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 Prediction of survival after hepatectomy using a physiologically based pharmacokinetic model of indocyanine green liver function tests

2021 ◽  
Author(s):  
Adrian Köller ◽  
Jan Grzegorzewski ◽  
Michael Tautenhahn ◽  
Matthias König
Keyword(s):  
Liver Cirrhosis ◽  
Liver Resection ◽  
Indocyanine Green ◽  
Pbpk Model ◽  
Hepatic Function ◽  
Pharmacokinetic Data ◽  
Functional Evaluation ◽  
Physiologically Based Pharmacokinetic ◽  
Model Predictions ◽  
Physiologically Based

The evaluation of hepatic function and functional capacity of the liver are essential tasks in hepatology, especially in the context of liver surgery. Indocyanine Green (ICG) is a widely applied test compound that is used in clinical routine to evaluate hepatic function. Important questions for the functional evaluation with ICG in the context of hepatectomy are how liver disease such as cirrhosis alters ICG elimination, and if postoperative survival can be predicted from preoperative ICG measurements. Within this work a physiologically based pharmacokinetic (PBPK) model of ICG pharmacokinetics was developed and applied to the prediction of liver resection under various degrees of cirrhosis. For the parametrization of the computational model and validation of model predictions a database of ICG pharmacokinetic data was established. The model was applied (i) to study the effect of liver cirrhosis and hepatectomy on ICG pharmacokinetics; and (ii) to evaluate model-based prediction of postoperative ICG-R15 as a measure for postoperative outcome. Key results were that the model is able to accurately predict changes in ICG pharmacokinetics caused by liver cirrhosis and postoperative changes of ICG-elimination after liver resection, as validated with a wide range of data sets. Based on the PBPK model predictions a classifier allowed to predict survival after hepatectomy, demonstrating its potential value as a clinical tool.

scholarly journals A physiologically based pharmacokinetic model to predict the superparamagnetic iron oxide nanoparticles (SPIONs) accumulation in vivo

2017 ◽  
Vol 9 (2) ◽  
Author(s):  
Adny Henrique Silva ◽  
Enio Lima Jr ◽  
Marcelo Vasquez Mansilla ◽  
Roberto Daniel Zysler ◽  
Mary Luz Mojica Pisciotti ◽  
...  
Keyword(s):  
Iron Oxide ◽  
Iron Oxide Nanoparticles ◽  
Pbpk Model ◽  
Superparamagnetic Iron Oxide ◽  
Superparamagnetic Iron Oxide Nanoparticles ◽  
Oxide Nanoparticles ◽  
Pharmacokinetic Data ◽  
Physiologically Based Pharmacokinetic ◽  
Physiologically Based

AbstractSuperparamagnetic iron oxide nanoparticles (SPIONs) have been identified as a promising material for biomedical applications. These include as contrast agents for medical imaging, drug delivery and/or cancer cell treatment. The nanotoxicological profile of SPIONs has been investigated in different studies and the distribution of SPIONs in the human body has not been fully characterized. The aim of this study was to develop a physiologically-based pharmacokinetic (PBPK) model to predict the pharmacokinetics of SPIONs. The distribution and accumulation of SPIONs in organs were simulated taking into consideration their penetration through capillary walls and their active uptake by specialized macrophages in the liver, spleen and lungs. To estimate the kinetics of SPION uptake, a novel experimental approach using primary macrophages was developed. The murine PBPK model was validated against in vivo pharmacokinetic data, and accurately described accumulation in liver, spleen and lungs. After validation of the murine model, a similar PBPK approach was developed to simulate the distribution of SPIONs in humans. These data demonstrate the utility of PBPK modeling for estimating biodistribution of inorganic nanoparticles and represents an initial platform to provide computational prediction of nanoparticle pharmacokinetics.

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 Predicting Pharmacokinetics of a Tenofovir Alafenamide Subcutaneous Implant Using Physiologically Based Pharmacokinetic Modelling

2020 ◽  
Vol 64 (8) ◽  
Author(s):  
Rajith K. R. Rajoli ◽  
Zach R. Demkovich ◽  
Charles Flexner ◽  
Andrew Owen ◽  
Marco Siccardi
Keyword(s):  
Peripheral Blood ◽  
Pbpk Model ◽  
Mononuclear Cells ◽  
Plasma Concentrations ◽  
Antiretroviral Drugs ◽  
Release Rates ◽  
Peripheral Blood Mononuclear ◽  
Physiologically Based Pharmacokinetic ◽  
Physiologically Based ◽  
Tenofovir Alafenamide

ABSTRACT Long-acting (LA) administration using a subcutaneous (s.c.) implant presents opportunities to simplify administration of antiretroviral drugs, improve pharmacological profiles, and overcome suboptimal adherence associated with daily oral formulations. Tenofovir alafenamide (TAF) is a highly potent nucleoside reverse transcriptase inhibitor (NRTI) and an attractive agent for LA delivery, with a high potency and long intracellular half-life. The aim of this study was to predict minimum TAF doses required to achieve concentrations effective for HIV preexposure prophylaxis (PrEP). Daily drug release requirements were then ascertained by averaging across the dosing interval. A TAF physiologically based pharmacokinetic (PBPK) model was developed and partially qualified against available oral single- and multiple-dose pharmacokinetics. The models were assumed to be qualified when simulated values were within 2-fold of the observed mean. TAF s.c. implants were simulated in five hundred individuals, reporting predicted TAF plasma and tenofovir (TFV) plasma concentrations for various release rates. Intracellular TFV diphosphate (TFV-DP) concentrations were also simulated in peripheral blood cells and cervical and rectal tissues. The minimum dose predicted to achieve intracellular TFV-DP levels above a target concentration of 48 fmol/106 cells for a month was identified. TAF, TFV, and TFV-DP concentrations for release rates between 1.0 and 1.6 mg/day were simulated. The PBPK model indicated that a minimum release of 1.4 mg/day TAF is necessary to achieve TFV-DP concentrations above the identified target in peripheral blood mononuclear cells (PBMCs). TFV-DP cervical and rectal tissue concentrations were predicted to be between 1.5 and 2.0 fmol/106 cells and 0.9 and 1.1 fmol/106 cells, respectively, for release rates between 1.3 and 1.6 mg/day. These simulations provide target minimum doses for LA TAF PrEP in humans. Based on the generated results, multiple implants delivering a total of 1.4 mg/day of TAF subcutaneously could provide protection levels for approximately 6 months to 1 year. This modeling may inform future design of s.c. implants to mitigate adherence issues for effective PrEP applications.

scholarly journals Prediction of Survival After Partial Hepatectomy Using a Physiologically Based Pharmacokinetic Model of Indocyanine Green Liver Function Tests

2021 ◽  
Vol 12 ◽  
Author(s):  
Adrian Köller ◽  
Jan Grzegorzewski ◽  
Hans-Michael Tautenhahn ◽  
Matthias König
Keyword(s):  
Liver Cirrhosis ◽  
Liver Resection ◽  
Indocyanine Green ◽  
Pbpk Model ◽  
Hepatic Function ◽  
Pharmacokinetic Data ◽  
Functional Evaluation ◽  
Physiologically Based Pharmacokinetic ◽  
Wide Range ◽  
Physiologically Based

The evaluation of hepatic function and functional capacity of the liver are essential tasks in hepatology as well as in hepatobiliary surgery. Indocyanine green (ICG) is a widely applied test compound that is used in clinical routine to evaluate hepatic function. Important questions for the functional evaluation with ICG in the context of hepatectomy are how liver disease such as cirrhosis alters ICG elimination, and if postoperative survival can be predicted from preoperative ICG measurements. Within this work a physiologically based pharmacokinetic (PBPK) model of ICG was developed and applied to the prediction of the effects of a liver resection under various degrees of cirrhosis. For the parametrization of the computational model and validation of model predictions a database of ICG pharmacokinetic data was established. The model was applied (i) to study the effect of liver cirrhosis and liver resection on ICG pharmacokinetics; and (ii) to evaluate the model-based prediction of postoperative ICG-R15 (retention ratio 15 min after administration) as a measure for postoperative outcome. Key results are the accurate prediction of changes in ICG pharmacokinetics caused by liver cirrhosis and postoperative changes of ICG-elimination after liver resection, as validated with a wide range of data sets. Based on the PBPK model, individual survival after liver resection could be classified, demonstrating its potential value as a clinical tool.

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 Physiologically Based Pharmacokinetic Modelling of Cabozantinib to Simulate Enterohepatic Recirculation, Drug–Drug Interaction with Rifampin and Liver Impairment

Pharmaceutics ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 778
Author(s):  
Bettina Gerner ◽  
Oliver Scherf-Clavel
Keyword(s):  
Hepatic Impairment ◽  
Kinase Inhibitor ◽  
Plasma Concentrations ◽  
Area Under The Curve ◽  
Enterohepatic Recirculation ◽  
Maximum Plasma ◽  
Good Precision ◽  
Physiologically Based Pharmacokinetic ◽  
Starting Point ◽  
Physiologically Based

Cabozantinib (CAB) is a receptor tyrosine kinase inhibitor approved for the treatment of several cancer types. Enterohepatic recirculation (EHC) of the substance is assumed but has not been further investigated yet. CAB is mainly metabolized via CYP3A4 and is susceptible for drug–drug interactions (DDI). The goal of this work was to develop a physiologically based pharmacokinetic (PBPK) model to investigate EHC, to simulate DDI with Rifampin and to simulate subjects with hepatic impairment. The model was established using PK-Sim® and six human clinical studies. The inclusion of an EHC process into the model led to the most accurate description of the pharmacokinetic behavior of CAB. The model was able to predict plasma concentrations with low bias and good precision. Ninety-seven percent of all simulated plasma concentrations fell within 2-fold of the corresponding concentration observed. Maximum plasma concentration (Cmax) and area under the curve (AUC) were predicted correctly (predicted/observed ratio of 0.9–1.2 for AUC and 0.8–1.1 for Cmax). DDI with Rifampin led to a reduction in predicted AUC by 77%. Several physiological parameters were adapted to simulate hepatic impairment correctly. This is the first CAB model used to simulate DDI with Rifampin and hepatic impairment including EHC, which can serve as a starting point for further simulations with regard to special populations.

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.

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