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).

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.

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.

Incorporation and Performance Verification of Hepatic Portal Blood Flow Shunting in Minimal and Full PBPK Models of Liver Cirrhosis

Patho-physiological changes in liver cirrhosis create portacaval shunts that allow blood flow to bypass the hepatic portal vein into the systemic circulation affecting drug pharmacokinetics (PKs). The objectives of this work were to implement a physiologically-based pharmacokinetic (PBPK) framework describing shunted blood flows in virtual patients with differing degrees of liver cirrhosis; and to assess the minimal and full PBPK model's performance using drugs with intermediate to high hepatic extraction. Single dose concentration-time profiles and PK parameters for oral ibrutinib, midazolam, propranolol, and buspirone were simulated in healthy volunteers (HVs) and subjects with cirrhosis (Child-Pugh severity score (CP-A, CP-B, or CP-C)). Model performance was verified by comparing predicted to observed fold-changes in PK parameters between HVs and cirrhotic subjects. The verified model was used to simulate the PK changes for simvastatin in patients with cirrhosis. The predicted area under the curve ratios (AUCCirr :AUCHV ) for ibrutinib were 3.38, 6.87, and 11.46 using the minimal PBPK model with shunt and 1.61, 2.58, and 4.33 without the shunt, these compared with observed values of 4.33, 8.14, and 9.04, respectively. For ibrutinib, propranolol, and buspirone, including a shunt in the PBPK model improved the prediction of the AUCCirr :AUCHV and maximum plasma concentration ratios (CmaxCirr :CmaxHV ). For midazolam, an intermediate extraction drug, the differences were less clear. Simulated simvastatin dose adjustments in cirrhosis suggested that 20 mg in CP-A and 10 mg in CP-B could be used clinically. A mechanistic model-informed understanding of the anatomic and pathophysiology of cirrhosis will facilitate improved dose prediction and adjustment in this vulnerable population.

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.

Quantification of drug metabolising enzymes and transporter proteins in the paediatric duodenum via LC-MS/MS proteomics using a QconCAT technique

Characterising the small intestine absorptive membrane is essential to enable prediction of the systemic exposure of oral formulations. In particular, the ontogeny of key intestinal Drug Metabolising Enzymes and Transporter (DMET) proteins involved in drug disposition needs to be elucidated to allow for accurate prediction of the PK profile of drugs in the paediatric cohort. Using pinch biopsies from the paediatric duodenum (n = 36; aged 11 months to 15 years), the abundance of 21 DMET proteins and two enterocyte markers were quantified via LC-MS/MS. An established LCMS nanoflow method was translated to enable analysis on a microflow LC system, and a new stable-isotope-labelled QconCAT standard developed to enable quantification of these proteins. Villin-1 was used to standardise abundancy values. The observed abundancies and ontogeny profiles, agreed with adult LC-MS/MS-based data, and historic paediatric data obtained via western blotting. A linear trend with age was observed for duodenal CYP3A4 and CES2 only. As this work quantified peptides on a pinch biopsy coupled with a microflow method, future studies using a wider population range are very feasible. Furthermore, this DMET ontogeny data can be used to inform paediatric PBPK modelling and to enhance the understanding of oral drug absorption and gut bioavailability in paediatric populations.

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.

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.

Implications of tree expansion in shrubland ecosystems for two generalist avian predators

Shrublands globally have undergone structural changes due to plant invasions, including the expansion of native trees. Removal of native conifer trees, especially juniper (Juniperus spp.), is occurring across the Great Basin of the western U.S. to support declining sagebrush (Artemisia spp.) habitats and associated wildlife species, such as greater sage-grouse (Centrocercus urophasianus). One justification for conifer removal is that it may improve survival of sagebrush-associated wildlife by reducing the abundance of avian predators. However, the relationship between conifer expansion and predator distributions has not been explicitly evaluated. Further, although structural characteristics of habitat are important for generalist predators, overall prey abundance may also affect habitat use by predators. We examined habitat use of common ravens (Corvus corax) and red-tailed hawks (Buteo jamaicensis), two generalist predators whose populations are increasing in western North America, to variation in structural characteristics and prey distributions in sagebrush habitat that has experienced conifer expansion. Structural characteristics of habitat were important predictors of habitat use for both ravens and red-tailed hawks, whereas measures of prey abundance were unimportant for both species likely because generalist predators can use a wide variety of food resources. Ravens, but not red-tailed hawks, responded positively to increasing cover of juniper and the probability of habitat use was highest (> 0.95) where juniper cover within 100 m was > 20%. Habitat use by red-tailed hawks, but not ravens, was greater near cliffs but was not associated with juniper cover. Our study suggests that the removal of conifer in similar environments may lower the probability of habitat use for ravens, a common predator with significant impacts on many prey species. Therefore, we suggest conifer removal may improve sage-grouse reproductive success and survival depending on responses to conifer removal from other predators. Our results may be reflective of similar changes in rangeland ecosystems around the world undergoing expansion of conifer and other woody vegetation. Though species identities differ from sagebrush habitats, generalist avian predators in other habitats may have similar relationships with structural resources.

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.

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.

Insights in the maturational processes influencing hydrocortisone pharmacokinetics in congenital adrenal hyperplasia patients using a middle-out approach

Introduction: Hydrocortisone is the standard of care in cortisol replacement therapy for congenital adrenal hyperplasia patients. Challenges in mimicking cortisol circadian rhythm and dosing individualization can be overcome by the support of mathematical modelling. Previously, a non-linear mixed-effects (NLME) model was developed based on clinical hydrocortisone pharmacokinetic (PK) pediatric and adult data. Additionally, a physiologically-based pharmacokinetic (PBPK) model was developed for adults and a pediatric model was obtained using maturation functions for relevant processes. In this work, a middle-out approach was applied. The aim was to investigate whether PBPK-derived maturation functions could provide a better description of hydrocortisone PK inter-individual variability when implemented in the NLME framework, with the goal of providing better individual predictions towards precision dosing at the patient level. Methods: Hydrocortisone PK data from 24 adrenal insufficiency pediatric patients and 30 adult healthy volunteers were used for NLME model development, while the PBPK model and maturation functions of clearance and cortisol binding globulin (CBG) were developed based on previous studies published in the literature. Results: Clearance (CL) estimates from both approaches were similar for children older than 1 year (CL/F increasing from around 150 L/h to 500 L/h), while CBG concentrations differed across the whole age range (CBG_NLME stable around 0.5 μM vs. steady increase from 0.35 to 0.8 μM for CBG _PBPK). PBPK-derived maturation functions were subsequently included in the NLME model. After inclusion of the maturation functions, none, a part of, or all parameters were re-estimated. However, the inclusion of CL and/or CBG maturation functions in the NLME model did not result in improved model performance for the CL maturation function (ΔOFV > -15.36) and the re-estimation of parameters using the CBG maturation function most often led to unstable models or individual CL prediction bias. Discussion: Three explanations for the observed discrepancies could be postulated, i) non-considered maturation of processes such as absorption or first-pass effect, ii) lack of patients between 1 and 12 months, iii) lack of correction of PBPK CL maturation functions derived from urinary concentration ratio data for the renal function relative to adults. These should be investigated in the future to determine how NLME and PBPK methods can work towards deriving insights into pediatric hydrocortisone PK.

Cytochrome P450 enzymes in the pediatric population: Connecting knowledge on P450 expression with pediatric pharmacokinetics

Cytochrome P450 enzymes play an important role in the pharmacokinetics, efficacy, and toxicity of drugs. Age-dependent changes in P450 enzyme expression have been studied based on several detection systems, as well as by deconvolution of in vivo pharmacokinetic data observed in pediatric populations. The age-dependent changes in P450 enzyme expression can be important determinants of drug disposition in childhood, in addition to the changes in body size and the other physiological parameters, and effects of pharmacogenetics and disease on organ functions. As a tool incorporating drug-specific and body-specific factors, physiologically-based pharmacokinetic (PBPK) models have become increasingly used to characterize and explore mechanistic insights into drug disposition. Thus, PBPK models can be a bridge between findings from basic science and utilization in predictive science. Pediatric PBPK models incorporate additional system specific information on developmental physiology and ontogeny and have been used to predict pharmacokinetic parameters from preterm neonates onwards. These models have been advocated by regulatory authorities in order to support pediatric clinical trials. The purpose of this chapter is to highlight accumulated knowledge and findings from basic research focusing on P450 enzymes, as well as the current status and future challenges of expanding the utilization of pediatric PBPK modeling.

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 (C_max) 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.

Increasing application of pediatric physiologically based pharmacokinetic models across academic and industry organizations

There has been a significant increase in the use of physiologically based pharmacokinetic (PBPK) models during the past 20 years, especially for pediatrics. The aim of this study was to give a detailed overview of the growth and areas of application of pediatric PBPK (P‐PBPK) models. A total of 181 publications and publicly available regulatory reviews were identified and categorized according to year, author affiliation, platform, and primary application of the P‐PBPK model (in clinical settings, drug development or to advance pediatric model development in general). Secondary application areas, including dose selection, biologics, and drug interactions, were also assessed. The growth rate for P‐PBPK modeling increased 33‐fold between 2005 and 2020; this was mainly attributed to growth in clinical and drug development applications. For primary applications, 50% of articles were classified under clinical, 18% under drug development, and 33% under model development. The most common secondary applications were dose selection (75% drug development), pharmacokinetic prediction and covariate identification (47% clinical), and model parameter identification (68% model development), respectively. Although population PK modeling remains the mainstay of approaches supporting pediatric drug development, the data presented here demonstrate the widespread application of P‐PBPK models in both drug development and clinical settings. Although applications for pharmacokinetic and drug–drug interaction predictions in pediatrics is advocated, this approach remains underused in areas such as assessment of pediatric formulations, toxicology, and trial design. The increasing number of publications supporting the development and refinement of the pediatric model parameters can only serve to enhance optimal use of P‐PBPK models.

Physiologically-Based Pharmacokinetic Modeling to Investigate the Effect of Maturation on Buprenorphine Pharmacokinetics in Newborns with Neonatal Opioid Withdrawal Syndrome

Neonatal opioid withdrawal syndrome (NOWS) is a major public health concern whose incidence has paralleled the opioid epidemic in the United States. Sublingual buprenorphine is an emerging treatment for NOWS, but given concerns about long-term adverse effects of perinatal opioid exposure, precision dosing of buprenorphine is needed. Buprenorphine pharmacokinetics (PK) in newborns, however, is highly variable. To evaluate underlying sources of PK variability, a neonatal physiologically-based pharmacokinetic (PBPK) model of sublingual buprenorphine was developed using Simcyp (version 19.1). The PBPK model included metabolism by cytochrome P450 (CYP) 3A4, CYP2C8, UDP-glucuronosyltransferase (UGT) 1A1, UGT1A3, UGT2B7, and UGT2B17, with additional biliary excretion. Maturation of metabolizing enzymes was incorporated, and default CYP2C8 and UGT2B7 ontogeny profiles were updated according to recent literature. A biliary clearance developmental profile was outlined using clinical data from neonates receiving sublingual buprenorphine as NOWS treatment. Extensive PBPK model validation in adults demonstrated good predictability, with geometric mean (95% confidence interval (CI)) predicted/observed ratios (P/O ratios) of area under the curve from zero to infinity (AUC_0-∞ ), peak concentration (C_max ), and time to reach peak concentration (T_max ) equaling 1.00 (0.74-1.33), 1.04 (0.84-1.29), and 0.95 (0.72-1.26), respectively. In neonates, the geometric mean (95% CI) P/O ratio of whole blood concentrations was 0.75 (95% CI 0.64-0.87). PBPK modeling and simulation demonstrated that variability in biliary clearance, sublingual absorption, and CYP3A4 abundance are likely important drivers of buprenorphine PK variability in neonates. The PBPK model could be used to guide development of improved buprenorphine starting dose regimens for the treatment of NOWS.

Are body surface area based estimates of liver volume applicable to children with overweight or obesity? An in vivo validation study

The liver is the primary organ responsible for clearing most drugs from the body and thus determines systemic drug concentrations over time. Drug clearance by the liver appears to be directly related to organ size. In children, organ size changes as children age and grow. Liver volume has been correlated with body surface area (BSA) in healthy children and adults and has been estimated by functions of BSA. However, these relationships were derived from "typical" populations and it is unknown whether they extend to estimations of liver volumes for population "outliers," such as children with overweight or obesity, who today represent one-third of the pediatric population. Using computerized tomography or magnetic resonance imaging, this study measured liver volumes in 99 children (2-21 years) with normal weight, overweight, or obesity and compared organ measurements with estimates calculated using an established liver volume equation. A previously developed equation relating BSA to liver volume adequately estimates liver volumes in children, regardless of weight status.

A best practice framework for applying physiologically-based pharmacokinetic modeling to pediatric drug development

Pediatric physiologically‐based pharmacokinetic (PBPK) models have broad application in the drug development process and are being used not only to project doses for clinical trials but increasingly to replace clinical studies. However, the approach has yet to become fully integrated in regulatory submissions. Emerging data support an expanded integration of the PBPK model informed approach in regulatory guidance on pediatrics. Best practice standards are presented for further development through interaction among regulators, industry, and model providers.

Physiologically Based Pharmacokinetic Modeling and Allometric Scaling in Pediatric Drug Development: Where Do We Draw the Line?

Developing medicines for children is now established in legislation in both the United States and Europe; new drugs require pediatric study or investigation plans as part of their development. Particularly in early age groups, many developmental processes are not reflected by simple scalars such as body weight or body surface area, and even projecting doses based on simple allometric scaling can lead to significant overdoses in certain age groups. Modeling and simulation methodology, including physiologically based modeling, has evolved as part of the drug development toolkit and is being increasingly applied to various aspects of pediatric drug development. Pediatric physiologically based pharmacokinetic (PBPK) models account for the development of organs and the ontogeny of specific enzymes and transporters that determine the age-related pharmacokinetic profiles. However, when should this approach be used, and when will simpler methods such as allometric scaling suffice in answering specific problems? The aim of this review article is to illustrate the application of allometric scaling and PBPK in pediatric drug development and explore the optimal application of the latter approach with reference to case examples. In reality, allometric scaling included as part of population pharmacokinetic and PBPK approaches are all part of a model-informed drug development toolkit helping with decision making during the process of drug discovery and development; to that end, they should be viewed as complementary.

A Preterm Physiologically Based Pharmacokinetic Model. Part I: Physiological Parameters and Model Building

BACKGROUND

Developmental physiology can alter pharmacotherapy in preterm populations. Because of ethical and clinical constraints in studying this vulnerable age group, physiologically based pharmacokinetic models offer a viable alternative approach to predicting drug pharmacokinetics and pharmacodynamics in this population. However, such models require comprehensive information on the changes of anatomical, physiological and biochemical variables, where such data are not available in a single source.

OBJECTIVE

The objective of this study was to integrate the relevant physiological parameters required to build a physiologically based pharmacokinetic model for the preterm population.

METHODS

Published information on developmental preterm physiology and some drug-metabolising enzymes were collated and analysed. Equations were generated to describe the changes in parameter values during growth.

RESULTS

Data on organ size show different growth patterns that were quantified as functions of bodyweight to retain physiological variability and correlation. Protein binding data were quantified as functions of age as the body weight was not reported in the original articles. Ontogeny functions were derived for cytochrome P450 1A2, 3A4 and 2C9. Tissue composition values and how they change with age are limited.

CONCLUSIONS

Despite the limitations identified in the availability of some tissue composition values, the data presented in this article provide an integrated resource of system parameters needed for building a preterm physiologically based pharmacokinetic model.

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., C_max, 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.

Fetal Physiologically Based Pharmacokinetic Models: Systems Information on Fetal Cardiac Output and Its Distribution to Different Organs during Development

BACKGROUND AND OBJECTIVE

Fetal circulation is unique and the parameters describing hemodynamic status during development are critical for constructing a fetal physiologically based pharmacokinetic model. To date, a comprehensive review of circulatory changes during fetal development, with a specific focus on developing these models, has not been reported. The objective of this work was to collate, analyze, and mathematically describe physiological information on fetal cardiac output and tissue blood flows during development.

METHODS

A comprehensive literature search was carried out to collate and evaluate the changes to fetal cardiac output and fetal tissue blood flows during growth. The collated data were assessed, integrated, and analyzed to establish continuous mathematical functions describing the average parameter changes and variability during development.

RESULTS

Data were available for fetal cardiac output (14 Doppler studies), blood flow through the fetal umbilical vein (15 studies), ductus venosus (6 studies), liver veins (5 studies), brain (4 studies), lungs (5 studies), and kidneys (2 studies). Fetal cardiac output is described as either an age- or weight-dependent function. The latter is preferred as it generates an individualized cardiac output that is correlated to the fetal body weight. Blood flow as a proportion of fetal cardiac output to the liver, placenta, brain, kidneys, and lungs was age varying, whilst for the adipose, bone, heart, muscle, and skin the blood flow proportions were fixed. The pattern of change (with respect to direction and pace) for each of these parameters was different.

CONCLUSIONS

Despite limitations in the availability of some values, the collected data provide a useful resource for fetal physiologically based pharmacokinetic modeling. Potential applications of these data include predicting xenobiotic exposure and risk assessment in the fetus following the administration of maternally dosed drugs or unintended exposure to environmental toxicants.

Pediatric Pharmacokinetics and Dose Predictions: A Report of a Satellite Meeting to the 10th Juvenile Toxicity Symposium

On April 24, 2019, a symposium on Pediatric Pharmacokinetics and Dose Predictions was held as a satellite meeting to the 10th Juvenile Toxicity Symposium. This symposium brought together scientists from academia, industry, and clinical research organizations with the aim to update each other on the current knowledge on pediatric drug development. Through more knowledge on specific ontogeny profiles of drug metabolism and transporter proteins, integrated into physiologically-based pharmacokinetic (PBPK) models, we have gained a more integrated understanding of age-related differences in pharmacokinetics (PKs), Relevant examples were presented during the meeting. PBPK may be considered the gold standard for pediatric PK prediction, but still it is important to know that simpler methods, such as allometry, allometry combined with maturation function, functions based on the elimination pathway, or linear models, also perform well, depending on the age range or the mechanisms involved. Knowledge from different methods and information sources should be combined (e.g., microdosing can reveal early read-out of age-related differences in exposure), and such results can be a value to verify models. To further establish best practices for dose setting in pediatrics, more in vitro and in vivo research is needed on aspects such as age-related changes in the exposure-response relationship and the impact of disease on PK. New information coupled with the refining of model-based drug development approaches will allow faster targeting of intended age groups and allow more efficient design of pediatric clinical trials.

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 5^th and 95^th 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.

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.

Chloroquine Dosing Recommendations for Pediatric COVID-19 Supported by Modeling and Simulation

As chloroquine (CHQ) is part of the Dutch Centre for Infectious Disease Control coronavirus disease 2019 (COVID-19) experimental treatment guideline, pediatric dosing guidelines are needed. Recent pediatric data suggest that existing World Health Organization (WHO) dosing guidelines for children with malaria are suboptimal. The aim of our study was to establish best-evidence to inform pediatric CHQ doses for children infected with COVID-19. A previously developed physiologically-based pharmacokinetic (PBPK) model for CHQ was used to simulate exposure in adults and children and verified against published pharmacokinetic data. The COVID-19 recommended adult dosage regimen of 44 mg/kg total was tested in adults and children to evaluate the extent of variation in exposure. Based on differences in area under the concentration-time curve from zero to 70 hours (AUC0-70h ) the optimal CHQ dose was determined in children of different ages compared with adults. Revised doses were re-introduced into the model to verify that overall CHQ exposure in each age band was within 5% of the predicted adult value. Simulations showed differences in drug exposure in children of different ages and adults when the same body-weight based dose is given. As such, we propose the following total cumulative doses: 35 mg/kg (CHQ base) for children 0-1 month, 47 mg/kg for 1-6 months, 55 mg/kg for 6 months-12 years, and 44 mg/kg for adolescents and adults, not to exceed 3,300 mg in any patient. Our study supports age-adjusted CHQ dosing in children with COVID-19 in order to avoid suboptimal or toxic doses. The knowledge-driven, model-informed dose selection paradigm can serve as a science-based alternative to recommend pediatric dosing when pediatric clinical trial data is absent.

Pharmacodynamic studies of nasal tetracosactide with salivary glucocorticoids for a noninvasive Short Synacthen Test

CONTEXT

The Short Synacthen Test (SST) is the gold standard for diagnosing adrenal insufficiency. It requires invasive administration of Synacthen, venous sampling, and is resource-intensive.

OBJECTIVE

To develop a nasally administered SST, with salivary glucocorticoids measurement, to assess the adrenal response.

DESIGN

We conducted 5 studies: 4 open-label, sequence-randomized, crossover, pharmacodynamic studies testing 6 doses/formulations and a repeatability study. Additionally, pharmacokinetic analysis was undertaken using our chosen formulation, 500 µg tetracosactide with mucoadhesive chitosan, Nasacthin003, in our pediatric study.

SETTING

Adult and children's clinical research facilities.

PARTICIPANTS

A total of 36 healthy adult males and 24 healthy children.

INTERVENTION

We administered all 6 nasal formulations using an European regulator endorsed atomization device. The IV comparators were 250 µg or 1 µg SST.

MAIN OUTCOME MEASURES

We analyzed paired blood and saliva samples for plasma cortisol and salivary cortisol and cortisone.

RESULTS

The addition of chitosan to tetracosactide and dose escalation increased peak cortisol response (P = 0.01 and 0.001, respectively). The bioavailability of Nasacthin003 was 14.3%. There was no significant difference in plasma cortisol at 60 minutes between 500 µg Nasacthin003 and 250 µg IV Synacthen (P = 0.17). The repeatability coefficient at 60 minutes was 105 nmol/L for IV Synacthen and salivary cortisol and cortisone was 10.3 and 21.1 nmol/L, respectively. The glucocorticoid response in children was indistinguishable from that of adults.

CONCLUSIONS

Nasal administration of Nasacthin003 generates equivalent plasma cortisol values to the 250-µg IV SST and, with measurement at 60 minutes of salivary cortisol or cortisone, provides a noninvasive test for adrenal insufficiency.

Fetal Physiologically Based Pharmacokinetic Models: Systems Information on Fetal Blood Components and Binding Proteins

BACKGROUND

Fetal blood and plasma volume and binding components are critical parameters in a fetal physiologically based pharmacokinetic model. To date, a comprehensive review of their changes during fetal development has not been reported.

OBJECTIVE

The objective of this work was to collate and analyze physiological information on fetal blood and plasma volume and binding component data during development and to provide a mathematical description of these parameters that can be integrated within a fetal physiologically based pharmacokinetic model.

METHODS

A comprehensive literature search was conducted on fetal blood and plasma volume and binding component parameters and their changes during growth from apparently healthy fetuses from uncomplicated pregnancies. Collated data were assessed, integrated, and analyzed to establish continuous mathematical functions describing their growth trends with fetal age and weight.

RESULTS

Data were available from 14 studies for blood, ten studies for hematocrit, 12 studies for albumin, and four studies for alpha-1-acid glycoprotein, while plasma and red blood cell volumes were described based on blood and hematocrit data. Fetal physiologically based pharmacokinetic parameters, including blood, plasma and red blood cell volumes, hematocrit, serum albumin, and acid glycoprotein were quantified as a function of fetal age and weight. Variability around the mean parameters at different fetal ages was also investigated. The growth of each of these parameters was different (with respect to direction and monotonicity).

CONCLUSIONS

Despite the limitations identified in the availability of some values, the collected data presented in this article provide a useful resource for fetal physiologically based pharmacokinetic modeling. Potential applications include predicting xenobiotic exposure and risk assessment in the fetus following maternally administered drugs or unintended exposure to environmental toxicants.

Scaling Drug Clearance from Adults to the Young Children for Drugs Undergoing Hepatic Metabolism: A Simulation Study to Search for the Simplest Scaling Method

Previous research showed that scaling drug clearance from adults to children based on body weight alone is not accurate for all hepatically cleared drugs in very young children. This study systematically assesses the accuracy of scaling methods that, in addition to body weight, also take age-based variables into account for drugs undergoing hepatic metabolism in children younger than five years, namely scaling with (1) a body weight-based function using an age-dependent exponent (ADE) and (2) a body weight-based function with fixed exponent of 0.75 (AS0.75) combined with isoenzyme maturation functions (MF_PBPK) similar to those implemented in physiologically based pharmacokinetic (PBPK) models (AS0.75 + MF_PBPK). A PBPK-based simulation workflow was used, including hypothetical drugs with a wide range of properties and metabolized by different isoenzymes. Adult clearance values were scaled to seven typical children between one day and four years. Prediction errors of ± 50% were considered reasonably accurate. Isoenzyme maturation was found to be an important driver of changes in hepatic metabolic clearance in children younger than five years, which prevents the systematic accuracy of ADE scaling. AS0.75 + MF_PBPK, when accounting for maturation of isoenzymes and microsomal protein per gram of liver (MPPGL), can reasonably accurately scale hepatic metabolic clearance for all low and intermediate extraction ratio drugs except for drugs binding to alpha-1-acid glycoprotein in neonates. As differences in the impact of changes in system-specific parameters on drugs with different properties yield differences in clearance ontogeny, it is unlikely that for the remaining drugs, scaling methods that do not take drug properties into account will be systematically accurate.

A Theoretical Physiologically-Based Pharmacokinetic Approach to Ascertain Covariates Explaining the Large Interpatient Variability in Tacrolimus Disposition

Physiologically‐based pharmacokinetic (PBPK) modeling allows assessment of the covariates contributing to the large pharmacokinetic (PK) variability of tacrolimus; these include multiple physiological and biochemical differences among patients. A PBPK model of tacrolimus was developed, including a virtual population with physiological parameter distributions reflecting renal transplant patients. The ratios of predicted to observed dose‐normalized maximum plasma concentration (C_max), 0–12‐hour area under the concentration–time curve (AUC_0–12 hour), and trough plasma concentration (C_trough) ranged from 0.92‐fold to 1.15‐fold, indicating good predictive performance. The model quantitatively indicated the impact of cytochrome P450 (CYP)3A4 abundance, hematocrit, and serum albumin levels, in addition to CYP3A5 genotype status, on tacrolimus PK and associated variability. Age‐dependent change in tacrolimus trough concentration in pediatric patients was mainly attributed to the CYP3A ontogeny profile. This study demonstrates the utility of PBPK modeling as a tool for mechanistic and quantitative assessment of the impact of patient physiological differences on observed large PK variability.

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.

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.

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.

Constraints on Sub-GeV Dark-Matter-Electron Scattering from the DarkSide-50 Experiment

We present new constraints on sub-GeV dark-matter particles scattering off electrons based on 6780.0 kg d of data collected with the DarkSide-50 dual-phase argon time projection chamber. This analysis uses electroluminescence signals due to ionized electrons extracted from the liquid argon target. The detector has a very high trigger probability for these signals, allowing for an analysis threshold of three extracted electrons, or approximately 0.05 keVee. We calculate the expected recoil spectra for dark matter-electron scattering in argon and, under the assumption of momentum-independent scattering, improve upon existing limits from XENON10 for dark-matter particles with masses between 30 and 100  MeV/c^{2}.

Low-Mass Dark Matter Search with the DarkSide-50 Experiment

We present the results of a search for dark matter weakly interacting massive particles (WIMPs) in the mass range below 20  GeV/c^{2} using a target of low-radioactivity argon with a 6786.0 kg d exposure. The data were obtained using the DarkSide-50 apparatus at Laboratori Nazionali del Gran Sasso. The analysis is based on the ionization signal, for which the DarkSide-50 time projection chamber is fully efficient at 0.1  keVee. The observed rate in the detector at 0.5  keVee is about 1.5  event/keVee/kg/d and is almost entirely accounted for by known background sources. We obtain a 90% C.L. exclusion limit above 1.8  GeV/c^{2} for the spin-independent cross section of dark matter WIMPs on nucleons, extending the exclusion region for dark matter below previous limits in the range 1.8-6  GeV/c^{2}.

PBPK Model of Morphine Incorporating Developmental Changes in Hepatic OCT1 and UGT2B7 Proteins to Explain the Variability in Clearances in Neonates and Small Infants

Morphine has large pharmacokinetic variability, which is further complicated by developmental changes in neonates and small infants. The impacts of organic cation transporter 1 (OCT1) genotype and changes in blood-flow on morphine clearance (CL) were previously demonstrated in children, whereas changes in UDP-glucuronosyltransferase 2B7 (UGT2B7) activity showed a small effect. This study, targeting neonates and small infants, was designed to assess the influence of developmental changes in OCT1 and UGT2B7 protein expression and modified blood-flow on morphine CL using physiologically based pharmacokinetic (PBPK) modeling. The implementation of these three age-dependent factors into the pediatric system platform resulted in reasonable prediction for an age-dependent increase in morphine CL in these populations. Sensitivity of morphine CL to changes in cardiac output increased with age up to 3 years, whereas sensitivity to changes in UGT2B7 activity decreased. This study suggests that morphine exhibits age-dependent extraction, likely due to the developmental increase in OCT1 and UGT2B7 protein expression/activity and hepatic blood-flow.

Using a Vancomycin PBPK Model in Special Populations to Elucidate Case-Based Clinical PK Observations

Simultaneous changes in several physiological factors may contribute to the large pharmacokinetic (PK) variability of vancomycin. This study was designed to systematically characterize the effects of multiple physiological factors to the altered PK of vancomycin observed in special populations. A vancomycin physiologically based pharmacokinetic (PBPK) model was developed as a PK simulation platform to quantitatively assess the effects of changes in physiologies to the PK profiles. The developed model predicted the concentration-time profiles in healthy adults and diseased patients. The implementation of developmental changes in both renal and non-renal elimination pathways to the pediatric model improved the predictability of vancomycin clearance. Simulated PK profiles with a 50% decrease in cardiac output (peak plasma concentration (C_max ), 59.9 ng/mL) were similar to those observed in patients before bypass surgery (C_max , 55.1 ng/mL). The PBPK modeling of vancomycin demonstrated its potential to provide mechanistic insights into the altered disposition observed in patients who have changes in multiple physiological factors.

Drugs Being Eliminated via the Same Pathway Will Not Always Require Similar Pediatric Dose Adjustments

For scaling drug plasma clearance (CLp) from adults to children, extrapolations of population pharmacokinetic (PopPK) covariate models between drugs sharing an elimination pathway have enabled accelerated development of pediatric models and dosing recommendations. This study aims at identifying conditions for which this approach consistently leads to accurate pathway specific CLp scaling from adults to children for drugs undergoing hepatic metabolism. A physiologically based pharmacokinetic (PBPK) simulation workflow utilizing mechanistic equations defining hepatic metabolism was developed. We found that drugs eliminated via the same pathway require similar pediatric dose adjustments only in specific cases, depending on drugs extraction ratio, unbound fraction, type of binding plasma protein, and the fraction metabolized by the isoenzyme pathway for which CLp is scaled. Overall, between‐drug extrapolation of pediatric covariate functions for CLp is mostly applicable to low and intermediate extraction ratio drugs eliminated by one isoenzyme and binding to human serum albumin in children older than 1 month.

Bioavailability of Oral Hydrocortisone Corrected for Binding Proteins and Measured by LC-MS/MS Using Serum Cortisol and Salivary Cortisone

Context

The assessment absolute bioavailability of oral hydrocortisone is complicated by its saturable binding to cortisol binding globulin (CBG). Previous assessment of bioavailability used a cortisol radioimmunoassay which has cross reactivity with other steroids. Salivary cortisone is a measure of free cortisol and LC-MS/MS is the gold standard method for measuring steroids. We here report the absolute bioavailability of hydrocortisone calculated using serum cortisol and salivary cortisone measured by LC-MS/MS.

Methods

14 healthy male dexamethasone suppressed volunteers were administered 20 mg hydrocortisone either intravenously or orally by tablet. Samples of serum and saliva were taken and measured for cortisol and cortisone by LC-MS/MS. Serum cortisol was corrected for saturable binding using published data and pharmacokinetic parameters derived using the program WinNonlin.

Results

The mean (95% CI) bioavailability of oral hydrocortisone calculated from serum cortisol, unbound serum cortisol and salivary cortisone was 1.00 (0.89-1.14); 0.88 (0.75-1.05); and 0.93 (0.83-1.05), respectively.

Conclusion

The data confirm that, after oral administration, hydrocortisone is completely absorbed. The data derived from serum cortisol corrected for protein binding, and that from salivary cortisone, are similar supporting the concept that salivary cortisone reflects serum free cortisol levels and that salivary cortisone can be used as a non-invasive method for measuring the pharmacokinetics of hydrocortisone.

Predictive Performance of Physiologically Based Pharmacokinetic (PBPK) Modeling of Drugs Extensively Metabolized by Major Cytochrome P450s in Children

The accuracy of physiologically based pharmacokinetic (PBPK) model prediction in children, especially those younger than 2 years old, has not been systematically evaluated. The aim of this study was to characterize the pediatric predictive performance of the PBPK approach for 10 drugs extensively metabolized by CYP1A2 (theophylline), CYP2C8 (desloratidine, montelukast), CYP2C9 (diclofenac), CYP2C19 (esomeprazole, lansoprazole), CYP2D6 (tramadol), and CYP3A4 (itraconazole, ondansetron, sufentanil). Model performance in children was evaluated by comparing simulated plasma concentration-time profiles with observed clinical results for each drug and age group. PBPK models reasonably predicted the pharmacokinetics of desloratadine, diclofenac, itraconazole, lansoprazole, montelukast, ondansetron, sufentanil, theophylline, and tramadol across all age groups. Collectively, 58 out of 67 predictions were within 2-fold and 43 out of 67 predictions within 1.5-fold of observed values. Developed PBPK models can reasonably predict exposure in children age 1 month and older for an array of predominantly CYP metabolized drugs.

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 (θ_Baseline ) and body surface area (θ_BSA ), 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.

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 C_max 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).

Characterization of Contributing Factors to Variability in Morphine Clearance Through PBPK Modeling Implemented With OCT1 Transporter

Morphine shows large interindividual variability in its pharmacokinetics; however, the cause of this has not been fully addressed. The variability in morphine disposition is considered to be due to a combination of pharmacogenetic and physiological determinants related to morphine disposition. We previously reported the effect of organic cation transporter (OCT1) genotype on morphine disposition in pediatric patients. To further explore the underlying mechanisms for variability arising from relevant determinants, including OCT1, a physiologically based pharmacokinetic (PBPK) model of morphine was developed. The PBPK model predicted morphine concentration‐time profiles well, in both adults and children. Almost all of the observed morphine clearances in pediatric patients fell within a twofold range of median predicted values for each OCT1 genotype in each age group. This PBPK modeling approach quantitatively demonstrates that OCT1 genotype, age‐related growth, and changes in blood flow as important contributors to morphine pharmacokinetic (PK) variability.

Predictive Performance of Physiologically Based Pharmacokinetic and Population Pharmacokinetic Modeling of Renally Cleared Drugs in Children

Predictive performance of physiologically based pharmacokinetic (PBPK) and population pharmacokinetic (PopPK) models of drugs predominantly eliminated through kidney in the pediatric population was evaluated. After optimization using adult clinical data, the verified PBPK models can predict 33 of 34 drug clearance within twofold of the observed values in children 1 month and older. More specifically, 10 of 11 of predicted clearance values were within 1.5‐fold of those observed in children between 1 month and 2 years old. The PopPK approach also predicted 19 of 21 drug clearance within twofold of the observed values in children. In summary, our analysis demonstrated both PBPK and PopPK adult models, after verification with additional adult pharmacokinetic (PK) studies and incorporation of known ontogeny of renal filtration, could be applied for dosing regimen recommendation in children 1 month and older for renally eliminated drugs in a first‐in‐pediatric study.