ≥10 mg/l had equivalent clinical outcomes compared to those <10 mg/L, and adverse effects occurred in 57%. Therapeutic drug monitoring (TDM) data correlated well with PBPK model. PBPK modelling of a 5 mg/kg iv loading dose (≤18yr) shows a mean Cmax of 8.99 mg/L (5th-95th centiles 5.5-13.7 mg/L), with 70.3% of subjects <10 mg/L, 29.4% achieving 10-20 mg/L, and 0.1% > 20 mg/L. For an aminophylline infusion (0-12 y) of 1.0  mg/kg/h, the mean steady state infusion concentration was 16.4 mg/L, (5th-95th centiles 5.3-32 mg/L), with 26.8% having a serum concentration >20 mg/L. For 12-18yr receiving 0.5  mg/kg/h infusion, the mean steady state infusion concentration was 9.37 mg/L (5th-95th centiles 3.4-18 mg/L), with 59.8% having a serum concentration <10 mg/L. CONCLUSION: PBPK software modelling correlates well with clinical data. Current aminophylline iv loading dosage recommendations achieve levels <10 mg/l in 70% of children. Routine TDM may need altering as low risk of toxicity (>20 mg/l).

Prediction of liver volume - a population-based approach to meta-analysis of paediatric, adult and geriatric populations - an update.

Liver volume is a critical scaling factor for predicting drug clearance in physiologically based pharmacokinetic modelling and for both donor/recipient graft size estimation in liver transplantation. The accurate and precise estimation of liver volume is therefore essential. The objective here was to extend an existing meta-analysis using a non-linear mixed effects modelling approach for the estimation of liver volume to other race groups and paediatric and geriatric populations. Interrogation of the PubMed® database was undertaken using a text string query to ensure as objective a retrieval of liver volume data for the modelling exercise as possible. Missing body size parameters were estimated using simulations from the Simcyp Simulator V13R1 for an age and ethnically appropriate population. Non-linear mixed effect modelling was undertaken in Phoenix 1.3 (Certara) utilizing backward deletion and forward inclusion of covariates from fully parameterized models. Existing liver volume models based on body surface area (BSA) and body weight and height were implemented for comparison. The extension of a structural model using a BSA equation and incorporating the Japanese race and age as covariates and exponents on LV0 (θBaseline ) and body surface area (θBSA ), respectively, delivered a comparatively low objective function value. Bootstrapping of the original dataset revealed that the confidence intervals (2.5-97.5%) for the fitted (theta) parameter estimates were bounded by the bootstrapped estimates of the same. In conclusion, extension and re-parameterization of the existing Johnson model adequately describes changes in liver volume using the body surface area in all investigated populations. Copyright © 2017 John Wiley & Sons, Ltd.

How Does In Vivo Biliary Elimination of Drugs Change with Age? Evidence from In Vitro and Clinical Data Using a Systems Pharmacology Approach.

Information on the developmental changes in biliary excretion (BE) of drugs is sparse. The aims of this study were to collate literature data on the pharmacokinetics of biliary excretion of drugs used in pediatrics and to apply a physiologically based pharmacokinetic (PBPK) model to predict their systemic clearance (CL) with a view to elucidating age-related changes in biliary excretion. Drug parameters for azithromycin, ceftriaxone, and digoxin administered intravenously and buprenorphine (intravenous and sublingual) were collated from the literature and used in the Simcyp Simulator to predict adult CL values, which were then validated against observed data. The change in CL with age was simulated in the pediatric model and compared with observed data; where necessary, the ontogeny function associated with BE was applied to recover the age-related CL. For azithromycin a fraction of adult BE activity of 15% was necessary to predict the CL in neonates (26 weeks gestational age) and 100% activity was apparent by 7 months. For ceftriaxone and digoxin full BE activity appeared to be present at term birth; for digoxin, an adult BE activity of 10% was needed to predict the CL in premature neonates (30 weeks gestational age). The CL of buprenorphine with age was described by the ontogeny of the major elimination pathways (CYP3A4 and UGT1A1) with no ontogeny assumed for the biliary component. Thus, the ontogeny of BE for all four drugs appears to be rapid and they attain adult levels at birth or within the first few months of postnatal age.

Development of a physiologically based pharmacokinetic model of actinomycin D in children with cancer.

AIMS: Use of the anti-tumour antibiotic actinomycin D is associated with development of hepatotoxicity, particularly in young children. A paucity of actinomycin D pharmacokinetic data make it challenging to develop a sound rationale for defining dosing regimens in younger patients. The study aim was to develop a physiologically based pharmacokinetic (PBPK) model using a combination of data from the literature and generated from experimental analyses. METHODS: Assays to determine actinomycin D Log P, blood:plasma partition ratio and ABCB1 kinetics were conducted. These data were combined with physiochemical properties sourced from the literature to generate a compound file for use within the modelling-simulation software Simcyp (version 14 release 1). For simulation, information was taken from two datasets, one from 117 patients under the age of 21 and one from 20 patients aged 16-48. RESULTS: The final model incorporated clinical renal and biliary clearance data and an additional systemic clearance value. The mean AUC0-26h of simulated subjects was within 1.25-fold of the observed AUC0-26h (84 ng h ml(-1) simulated vs. 93 ng h ml(-1) observed). For the younger age ranges, AUC predictions were within two-fold of observed values, with simulated data from six of the eight age/dose ranges falling within 15% of observed data. Simulated values for actinomycin D AUC0-26h and clearance in infants aged 0-12 months ranged from 104 to 115 ng h ml(-1) and 3.5-3.8 l h(-1) , respectively. CONCLUSIONS: The model has potential utility for prediction of actinomycin D exposure in younger patients and may help guide future dosing. However, additional independent data from neonates and infants is needed for further validation. Physiological differences between paediatric cancer patients and healthy children also need to be further characterized and incorporated into PBPK models.

Does age affect gastric emptying time? A model-based meta-analysis of data from premature neonates through to adults.

PURPOSE: Gastric emptying (GE) is often reported to be slower and more irregular in premature neonates than in older children and adults. The aim of this study was to investigate the impact of age and other covariates on the rate of GE. METHODS: The effect of age on the mean gastric residence times (MGRT) of liquid and solid food was assessed by analysing 49 published studies of 1457 individuals, aged from 28 weeks gestation to adults. The data were modelled using the nonlinear mixed-effects approach within NONMEM version 7.2 (ICON, Dublin, Ireland), with evaluation of postnatal age, gestational age and meal type as covariates. A double Weibull function was selected as a suitable model since it could account for the typical biphasic nature of GE. RESULTS: Age was not a significant covariate for GE but meal type was. Aqueous solutions were associated with the fastest emptying time (mean simulated gastric residence time of 45 min) and solid food was associated with the slowest (98 min). CONCLUSIONS: These findings challenge the assertion that GE is different in neonates, as compared with older children and adults due to age, and they reinforce the significance of food type in modulating GE.

Development of physiologically based pharmacokinetic model to evaluate the relative systemic exposure to quetiapine after administration of IR and XR formulations to adults, children and adolescents.

Quetiapine is an atypical antipsychotic drug with a high permeability, moderate solubility and defined as a Biopharmaceutics Classification System class ll compound. The pharmacokinetics (PK) of the quetiapine immediate-release (IR) formulation has been studied in both adults and children, but the quetiapine extended-release (XR) formulation has only been conducted in adults. The purpose of the current study was to use physiologically based pharmacokinetic modeling (PBPK) quantitatively to predict the PK of the XR formulation in children and adolescents. Using a 'learn and confirm' approach, PBPK models were developed employing in vitro ADME and physicochemical data, clinical PK data of quetiapine IR/XR in adults and clinical PK data of quetiapine IR in children. These models can predict well the effects of CYP3A4 inhibition and induction on the PK of quetiapine, the PK profile of quetiapine IR in children and adults, and the PK profile of quetiapine XR in adults. The AUC and Cmax ratios (children vs adults) for the different age groups were in reasonable agreement with the observed ratios. In addition, the PBPK model predicted that children and adolescents are likely to achieve a similar exposure following administration of either the XR formulation once daily or the IR formulation twice daily at similar total daily doses. The results from the study can help inform dosing regimens in pediatrics using the quetiapine XR formulation.

Prediction of Pediatric Pharmacokinetics for CYP3A4 Metabolized Drugs: Comparison of the Performance of Two Hepatic Ontogeny Within a Physiologically Based Pharmacokinetic Model.

The rapid growth in the use of pediatric physiologically based pharmacokinetic (PBPK) models, particularly for regulatory applications, has focused emphasis on model verification and ensuring system parameters are robust, including how these change with age. Uncertainty remains regarding the ontogeny of some enzymes and transporters, in this study 2 published ontogeny profiles for hepatic CYP3A4 were compared. Clinical pharmacokinetic data on 4 intravenously administered CYP3A4 substrates (alfentanil, fentanyl, midazolam, and sildenafil) used across the pediatric age range was collected from the literature. The PBPK models were verified in the adult population and then used to compare the Salem and a modified Upreti ontogeny profiles for CYP3A4 in terms of parent drug clearance and area under the curve from birth onward. Overall, the modified Upreti ontogeny profile resulted in 15 out of 17 age-related predictions within 2-fold and 12 out of 17 predictions within 1.5-fold ranges of observed values, for the Salem ontogeny these values were 12 out of 17 and 8 out of 17, respectively. The Upreti ontogeny profile performed better than Salem, average fold error and absolute average fold error were 1.14 and 1.35 compared to 1.56 and 1.90, respectively. Identifying the optimal CYP3A4 ontogeny is important for regulatory use of PBPK especially given the number of drugs cleared by this enzyme. This study broadens the evidence from previous studies that Upreti is more favorable than Salem, but further work is needed especially in the neonatal and early infant age range.

Combining data on the bioavailability of midazolam and physiologically-based pharmacokinetic modeling to investigate intestinal CYP3A4 ontogeny.

Pediatric physiologically-based modeling in drug development has grown in the past decade and optimizing the underlying systems parameters is important in relation to overall performance. In this study, variation of clinical oral bioavailability of midazolam as a function of age is used to assess the underlying ontogeny models for intestinal CYP3A4. Data on midazolam bioavailability in adults and children and different ontogeny patterns for intestinal CYP3A4 were first collected from the literature. A pediatric PBPK model was then used to assess six different ontogeny models in predicting bioavailability from preterm neonates to adults. The average fold error ranged from 0.7 to 1.38, with the rank order of least to most biased model being No Ontogeny < Upreti = Johnson < Goelen < Chen < Kiss. The absolute average fold error ranged from 1.17 to 1.64 with the rank order of most to least precise being Johnson > Upreti > No Ontogeny > Goelen > Kiss > Chen. The optimal ontogeny model is difficult to discern when considering the possible influence of CYP3A5 and other population variability; however, this study suggests that from term neonates and older a faster onset Johnson model with a lower fraction at birth may be close to this. For inclusion in other PBPK models, independent verification will be needed to confirm these results. Further research is needed in this area both in terms of age-related changes in midazolam and similar drug bioavailability and intestinal CYP3A4 ontogeny.

Forecasting Fetal Buprenorphine Exposure through Maternal-Fetal Physiologically Based Pharmacokinetic Modeling.

Buprenorphine readily crosses the placenta, and with greater prenatal exposure, neonatal opioid withdrawal syndrome (NOWS) likely grows more severe. Current dosing strategies can be further improved by tailoring doses to expected NOWS severity. To allow the conceptualization of fetal buprenorphine exposure, a maternal-fetal physiologically based pharmacokinetic (PBPK) model for sublingual buprenorphine was developed using Simcyp (v21.0). Buprenorphine transplacental passage was predicted from its physicochemical properties. The maternal-fetal PBPK model integrated reduced transmucosal absorption driven by lower salivary pH and induced metabolism observed during pregnancy. Maternal pharmacokinetics was adequately predicted in the second trimester, third trimester, and postpartum period, with the simulated area under the curve from 0 to 12 h, apparent clearance, and peak concentration falling within the 1.25-fold prediction error range. Following post hoc adjustment of the likely degree of individual maternal sublingual absorption, umbilical cord blood concentrations at delivery (n = 21) were adequately predicted, with a geometric mean ratio between predicted and observed fetal concentrations of 1.15 and with 95.2% falling within the 2-fold prediction error range. The maternal-fetal PBPK model developed in this study can be used to forecast fetal buprenorphine exposure and would be valuable to investigate its correlation to NOWS severity.

Development and Verification of a Japanese Pediatric Physiologically Based Pharmacokinetic Model with Emphasis on Drugs Eliminated by Cytochrome P450 or Renal Excretion.

Physiologically based pharmacokinetic (PBPK) models are useful in bridging drug exposure in different ethnic groups, and there is increasing regulatory application of this approach in adults. Reported pediatric PBPK models tend to focus on the North European population, with few examples in other ethnic groups. This study describes the development and verification of a Japanese pediatric PBPK population. The development of the model was based on the existing North European pediatric population. Japanese systems and clinical data were collated from public databases and the literature, and the underlying demographics and equations were optimized so that physiological outputs represented the Japanese pediatric population. The model was tested using 14 different small molecule drugs, eliminated by a variety of pathways, including cytochrome P450 3A4 (CYP3A4) metabolism and renal excretion. Given the limitations of the clinical data, the overall performance of the model was good, with 44/62 predictions for PK parameters (area under the plasma drug concentration-time curve, AUC; maximum serum concentration, Cmax ; clearance, CL) being within 0.8- to 1.25-fold, 56/62 within 0.67- to 1.5-fold, and 61/62 within 0.5- to 2.0-fold of the observed values. Specific results for the 5 CYP3A4 substrates showed 20/31 cases were predicted within 0.8- to 1.25-fold, 27/31 within 0.67- to 1.5-fold, and all were within 0.5- to 2.0-fold of the observed values. Given the increased regulatory use of pediatric PBPK in drug development, expanding these models to other ethnic groups are important. Considering qualifying these models based on the context of use, there is a need to expand on the current research to include a larger range of drugs with different elimination pathways. Collaboration among academic, industry, model providers, and regulators will facilitate further development.

Another Step Toward Qualification of Pediatric Physiologically Based Pharmacokinetic Models to Facilitate Inclusivity and Diversity in Pediatric Clinical Studies.

Robust prediction of pharmacokinetics (PKs) in pediatric subjects of diverse ages, ethnicities, and morbidities is critical. Qualification of pediatric physiologically-based pharmacokinetic (P-PBPK) models is an essential step toward enabling precision dosing of these vulnerable groups. Twenty-two manuscripts involving P-PBPK predictions and corresponding observed PK data (e.g., area under the curve and clearance) for 22 small-molecule compounds metabolized by CYP (3A4, 1A2, and 2C9), UGT (1A9 and 2B7), FMO3, renal, non-renal, and complex routes were identified; ratios of mean predicted/observed (P/O) PK parameters were calculated. Seventy-eight of 115 mean predicted PK parameters were within 0.8 to 1.25-fold of observed data, 98 within 0.67 to 1.5-fold, 109 within 2-fold, and only 6 P/O ratios were outside of these bounds. A set of 12 CYP3A4-metabolized compounds and a set of 6 metabolized by other enzymes, CYP1A2 (1 compound), CYP2C9 (2 compounds), UGT1A9 (1 compound) and UGT2B7 (2 compounds) had 56 of 59 and 22 of 25 mean P/O ratios, respectively, that fell within the > 0.5 and < 2.0-fold boundaries. For compounds covering renal, non-renal, complex, and FM03 routes of elimination, 29 of 31 mean P/O ratios fell within the 0.67 to 1.5-fold bounds, including 4 of 5 P/O ratios from newborns. P-PBPK modeling and simulation is a strategic component of the complement of precision dosing methods and has a vital role to play in dose adjustment in vulnerable pediatric populations, such as those with disease or in different ethnic groups. Qualification of such models is an essential step toward acceptance of this methodology by regulators.

Physiologically Based Pharmacokinetics Modeling in the Neonatal Population-Current Advances, Challenges, and Opportunities.

Physiologically based pharmacokinetic (PBPK) modeling is an approach to predicting drug pharmacokinetics, using knowledge of the human physiology involved and drug physiochemical properties. This approach is useful when predicting drug pharmacokinetics in under-studied populations, such as pediatrics. PBPK modeling is a particularly important tool for dose optimization for the neonatal population, given that clinical trials rarely include this patient population. However, important knowledge gaps exist for neonates, resulting in uncertainty with the model predictions. This review aims to outline the sources of variability that should be considered with developing a neonatal PBPK model, the data that are currently available for the neonatal ontogeny, and lastly to highlight the data gaps where further research would be needed.

Physiologically Based Pharmacokinetic Modelling to Predict Imatinib Exposures in Cancer Patients with Renal Dysfunction: A Case Study.

Imatinib is mainly metabolised by CYP3A4 and CYP2C8 and is extensively bound to α-acid glycoprotein (AAG). A physiologically based pharmacokinetic (PBPK) model for imatinib describing the CYP3A4-mediated autoinhibition during multiple dosing in gastrointestinal stromal tumor patients with normal renal function was previously reported. After performing additional verification, the PBPK model was applied to predict the exposure of imatinib after multiple dosing in cancer patients with varying degrees of renal impairment. In agreement with the clinical data, there was a positive correlation between AAG levels and imatinib exposure. A notable finding was that for recovery of the observed data in cancer patients with moderate RI (CrCL 20 to 39 mL/min), reductions of hepatic CYP3A4 and CYP2C8 abundances, which reflect the effects of RI, had to be included in the simulations. This was not the case for mild RI (CrCL 40 to 50 mL/min). The results support the finding of the clinical study, which demonstrated that both AAG levels and the degree of renal impairment are key components that contribute to the interpatient variability associated with imatinib exposure. As indicated in the 2020 FDA draft RI guidance, PBPK modelling could be used to support an expanded inclusion of patients with RI in clinical studies.