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 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 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.

A Physiologically Based Pharmacokinetic Model of Parathion Based on Chemical-Specific Parameters Determined In Vitro

1990 ◽  
Vol 9 (6) ◽  
pp. 611-619 ◽  
Author(s):  
Lester G. Sultatos
Keyword(s):  
Pbpk Model ◽  
Equilibrium Dialysis ◽  
Distribution Coefficients ◽  
Kinetic Constants ◽  
Pbpk Modeling ◽  
Pbpk Models ◽  
Physiologically Based Pharmacokinetic ◽  
Hepatic Extraction Ratio ◽  
Physiologically Based

Physiologically based pharmacokinetic (PBPK) modeling is an approach that has been used to predict successfully the pharmacokinetic disposition of numerous foreign chemicals. The accuracy of a PBPK model is dependent on the reliability of estimates of tissue/blood distribution coefficients (Kp) and appropriate kinetic constants descriptive of the elimination of the chemical under consideration. The present study evaluates the validity of the use of Kp values and kinetic constants determined in vitro for use in a PBPK model for the organothiophosphorus insecticide parathion. Kps were determined by equilibrium dialysis, whereas Vmaxs and Kms descriptive of the biotransformation of parathion were calculated from values determined previously in this laboratory. Using these kinetic constants to calculate a hepatic extraction ratio of parathion in the mouse yielded a value identical to that observed with mouse liver perfusions in situ performed previously in this laboratory. Use of Kp values and kinetic constants determined in vitro in a PBPK model accurately simulated levels of parathion in brain, lungs, blood, and liver up to 3 h after intravenous administration of this insecticide. This study demonstrates that chemical-specific parameters determined entirely in vitro can be used to construct accurate PBPK models.

scholarly journals 1315. No Dose Adjustment of Metformin with Fostemsavir Coadministration Based on Mechanistic Static and Physiologically Based Pharmacokinetic Models

2020 ◽  
Vol 7 (Supplement_1) ◽  
pp. S669-S669
Author(s):  
Dung N Nguyen ◽  
Xiusheng Miao ◽  
Mindy Magee ◽  
Guoying Tai ◽  
Peter D Gorycki ◽  
...  
Keyword(s):  
Dose Adjustment ◽  
Pbpk Model ◽  
Systemic Exposure ◽  
Multidrug Resistant ◽  
Pbpk Modeling ◽  
Repeat Dose ◽  
Physiologically Based Pharmacokinetic ◽  
Physiologically Based

Abstract Background Fostemsavir (FTR) is an oral prodrug of the first-in-class attachment inhibitor temsavir (TMR) which is being evaluated in patients with multidrug resistant HIV-1 infection. In vitro studies indicated that TMR and its 2 major metabolites are inhibitors of organic cation transporters (OCT)1, OCT2, and multidrug and toxin extrusion transporters (MATEs). To assess the clinical relevance, of OCT and MATE inhibition, mechanistic static DDI prediction with calculated Imax,u/IC50 ratios was below the cut-off limits for a DDI flag based on FDA guidelines and above the cut-off limits for MATEs based on EMA guidelines. Methods Metformin is a commonly used probe substrate for OCT1, OCT2 and MATEs. To predict the potential for a drug interaction between TMR and metformin, a physiologically based pharmacokinetic (PBPK) model for TMR was developed based on its physicochemical properties, in vitro and in vivo data. The model was verified and validated through comparison with clinical data. The TMR PBPK model accurately described AUC and Cmax within 30% of the observed data for single and repeat dose studies with or without food. The SimCYP models for metformin and ritonavir were qualified using literature data before applications of DDI prediction for TMR Results TMR was simulated at steady state concentrations after repeated oral doses of FTR 600 mg twice daily which allowed assessment of the potential OCT1, OCT2, and MATEs inhibition by TMR and metabolites. No significant increase in metformin systemic exposure (AUC or Cmax) was predicted with FTR co-administration. In addition, a sensitivity analysis was conducted for either hepatic OCT1 Ki, or renal OCT2 and MATEs Ki values. The model output indicated that, a 10-fold more potent Ki value for TMR would be required to have a ~15% increase in metformin exposure Conclusion Based on mechanistic static models and PBPK modeling and simulation, the OCT1/2 and MATEs inhibition potential of TMR and its metabolites on metformin pharmacokinetics is not clinically significant. No dose adjustment of metformin is necessary when co-administered with FTR Disclosures Xiusheng Miao, PhD, GlaxoSmithKline (Employee) Mindy Magee, Doctor of Pharmacy, GlaxoSmithKline (Employee, Shareholder) Peter D. Gorycki, BEChe, MSc, PhD, GSK (Employee, Shareholder) Katy P. Moore, PharmD, RPh, ViiV Healthcare (Employee)

scholarly journals Physiologically Based Pharmacokinetic Models of Probenecid and Furosemide to Predict Transporter Mediated Drug-Drug Interactions

2020 ◽  
Vol 37 (12) ◽  
Author(s):  
Hannah Britz ◽  
Nina Hanke ◽  
Mitchell E. Taub ◽  
Ting Wang ◽  
Bhagwat Prasad ◽  
...  
Keyword(s):  
Plasma Concentration ◽  
Organic Anion ◽  
Plasma Concentrations ◽  
Whole Body ◽  
Time Profiles ◽  
Pbpk Models ◽  
Physiologically Based Pharmacokinetic ◽  
Concentration Time ◽  
Anion Transporter ◽  
Physiologically Based

Abstract Purpose To provide whole-body physiologically based pharmacokinetic (PBPK) models of the potent clinical organic anion transporter (OAT) inhibitor probenecid and the clinical OAT victim drug furosemide for their application in transporter-based drug-drug interaction (DDI) modeling. Methods PBPK models of probenecid and furosemide were developed in PK-Sim®. Drug-dependent parameters and plasma concentration-time profiles following intravenous and oral probenecid and furosemide administration were gathered from literature and used for model development. For model evaluation, plasma concentration-time profiles, areas under the plasma concentration–time curve (AUC) and peak plasma concentrations (Cmax) were predicted and compared to observed data. In addition, the models were applied to predict the outcome of clinical DDI studies. Results The developed models accurately describe the reported plasma concentrations of 27 clinical probenecid studies and of 42 studies using furosemide. Furthermore, application of these models to predict the probenecid-furosemide and probenecid-rifampicin DDIs demonstrates their good performance, with 6/7 of the predicted DDI AUC ratios and 4/5 of the predicted DDI Cmax ratios within 1.25-fold of the observed values, and all predicted DDI AUC and Cmax ratios within 2.0-fold. Conclusions Whole-body PBPK models of probenecid and furosemide were built and evaluated, providing useful tools to support the investigation of transporter mediated DDIs.

scholarly journals Physiologically Based Pharmacokinetic Model of Rifapentine and 25-Desacetyl Rifapentine Disposition in Humans

2016 ◽  
Vol 60 (8) ◽  
pp. 4860-4868
Author(s):  
Todd J. Zurlinden ◽  
Garrett J. Eppers ◽  
Brad Reisfeld
Keyword(s):  
Time Course ◽  
Pbpk Model ◽  
Plasma Concentrations ◽  
Optimal Dose ◽  
Tissue Level ◽  
Pharmacokinetic Data ◽  
Rat Tissues ◽  
Content Type ◽  
Physiologically Based Pharmacokinetic ◽  
Physiologically Based

ABSTRACTRifapentine (RPT) is a rifamycin antimycobacterial and, as part of a combination therapy, is indicated for the treatment of pulmonary tuberculosis (TB) caused byMycobacterium tuberculosis. Although the results from a number of studies indicate that rifapentine has the potential to shorten treatment duration and enhance completion rates compared to other rifamycin agents utilized in antituberculosis drug regimens (i.e., regimens 1 to 4), its optimal dose and exposure in humans are unknown. To help inform such an optimization, a physiologically based pharmacokinetic (PBPK) model was developed to predict time course, tissue-specific concentrations of RPT and its active metabolite, 25-desacetyl rifapentine (dRPT), in humans after specified administration schedules for RPT. Starting with the development and verification of a PBPK model for rats, the model was extrapolated and then tested using human pharmacokinetic data. Testing and verification of the models included comparisons of predictions to experimental data in several rat tissues and time course RPT and dRPT plasma concentrations in humans from several single- and repeated-dosing studies. Finally, the model was used to predict RPT concentrations in the lung during the intensive and continuation phases of a current recommended TB treatment regimen. Based on these results, it is anticipated that the PBPK model developed in this study will be useful in evaluating dosing regimens for RPT and for characterizing tissue-level doses that could be predictors of problems related to efficacy or safety.

scholarly journals Development of a Physiologically Based Pharmacokinetic Model for Prediction of Ethanol Concentration-Time Profile in Different Organs

2020 ◽  
Author(s):  
Armin Sadighi ◽  
Lorenzo Leggio ◽  
Fatemeh Akhlaghi
Keyword(s):  
Pbpk Model ◽  
Organ Damage ◽  
Time Profile ◽  
Sensitivity Analyses ◽  
Pbpk Modeling ◽  
Time Curve ◽  
Physiologically Based Pharmacokinetic ◽  
Concentration Time ◽  
Physiologically Based

Abstract Aims A physiologically based pharmacokinetic (PBPK) modeling approach was used to simulate the concentration-time profile of ethanol (EtOH) in stomach, duodenum, plasma and other tissues upon consumption of beer and whiskey under fasted and fed conditions. Methods A full PBPK model was developed for EtOH using the advanced dissolution, absorption and metabolism (ADAM) model fully integrated into the Simcyp Simulator® 15 (Simcyp Ltd., Sheffield, UK). The prediction performance of the developed model was verified and the EtOH concentration-time profile in different organs was predicted. Results Simcyp simulation showed ≤ 2-fold difference in values of EtOH area under the concentration-time curve (AUC) in stomach and duodenum as compared to the observed values. Moreover, the simulated EtOH maximum concentration (Cmax), time to reach Cmax (Tmax) and AUC in plasma were comparable to the observed values. We showed that liver is exposed to the highest EtOH concentration, faster than other organs (Cmax = 839.50 mg/L and Tmax = 0.53 h), while brain exposure of EtOH (AUC = 1139.43 mg·h/L) is the highest among all other organs. Sensitivity analyses (SAs) showed direct proportion of EtOH rate and extent of absorption with administered EtOH dose and inverse relationship with gastric emptying time (GE) and steady-state volume of distribution (Vss). Conclusions The current PBPK model approach might help with designing in vitro experiments in the area of alcohol organ damage or alcohol-drug interaction studies.

scholarly journals Physiologically Based Pharmacokinetic Modelling for Nicotine and Cotinine Clearance in Pregnant Women

2021 ◽  
Vol 12 ◽  
Author(s):  
Basile Amice ◽  
Harvey Ho ◽  
En Zhang ◽  
Chris Bullen
Keyword(s):  
Pregnant Women ◽  
Pbpk Model ◽  
Research Report ◽  
Pharmacokinetic Parameters ◽  
Nicotine Concentration ◽  
Pbpk Models ◽  
Physiologically Based Pharmacokinetic ◽  
Physiologically Based ◽  
Fetal Organs ◽  
Temporal Profiles

Introduction: Physiologically based pharmacokinetic (PBPK) models for the absorption, disposition, metabolism and excretion (ADME) of nicotine and its major metabolite cotinine in pregnant women (p-PBPK) are rare. The aim of this short research report is to present a p-PBPK model and its simulations for nicotine and cotinine clearance.Methods: The maternal-placental-fetal compartments of the p-PBPK model contain a total of 16 compartments representing major maternal and fetal organs and tissue groups. Qualitative and quantitative data of nicotine and cotinine disposition and clearance have been incorporated into pharmacokinetic parameters.Results: The p-PBPK model reproduced the higher clearance rates of nicotine and cotinine in pregnant women than non-pregnant women. Temporal profiles for their disposition in organs such as the brain were also simulated. Nicotine concentration reaches its maximum value within 2 min after an intravenous injection.Conclusion: The proposed p-PBPK model produces results consistent with available data sources. Further pharmacokinetic experiments are required to calibrate clearance parameters for individual organs, and for the fetus.

scholarly journals 1,1-Difluoroethane Detection Time in Blood after Inhalation Abuse Estimated by Monte Carlo PBPK Modeling

Pharmaceutics ◽  
2020 ◽  
Vol 12 (10) ◽  
pp. 997 ◽  
Author(s):  
Raul Huet ◽  
Gunnar Johanson
Keyword(s):  
Body Mass Index ◽  
Monte Carlo ◽  
Body Mass ◽  
Pbpk Model ◽  
Sensitivity Analyses ◽  
Pbpk Modeling ◽  
Detection Time ◽  
Adverse Health Effects ◽  
Physiologically Based Pharmacokinetic ◽  
Physiologically Based

(1) Background: Inhalant abuse and misuse are still widespread problems. 1,1-Difluoroethane abuse is reported to be potentially fatal and to cause acute and chronic adverse health effects. Lab testing for difluoroethane is seldom done, partly because the maximum detection time (MDT) is unknown. We sought to reliably estimate the MDT of difluoroethane in blood after inhalation abuse; (2) Methods: MDT were estimated for the ad ult male American population using a physiologically based pharmacokinetic (PBPK) model and abuse patterns detailed by two individuals. Based on sensitivity analyses, variability in huffing pattern and body mass index was introduced in the model by Monte Carlo simulation; (3) Results: With a detection limit of 0.14 mg/L, the median MDT was estimated to be 10.5 h (5th–95th percentile 7.8–12.8 h) after the 2-h abuse scenario and 13.5 h (10.5–15.8 h) after the 6-h scenario. The ranges reflect variability in body mass index (and, hence, amount of body fat) and, more so, variable inhalation patterns; (4) Conclusions: Our simulations suggest that the MDT of difluoroethane in blood after abuse ranges from 7.8 to 15.8 h. Although shorter compared to many other drugs, these MDT are sufficient to allow for testing several hours after suspected intoxication in a patient.

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.

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