Variability of physiologically based pharmacokinetic (PBPK) model parameters and their effects on PBPK model predictions in a risk assessment for perchloroethylene (PCE)

1993 ◽  
Vol 68 (1-2) ◽  
pp. 131-144 ◽  
Author(s):  
J.M. Gearhart ◽  
D.A. Mahle ◽  
R.J. Greene ◽  
C.S. Seckel ◽  
C.D. Flemming ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Pbpk Model ◽  
Model Parameters ◽  
Physiologically Based Pharmacokinetic ◽  
Model Predictions ◽  
Physiologically Based

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 Mechanistic Coupling of a Novel in silico Cotyledon Perfusion Model and a Physiologically Based Pharmacokinetic Model to Predict Fetal Acetaminophen Pharmacokinetics at Delivery

2021 ◽  
Vol 9 ◽  
Author(s):  
Paola Mian ◽  
Bridget Nolan ◽  
John N. van den Anker ◽  
Kristel van Calsteren ◽  
Karel Allegaert ◽  
...  
Keyword(s):  
Clinical Studies ◽  
In Silico ◽  
Pbpk Model ◽  
Umbilical Vein ◽  
Whole Body ◽  
Model Parameters ◽  
Drug Transfer ◽  
Physiologically Based Pharmacokinetic ◽  
Perfusion Model ◽  
Physiologically Based

Little is known about placental drug transfer and fetal pharmacokinetics despite increasing drug use in pregnant women. While physiologically based pharmacokinetic (PBPK) models can help in some cases to shed light on this knowledge gap, adequate parameterization of placental drug transfer remains challenging. A novel in silico model with seven compartments representing the ex vivo cotyledon perfusion assay was developed and used to describe placental transfer and fetal pharmacokinetics of acetaminophen. Unknown parameters were optimized using observed data. Thereafter, values of relevant model parameters were copied to a maternal-fetal PBPK model and acetaminophen pharmacokinetics were predicted at delivery after oral administration of 1,000 mg. Predictions in the umbilical vein were evaluated with data from two clinical studies. Simulations from the in silico cotyledon perfusion model indicated that acetaminophen accumulates in the trophoblasts; simulated steady state concentrations in the trophoblasts were 4.31-fold higher than those in the perfusate. The whole-body PBPK model predicted umbilical vein concentrations with a mean prediction error of 24.7%. Of the 62 concentration values reported in the clinical studies, 50 values (81%) were predicted within a 2-fold error range. In conclusion, this study presents a novel in silico cotyledon perfusion model that is structurally congruent with the placenta implemented in our maternal-fetal PBPK model. This allows transferring parameters from the former model into our PBPK model for mechanistically exploring whole-body pharmacokinetics and concentration-effect relationships in the placental tissue. Further studies should investigate acetaminophen accumulation and metabolism in the placenta as the former might potentially affect placental prostaglandin synthesis and subsequent fetal exposure.

scholarly journals A Physiologically Based Pharmacokinetic Model of Rifampin in Mice

2013 ◽  
Vol 57 (4) ◽  
pp. 1763-1771 ◽  
Author(s):  
Michael A. Lyons ◽  
Brad Reisfeld ◽  
Raymond S. H. Yang ◽  
Anne J. Lenaerts
Keyword(s):  
Pbpk Model ◽  
Oral Absorption ◽  
Whole Body ◽  
Model Parameters ◽  
Mathematical Framework ◽  
Physiologically Based Pharmacokinetic ◽  
Starting Point ◽  
Physiologically Based ◽  
Multiple Drugs

ABSTRACTOne problem associated with regimen-based development of antituberculosis (anti-TB) drugs is the difficulty of a systematic and thoroughin vivoevaluation of the large number of possible regimens that arise from consideration of multiple drugs tested together. A mathematical model capable of simulating the pharmacokinetics and pharmacodynamics of experimental combination chemotherapy of TB offers a way to mitigate this problem by extending the use of available data to investigate regimens that are not initially tested. In order to increase the available mathematical tools needed to support such a model for preclinical anti-TB drug development, we constructed a preliminary whole-body physiologically based pharmacokinetic (PBPK) model of rifampin in mice, using data from the literature. Interindividual variability was approximated using Monte Carlo (MC) simulation with assigned probability distributions for the model parameters. An MC sensitivity analysis was also performed to determine correlations between model parameters and plasma concentration to inform future model development. Model predictions for rifampin concentrations in plasma, liver, kidneys, and lungs, following oral administration, were generally in agreement with published experimental data from multiple studies. Sensitive model parameters included those descriptive of oral absorption, total clearance, and partitioning of rifampin between blood and muscle. This PBPK model can serve as a starting point for the integration of rifampin pharmacokinetics in mice into a larger mathematical framework, including the immune response toMycobacterium tuberculosisinfection, and pharmacokinetic models for other anti-TB drugs.

scholarly journals Physiologically Based Pharmacokinetic Modeling of Transdermal Selegiline and Its Metabolites for the Evaluation of Disposition Differences between Healthy and Special Populations

Pharmaceutics ◽  
2020 ◽  
Vol 12 (10) ◽  
pp. 942
Author(s):  
Santosh Kumar Puttrevu ◽  
Sumit Arora ◽  
Sebastian Polak ◽  
Nikunj Kumar Patel
Keyword(s):  
Pbpk Model ◽  
Systemic Exposure ◽  
Special Populations ◽  
Physiologically Based Pharmacokinetic Modeling ◽  
Primary Metabolites ◽  
Physiologically Based Pharmacokinetic ◽  
Significant Difference ◽  
Model Predictions ◽  
Physiologically Based ◽  
Simulation Results

A physiologically based pharmacokinetic (PBPK) model of selegiline (SEL), and its metabolites, was developed in silico to evaluate the disposition differences between healthy and special populations. SEL is metabolized to methamphetamine (MAP) and desmethyl selegiline (DMS) by several CYP enzymes. CYP2D6 metabolizes the conversion of MAP to amphetamine (AMP), while CYP2B6 and CYP3A4 predominantly mediate the conversion of DMS to AMP. The overall prediction error in simulated PK, using the developed PBPK model, was within 0.5–1.5-fold after intravenous and transdermal dosing in healthy and elderly populations. Simulation results generated in the special populations demonstrated that a decrease in cardiac output is a potential covariate that affects the SEL exposure in renally impaired (RI) and hepatic impaired (HI) subjects. A decrease in CYP2D6 levels increased the systemic exposure of MAP. DMS exposure increased due to a reduction in the abundance of CYP2B6 and CYP3A4 in RI and HI subjects. In addition, an increase in the exposure of the primary metabolites decreased the exposure of AMP. No significant difference between the adult and adolescent populations, in terms of PK, were observed. The current PBPK model predictions indicate that subjects with HI or RI may require closer clinical monitoring to identify any untoward effects associated with the administration of transdermal SEL patch.

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

scholarly journals Reconstructing Organophosphorus Pesticide Doses Using the Reversed Dosimetry Approach in a Simple Physiologically-Based Pharmacokinetic Model

2012 ◽  
Vol 2012 ◽  
pp. 1-8
Author(s):  
Chensheng Lu ◽  
Leo Andres
Keyword(s):  
Risk Assessment ◽  
Pharmacokinetic Model ◽  
Pbpk Model ◽  
Organophosphorus Pesticide ◽  
Pbpk Modeling ◽  
Physiologically Based Pharmacokinetic Model ◽  
Urinary Biomarker ◽  
Physiologically Based Pharmacokinetic ◽  
Physiologically Based ◽  
Composite Data

We illustrated the development of a simple pharmacokinetic (SPK) model aiming to estimate the absorbed chlorpyrifos doses using urinary biomarker data, 3,5,6-trichlorpyridinol as the model input. The effectiveness of the SPK model in the pesticide risk assessment was evaluated by comparing dose estimates using different urinary composite data. The dose estimates resulting from the first morning voids appeared to be lower than but not significantly different to those using before bedtime, lunch or dinner voids. We found similar trend for dose estimates using three different urinary composite data. However, the dose estimates using the SPK model for individual children were significantly higher than those from the conventional physiologically based pharmacokinetic (PBPK) modeling using aggregate environmental measurements of chlorpyrifos as the model inputs. The use of urinary data in the SPK model intuitively provided a plausible alternative to the conventional PBPK model in reconstructing the absorbed chlorpyrifos dose.

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.

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