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 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 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 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 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 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 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 Development of a Physiologically Based Pharmacokinetic Model for Hydroxychloroquine and Its Application in Dose Optimization in Specific COVID-19 Patients

2021 ◽  
Vol 11 ◽  
Author(s):  
Miao Zhang ◽  
Xueting Yao ◽  
Zhe Hou ◽  
Xuan Guo ◽  
Siqi Tu ◽  
...  
Keyword(s):  
Pbpk Model ◽  
Clinical Findings ◽  
Lung Model ◽  
Elderly Subjects ◽  
Distribution Data ◽  
Physiologically Based Pharmacokinetic ◽  
Physiologically Based ◽  
Drug Actions

In Feb 2020, we developed a physiologically-based pharmacokinetic (PBPK) model of hydroxychloroquine (HCQ) and integrated in vitro anti-viral effect to support dosing design of HCQ in the treatment of COVID-19 patients in China. This, along with emerging research and clinical findings, supported broader uptake of HCQ as a potential treatment for COVID-19 globally at the beginning of the pandemics. Therefore, many COVID-19 patients have been or will be exposed to HCQ, including specific populations with underlying intrinsic and/or extrinsic characteristics that may affect the disposition and drug actions of HCQ. It is critical to update our PBPK model of HCQ with adequate drug absorption and disposition mechanisms to support optimal dosing of HCQ in these specific populations. We conducted relevant in vitro and in vivo experiments to support HCQ PBPK model update. Different aspects of this model are validated using PK study from 11 published references. With parameterization informed by results from monkeys, a permeability-limited lung model is employed to describe HCQ distribution in the lung tissues. The updated model is applied to optimize HCQ dosing regimens for specific populations, including those taking concomitant medications. In order to meet predefined HCQ exposure target, HCQ dose may need to be reduced in young children, elderly subjects with organ impairment and/or coadministration with a strong CYP2C8/CYP2D6/CYP3A4 inhibitor, and be increased in pregnant women. The updated HCQ PBPK model informed by new metabolism and distribution data can be used to effectively support dosing recommendations for clinical trials in specific COVID-19 patients and treatment of patients with malaria or autoimmune diseases.

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