scholarly journals Physiologically-Based Pharmacokinetic (PBPK) Modeling of Buprenorphine in Adults, Children and Preterm Neonates

Pharmaceutics ◽  
2020 ◽  
Vol 12 (6) ◽  
pp. 578 ◽  
Author(s):  
Lukas Kovar ◽  
Christina Schräpel ◽  
Dominik Selzer ◽  
Yvonne Kohl ◽  
Robert Bals ◽  
...  
Keyword(s):  
Drug Exposure ◽  
Geometric Mean ◽  
Pbpk Modeling ◽  
Preterm Neonates ◽  
Pharmacokinetic Studies ◽  
Acceptance Criterion ◽  
Pbpk Models ◽  
Physiologically Based Pharmacokinetic ◽  
Age Related ◽  
Physiologically Based

Buprenorphine plays a crucial role in the therapeutic management of pain in adults, adolescents and pediatric subpopulations. However, only few pharmacokinetic studies of buprenorphine in children, particularly neonates, are available as conducting clinical trials in this population is especially challenging. Physiologically-based pharmacokinetic (PBPK) modeling allows the prediction of drug exposure in pediatrics based on age-related physiological differences. The aim of this study was to predict the pharmacokinetics of buprenorphine in pediatrics with PBPK modeling. Moreover, the drug-drug interaction (DDI) potential of buprenorphine with CYP3A4 and P-glycoprotein perpetrator drugs should be elucidated. A PBPK model of buprenorphine and norbuprenorphine in adults has been developed and scaled to children and preterm neonates, accounting for age-related changes. One-hundred-percent of the predicted AUClast values in adults (geometric mean fold error (GMFE): 1.22), 90% of individual AUClast predictions in children (GMFE: 1.54) and 75% in preterm neonates (GMFE: 1.57) met the 2-fold acceptance criterion. Moreover, the adult model was used to simulate DDI scenarios with clarithromycin, itraconazole and rifampicin. We demonstrate the applicability of scaling adult PBPK models to pediatrics for the prediction of individual plasma profiles. The novel PBPK models could be helpful to further investigate buprenorphine pharmacokinetics in various populations, particularly pediatric subgroups.

scholarly journals Physiologically-Based Pharmacokinetic (PBPK) Modeling Providing Insights into Fentanyl Pharmacokinetics in Adults and Pediatric Patients

Pharmaceutics ◽  
2020 ◽  
Vol 12 (10) ◽  
pp. 908
Author(s):  
Lukas Kovar ◽  
Andreas Weber ◽  
Michael Zemlin ◽  
Yvonne Kohl ◽  
Robert Bals ◽  
...  
Keyword(s):  
Pbpk Model ◽  
Peak Plasma ◽  
Plasma Concentrations ◽  
Pbpk Modeling ◽  
Pharmacokinetic Studies ◽  
Pbpk Models ◽  
Physiologically Based Pharmacokinetic ◽  
Age Related ◽  
Physiologically Based ◽  
Pediatric Populations

Fentanyl is widely used for analgesia, sedation, and anesthesia both in adult and pediatric populations. Yet, only few pharmacokinetic studies of fentanyl in pediatrics exist as conducting clinical trials in this population is especially challenging. Physiologically-based pharmacokinetic (PBPK) modeling is a mechanistic approach to explore drug pharmacokinetics and allows extrapolation from adult to pediatric populations based on age-related physiological differences. The aim of this study was to develop a PBPK model of fentanyl and norfentanyl for both adult and pediatric populations. The adult PBPK model was established in PK-Sim® using data from 16 clinical studies and was scaled to several pediatric subpopulations. ~93% of the predicted AUClast values in adults and ~88% in pediatrics were within 2-fold of the corresponding value observed. The adult PBPK model predicted a fraction of fentanyl dose metabolized to norfentanyl of ~33% and a fraction excreted in urine of ~7%. In addition, the pediatric PBPK model was used to simulate differences in peak plasma concentrations after bolus injections and short infusions. The novel PBPK models could be helpful to further investigate fentanyl pharmacokinetics in both adult and pediatric populations.

scholarly journals A Physiologically-Based Pharmacokinetic (PBPK) Model Network for the Prediction of CYP1A2 and CYP2C19 Drug–Drug–Gene Interactions with Fluvoxamine, Omeprazole, S-mephenytoin, Moclobemide, Tizanidine, Mexiletine, Ethinylestradiol, and Caffeine

Pharmaceutics ◽  
2020 ◽  
Vol 12 (12) ◽  
pp. 1191
Author(s):  
Tobias Kanacher ◽  
Andreas Lindauer ◽  
Enrica Mezzalana ◽  
Ingrid Michon ◽  
Celine Veau ◽  
...  
Keyword(s):  
San Francisco ◽  
Drug Exposure ◽  
Pbpk Modeling ◽  
Whole Body ◽  
Validation Dataset ◽  
Extrinsic Factors ◽  
Time Profiles ◽  
Pbpk Models ◽  
Physiologically Based Pharmacokinetic ◽  
Physiologically Based

Physiologically-based pharmacokinetic (PBPK) modeling is a well-recognized method for quantitatively predicting the effect of intrinsic/extrinsic factors on drug exposure. However, there are only few verified, freely accessible, modifiable, and comprehensive drug–drug interaction (DDI) PBPK models. We developed a qualified whole-body PBPK DDI network for cytochrome P450 (CYP) CYP2C19 and CYP1A2 interactions. Template PBPK models were developed for interactions between fluvoxamine, S-mephenytoin, moclobemide, omeprazole, mexiletine, tizanidine, and ethinylestradiol as the perpetrators or victims. Predicted concentration–time profiles accurately described a validation dataset, including data from patients with genetic polymorphisms, demonstrating that the models characterized the CYP2C19 and CYP1A2 network over the whole range of DDI studies investigated. The models are provided on GitHub (GitHub Inc., San Francisco, CA, USA), expanding the library of publicly available qualified whole-body PBPK models for DDI predictions, and they are thereby available to support potential recommendations for dose adaptations, support labeling, inform the design of clinical DDI trials, and potentially waive those.

scholarly journals A Physiologically-Based Pharmacokinetic Framework for Prediction of Drug Exposure in Malnourished Children

Pharmaceutics ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 204
Author(s):  
Erik Sjögren ◽  
Joel Tarning ◽  
Karen I. Barnes ◽  
E. Niclas Jonsson
Keyword(s):  
Body Composition ◽  
Drug Exposure ◽  
Drug Disposition ◽  
Pediatric Population ◽  
Model Performance ◽  
Vulnerable Population ◽  
Pbpk Modeling ◽  
Malnourished Children ◽  
Physiologically Based Pharmacokinetic ◽  
Physiologically Based

Malnutrition in children is a global health problem, particularly in developing countries. The effects of an insufficient supply of nutrients on body composition and physiological functions may have implications for drug disposition and ultimately affect the clinical outcome in this vulnerable population. Physiologically-based pharmacokinetic (PBPK) modeling can be used to predict the effect of malnutrition as it links physiological changes to pharmacokinetic (PK) consequences. However, the absence of detailed information on body composition and the limited availability of controlled clinical trials in malnourished children complicates the establishment and evaluation of a generic PBPK model in this population. In this manuscript we describe the creation of physiologically-based bridge to a malnourished pediatric population, by combining information on (a) the differences in body composition between healthy and malnourished adults and (b) the differences in physiology between healthy adults and children. Model performance was confirmed using clinical reference data. This study presents a physiologically-based translational framework for prediction of drug disposition in malnourished children. The model is readily applicable for dose recommendation strategies to address the urgent medicinal needs of this vulnerable population.

scholarly journals Development of Physiologically Based Pharmacokinetic Model for Orally Administered Fexuprazan in Humans

Pharmaceutics ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 813
Author(s):  
Yoo-Seong Jeong ◽  
Min-Soo Kim ◽  
Nora Lee ◽  
Areum Lee ◽  
Yoon-Jee Chae ◽  
...  
Keyword(s):  
Gastric Acid ◽  
Pbpk Model ◽  
Pbpk Modeling ◽  
Drug Candidate ◽  
Metabolite Formation ◽  
Pbpk Models ◽  
Physiologically Based Pharmacokinetic ◽  
Physiologically Based

Fexuprazan is a new drug candidate in the potassium-competitive acid blocker (P-CAB) family. As proton pump inhibitors (PPIs), P-CABs inhibit gastric acid secretion and can be used to treat gastric acid-related disorders such as gastroesophageal reflux disease (GERD). Physiologically based pharmacokinetic (PBPK) models predict drug interactions as pharmacokinetic profiles in biological matrices can be mechanistically simulated. Here, we propose an optimized and validated PBPK model for fexuprazan by integrating in vitro, in vivo, and in silico data. The extent of fexuprazan tissue distribution in humans was predicted using tissue-to-plasma partition coefficients in rats and the allometric relationships of fexuprazan distribution volumes (VSS) among preclinical species. Urinary fexuprazan excretion was minimal (0.29–2.02%), and this drug was eliminated primarily by the liver and metabolite formation. The fraction absorbed (Fa) of 0.761, estimated from the PBPK modeling, was consistent with the physicochemical properties of fexuprazan, including its in vitro solubility and permeability. The predicted oral bioavailability of fexuprazan (38.4–38.6%) was within the range of the preclinical datasets. The Cmax, AUClast, and time-concentration profiles predicted by the PBPK model established by the learning set were accurately predicted for the validation sets.

scholarly journals Application of physiologically based pharmacokinetic modeling for sertraline dosing recommendations in pregnancy

2020 ◽  
Vol 6 (1) ◽  
Author(s):  
Blessy George ◽  
Annie Lumen ◽  
Christine Nguyen ◽  
Barbara Wesley ◽  
Jian Wang ◽  
...  
Keyword(s):  
Pregnant Women ◽  
Gestational Age ◽  
Drug Exposure ◽  
Pbpk Model ◽  
Pbpk Modeling ◽  
Quantitative Prediction ◽  
Pharmacokinetic Parameters ◽  
Physiologically Based Pharmacokinetic ◽  
Physiologically Based ◽  
In Pregnancy

Abstract Pregnancy is a period of significant change that impacts physiological and metabolic status leading to alterations in the disposition of drugs. Uncertainty in drug dosing in pregnancy can lead to suboptimal therapy, which can contribute to disease exacerbation. A few studies show there are increased dosing requirements for antidepressants in late pregnancy; however, the quantitative data to guide dose adjustments are sparse. We aimed to develop a physiologically based pharmacokinetic (PBPK) model that allows gestational-age dependent prediction of sertraline dosing in pregnancy. A minimal physiological model with defined gut, liver, plasma, and lumped placental-fetal compartments was constructed using the ordinary differential equation solver package, ‘mrgsolve’, in R. We extracted data from the literature to parameterize the model, including sertraline physicochemical properties, in vitro metabolism studies, disposition in nonpregnant women, and physiological changes during pregnancy. The model predicted the pharmacokinetic parameters from a clinical study with eight subjects for the second trimester and six subjects for the third trimester. Based on the model, gestational-dependent changes in physiology and metabolism account for increased clearance of sertraline (up to 143% at 40 weeks gestational age), potentially leading to under-dosing of pregnant women when nonpregnancy doses are used. The PBPK model was converted to a prototype web-based interactive dosing tool to demonstrate how the output of a PBPK model may translate into optimal sertraline dosing in pregnancy. Quantitative prediction of drug exposure using PBPK modeling in pregnancy will support clinically appropriate dosing and increase the therapeutic benefit for pregnant women.

scholarly journals Physiologically Based Pharmacokinetic (PBPK) Modeling of Metabolic Pathways of Bromochloromethane in Rats

2012 ◽  
Vol 2012 ◽  
pp. 1-14 ◽  
Author(s):  
W. S. Cuello ◽  
T. A. T. Janes ◽  
J. M. Jessee ◽  
M. A. Venecek ◽  
M. E. Sawyer ◽  
...  
Keyword(s):  
Binding Site ◽  
Metabolic Pathways ◽  
Glutathione Transferase ◽  
Pbpk Modeling ◽  
Pathway Model ◽  
Site Model ◽  
Pbpk Models ◽  
Physiologically Based Pharmacokinetic ◽  
Physiologically Based ◽  
Uptake Data

Bromochloromethane (BCM) is a volatile compound and a by-product of disinfection of water by chlorination. Physiologically based pharmacokinetic (PBPK) models are used in risk assessment applications. An updated PBPK model for BCM is generated and applied to hypotheses testing calibrated using vapor uptake data. The two different metabolic hypotheses examined are (1) a two-pathway model using both CYP2E1 and glutathione transferase enzymes and (2) a two-binding site model where metabolism can occur on one enzyme, CYP2E1. Our computer simulations show that both hypotheses describe the experimental data in a similar manner. The two pathway results were comparable to previously reported values (Vmax=3.8 mg/hour,Km=0.35 mg/liter, andkGST=4.7 /hour). The two binding site results wereVmax⁡1=3.7 mg/hour,Km⁡1=0.3 mg/hour, CL2= 0.047 liter/hour. In addition, we explore the sensitivity of different parameters for each model using our obtained optimized values.

scholarly journals A Physiologically Based Pharmacokinetic Framework for Prediction of Drug Exposure in Malnourished Children

2020 ◽  
Author(s):  
Erik Sjögren ◽  
Joel Tarning ◽  
Karen I. Barnes ◽  
E. Niclas Jonsson
Keyword(s):  
Body Composition ◽  
Drug Exposure ◽  
Drug Disposition ◽  
Pediatric Population ◽  
Model Performance ◽  
Vulnerable Population ◽  
Pbpk Modeling ◽  
Malnourished Children ◽  
Physiologically Based Pharmacokinetic ◽  
Physiologically Based

Malnutrition in children is a global health problem, particularly in developing countries. The effects of an insufficient supply of nutrients on body composition and physiological functions may have implications for drug disposition and ultimately affect the clinical outcome in this vulnerable population. Physiologically based pharmacokinetic (PBPK) modeling can be used to predict the effect of malnutrition as it links physiological changes to pharmacokinetic (PK) consequences. However, the absence of detailed information on body composition and the limited availability of controlled clinical trials in malnourished children complicates the establishment and evaluation of a generic PBPK model in this population. In this manuscript we describe the creation of physiologically-based bridge to a malnourished pediatric population, by combining information on a) the differences in body composition between healthy and malnourished adults and b) the differences in physiology between healthy adults and children. Model performance was confirmed using clinical reference data. This study presents a physiologically-based translational framework for prediction of drug disposition in malnourished children. The model is readily applicable for dose recommendation strategies to address the urgent medicinal needs of this vulnerable population.

Physiologically-based Pharmacokinetic (PBPK) Modeling for Prediction of the Optimal Dose Regimens of Quinine and Phenobarbital Co-administration in Adult Patients with Cerebral Malaria and Seizures

2020 ◽  
Author(s):  
Teerachat Saeheng ◽  
Juntra Karbwang ◽  
Rajith Kumar Reddy Rajoli ◽  
Marco Siccardi ◽  
Kesara Na-Bangchang
Keyword(s):  
Cerebral Malaria ◽  
Dose Regimen ◽  
Optimal Dose ◽  
Model Verification ◽  
Pbpk Modeling ◽  
Whole Body ◽  
Loading Dose ◽  
Pbpk Models ◽  
Physiologically Based Pharmacokinetic ◽  
Physiologically Based

Abstract Background: Cerebral malaria is a fatal disease. Patients with cerebral malaria are at risk of seizure development, therefore, the co-administration of antimalarial and antiepileptic drugs are needed. Quinine and phenobarbital are standard drugs for the treatment of cerebral malaria with seizures. However, there is no information on the optimal dosage regimens of both drugs when used concomitantly.T he study applied physiologically-based pharmacokinetic (PBPK) modeling for prediction of the optimal dose regimens of quinine and phenobarbital when co-administered in patients with cerebral malaria and concurrent seizures who carry wild type and polymorphic cytochrome P450 (CYP450) 2C9/2C19. Methods: The whole-body PBPK models for quinine and phenobarbital were constructed based on the previously published information using Simbiology®. One hundred virtual population were simulated. Four published articles were used for model verification. Sensitivity analysis was carried out to determine the effect of the changes in model parameters on AUC0–72h. Simulation of optimal dose regimens was based on standard drug-drug interactions (DDIs), and actual clinical use study approaches. Results: Dose adjustment of the standard regimen of phenobarbital is not required when co-administered with quinine. The proposed optimal dose regimen for quinine, when co-administered with phenobarbital for patients with a single or continuous seizure in all malaria-endemic areas regardless of CYP2C9/CYP2C19 genotypes, is a loading dose of 1,500 mg IV infusion over 8 hours, followed by 1,200 mg infusion over 8 hours given three times daily, or multiple doses of 1,400 mg IV infusion over 8 hours, given three times daily. In areas with quinine resistance, the dose regimen should be increased as a loading dose of 2,000 mg IV infusion over 8 hours, followed by 1,750 mg infusion over 8 hours given three times daily.Conclusion: The developed PBPK models are reliable, and successfully predicted the optimal doses regimens of quinine-phenobarbital co-administration with no requirement of CYP2C9/CYP2C19 genotyping.

scholarly journals Simulating Intestinal Transporter and Enzyme Activity in a Physiologically Based Pharmacokinetic Model for Tenofovir Disoproxil Fumarate

2017 ◽  
Vol 61 (7) ◽  
Author(s):  
Darren M. Moss ◽  
Paul Domanico ◽  
Melynda Watkins ◽  
Seonghee Park ◽  
Ryan Randolph ◽  
...  
Keyword(s):  
Enzyme Activity ◽  
Tenofovir Disoproxil Fumarate ◽  
Drug Exposure ◽  
Pbpk Model ◽  
Intestinal Transport ◽  
Pbpk Modeling ◽  
Time Curve ◽  
Physiologically Based Pharmacokinetic ◽  
Physiologically Based

ABSTRACT Tenofovir disoproxil fumarate (TDF), a prodrug of tenofovir, has oral bioavailability (25%) limited by intestinal transport (P-glycoprotein), and intestinal degradation (carboxylesterase). However, the influence of luminal pancreatic enzymes is not fully understood. Physiologically based pharmacokinetic (PBPK) modeling has utility for estimating drug exposure from in vitro data. This study aimed to develop a PBPK model that included luminal enzyme activity to inform dose reduction strategies. TDF and tenofovir stability in porcine pancrelipase concentrations was assessed (0, 0.48, 4.8, 48, and 480 U/ml of lipase; 1 mM TDF; 37°C; 0 to 30 min). Samples were analyzed using mass spectrometry. TDF stability and permeation data allowed calculation of absorption rates within a human PBPK model to predict plasma exposure following 6 days of once-daily dosing with 300 mg of TDF. Regional absorption of drug was simulated across gut segments. TDF was degraded by pancrelipase (half-lives of 0.07 and 0.62 h using 480 and 48 U/ml, respectively). Previously reported maximum concentration (C max; 335 ng/ml), time to C max (T max; 2.4 h), area under the concentration-time curve from 0 to 24 h (AUC0–24; 3,045 ng · h/ml), and concentration at 24 h (C 24; 48.3 ng/ml) were all within a 0.5-fold difference from the simulated C max (238 ng/ml), T max (3 h), AUC0–24 (3,036 ng · h/ml), and C 24 (42.7 ng/ml). Simulated TDF absorption was higher in duodenum and jejunum than in ileum (p<0.05). These data support that TDF absorption is limited by the action of intestinal lipases. Our results suggest that bioavailability may be improved by protection of drug from intestinal transporters and enzymes, for example, by coadministration of enzyme-inhibiting agents or nanoformulation strategies.

scholarly journals P01 Application of feto-placental-maternal physiologically-based pharmacokinetic model to predict tenofovir concentration during pregnancy

2019 ◽  
Vol 104 (6) ◽  
pp. e17.2-e18
Author(s):  
K Abduljalil ◽  
TN Johnson ◽  
M Jamei
Keyword(s):  
Tenofovir Disoproxil Fumarate ◽  
Drug Exposure ◽  
Pbpk Model ◽  
Model Parameters ◽  
List Type ◽  
Large Variability ◽  
Pbpk Models ◽  
Physiologically Based Pharmacokinetic ◽  
Physiologically Based ◽  
Fetal Organs

BackgroundTenofovir is a drug used in combination with other anti-HIV drugs to treat patients with HIV-1 infection. It is used during pregnancy to reduce the risk of HIV transmission to the child. The aim of this work is to use a Physiologically-Based Pharmacokinetic (PBPK) model for prediction of maternal and fetal tenofovir concentration at birth.MethodsA full Feto-Placental-Maternal PBPK model that includes placenta as a 3-comparment permeability limited organ and 14 compartments for different fetal organs was developed using physiological1,2 and drug specific parameters3 to predict tenofovir concentration in 50 virtual pregnant mothers at term after single administration of 600 mg of tenofovir disoproxil fumarate (272 mg tenofovir). The mechanistic model implemented using the Simcyp Lua interface within the Simcyp Simulator. Fetal as well as maternal tissue to plasma ratio values were predicted using the Rodgers & Rowland method with a scalar of 1.5. Predictions of tenofovir maternal and fetal plasma concentration were compared to reported observations.4ResultsIn spite of the large variability in the observed data, the model adequately replicated the maternal as well as fetal clinical observations.4 The placenta transfer by cotyledon was changed 10 times the mean reported value from perfusion experiment.5 All other model parameters were calculated using bottom-up approach.The maternal predicted-to-observed ratio for AUC24hr and Cmax was 1.13 and 1.08, respectively. The predicted fetal exposure was well predicted within the 5th and 95th percentiles and was 0.51 of maternal exposure (AUC24h), the reported value is 0.60.4ConclusionThe developed feto-placental-maternal PBPK models can be used to predict drug exposure in fetal organs during in utero growth. The inter-subject variability can be predicted incorporating both the drug physicochemical properties and system (placental, maternal and fetal) parameters.ReferencesAbduljalil, et al. Clin Pharmacokinet 2018;57(9):1149–1171.Abduljalil, et al. Clin Pharmacokinet 2019;58:235–262Gilead Sciences, Inc. Product Information: tenofovir disoproxil fumarate (VIREAD) tablets.Hirt D, et al., Clin Pharmacol Ther 2009; 85: 182–9.De Sousa Mendes, et al., Br J Clin Pharmacol 2016;81(4):646–57.Disclosure(s)Nothing to disclose

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