scholarly journals A Comprehensive Whole-Body Physiologically Based Pharmacokinetic Drug–Drug–Gene Interaction Model of Metformin and Cimetidine in Healthy Adults and Renally Impaired Individuals

2020 ◽  
Vol 59 (11) ◽  
pp. 1419-1431 ◽  
Author(s):  
Nina Hanke ◽  
Denise Türk ◽  
Dominik Selzer ◽  
Naoki Ishiguro ◽  
Thomas Ebner ◽  
...  
Pharmaceutics ◽  
2021 ◽  
Vol 13 (3) ◽  
pp. 331
Author(s):  
Fatima Zahra Marok ◽  
Laura Maria Fuhr ◽  
Nina Hanke ◽  
Dominik Selzer ◽  
Thorsten Lehr

The noradrenaline and dopamine reuptake inhibitor bupropion is metabolized by CYP2B6 and recommended by the FDA as the only sensitive substrate for clinical CYP2B6 drug–drug interaction (DDI) studies. The aim of this study was to build a whole-body physiologically based pharmacokinetic (PBPK) model of bupropion including its DDI-relevant metabolites, and to qualify the model using clinical drug–gene interaction (DGI) and DDI data. The model was built in PK-Sim® applying clinical data of 67 studies. It incorporates CYP2B6-mediated hydroxylation of bupropion, metabolism via CYP2C19 and 11β-HSD, as well as binding to pharmacological targets. The impact of CYP2B6 polymorphisms is described for normal, poor, intermediate, and rapid metabolizers, with various allele combinations of the genetic variants CYP2B6*1, *4, *5 and *6. DDI model performance was evaluated by prediction of clinical studies with rifampicin (CYP2B6 and CYP2C19 inducer), fluvoxamine (CYP2C19 inhibitor) and voriconazole (CYP2B6 and CYP2C19 inhibitor). Model performance quantification showed 20/20 DGI ratios of hydroxybupropion to bupropion AUC ratios (DGI AUCHBup/Bup ratios), 12/13 DDI AUCHBup/Bup ratios, and 7/7 DDGI AUCHBup/Bup ratios within 2-fold of observed values. The developed model is freely available in the Open Systems Pharmacology model repository.


Pharmaceutics ◽  
2020 ◽  
Vol 12 (12) ◽  
pp. 1200
Author(s):  
Simeon Rüdesheim ◽  
Jan-Georg Wojtyniak ◽  
Dominik Selzer ◽  
Nina Hanke ◽  
Felix Mahfoud ◽  
...  

The beta-blocker metoprolol (the sixth most commonly prescribed drug in the USA in 2017) is subject to considerable drug–gene interaction (DGI) effects caused by genetic variations of the CYP2D6 gene. CYP2D6 poor metabolizers (5.7% of US population) show approximately five-fold higher metoprolol exposure compared to CYP2D6 normal metabolizers. This study aimed to develop a whole-body physiologically based pharmacokinetic (PBPK) model to predict CYP2D6 DGIs with metoprolol. The metoprolol (R)- and (S)-enantiomers as well as the active metabolite α-hydroxymetoprolol were implemented as model compounds, employing data of 48 different clinical studies (dosing range 5–200 mg). To mechanistically describe the effect of CYP2D6 polymorphisms, two separate metabolic CYP2D6 pathways (α-hydroxylation and O-demethylation) were incorporated for both metoprolol enantiomers. The good model performance is demonstrated in predicted plasma concentration–time profiles compared to observed data, goodness-of-fit plots, and low geometric mean fold errors of the predicted AUClast (1.27) and Cmax values (1.23) over all studies. For DGI predictions, 18 out of 18 DGI AUClast ratios and 18 out of 18 DGI Cmax ratios were within two-fold of the observed ratios. The newly developed and carefully validated model was applied to calculate dose recommendations for CYP2D6 polymorphic patients and will be freely available in the Open Systems Pharmacology repository.


2020 ◽  
Vol 37 (12) ◽  
Author(s):  
Hannah Britz ◽  
Nina Hanke ◽  
Mitchell E. Taub ◽  
Ting Wang ◽  
Bhagwat Prasad ◽  
...  

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.


Pharmaceutics ◽  
2019 ◽  
Vol 11 (11) ◽  
pp. 578
Author(s):  
Muhammad F. Rasool ◽  
Sundus Khalid ◽  
Abdul Majeed ◽  
Hamid Saeed ◽  
Imran Imran ◽  
...  

The physiologically based pharmacokinetic (PBPK) approach facilitates the construction of novel drug–disease models by allowing incorporation of relevant pathophysiological changes. The aim of the present work was to explore and identify the differences in rifampicin pharmacokinetics (PK) after the application of its single dose in healthy and diseased populations by using PBPK drug–disease models. The Simcyp® simulator was used as a platform for modeling and simulation. The model development process was initiated by predicting rifampicin PK in healthy population after intravenous (i.v) and oral administration. Subsequent to successful evaluation in healthy population, the pathophysiological changes in tuberculosis and cirrhosis population were incorporated into the developed model for predicting rifampicin PK in these populations. The model evaluation was performed by using visual predictive checks and the comparison of mean observed/predicted ratios (ratio(Obs/pred)) of the PK parameters. The predicted PK parameters in the healthy population were in adequate harmony with the reported clinical data. The incorporation of pathophysiological changes in albumin concentration in the tuberculosis population revealed improved prediction of clearance. The developed PBPK drug–disease models have efficiently described rifampicin PK in tuberculosis and cirrhosis populations after administering single drug dose, as the ratio(Obs/pred) for all the PK parameters were within a two-fold error range. The mechanistic nature of the developed PBPK models may facilitate their extension to other diseases and drugs.


2018 ◽  
Vol 5 (suppl_1) ◽  
pp. S429-S430 ◽  
Author(s):  
Amit Desai ◽  
Laura Kovanda ◽  
Christopher Lademacher ◽  
William Hope ◽  
Michael Neely ◽  
...  

Abstract Background Best practice to establish dosage regimens for “first-in-pediatric” clinical trials requires knowledge of efficacious and safe exposures in adults. Methods Pediatric equivalent doses were predicted for patients aged 6 months and <18 years using physiologically based pharmacokinetic (PBPK) modeling, and compared with predictions by allometric scaling. All simulations were completed using PK-Sim®, which implements a whole-body PBPK model with 15 organs and appropriate maturation of anatomical and physiological parameters for children. The adult PBPK model was built using knowledge of drug physico-chemistry and clearance partitioning (CYP3A4, CYP3A5, glomerular filtration). PK data following IV (40, 80, 160 mg 60-minute infusion) and oral (100, 200, 400 mg capsule) doses in adults were used for initial model development. This model was validated by matching observed adult concentrations after multiple oral 200 mg doses. From this adult model, a virtual pediatric population (n = 4,600) from 6 months to <18 years was created. Simulations with the pediatric model assessed optimal doses of isavuconazonium sulfate based on age and weight to achieve at least a median steady-state daily area under the curve (AUCss) of 100 mg hour/L, and the majority below 230 mg hour/L. These targets were derived from efficacy and safety data in clinical trials with adults. Results As shown in the figure, an isavuconazonium sulfate dose of 10 mg/kg is expected to result in AUCss within the target range for the majority of patients >1 year old, in agreement with that predicted by allometry for patients aged 2–17 years. For patients aged 6 months to 1 year, a dose of 6 mg/kg predicts comparable exposures. Conclusion A proposed isavuconazonium sulfate dose of 10 mg/kg administered every 8 hours for the first 2 days and once daily thereafter is predicted to result in safe and efficacious steady state exposures in patients aged 1–17 years, similar to predictions from allometric scaling for patients aged 2–17 years. For subjects aged 6 months to 1 year, a dose of 6 mg/kg is predicted to achieve similar exposures. These doses should be tested in clinical trials to confirm. Disclosures A. Desai, Astellas Pharma, Inc.: Employee, Salary. L. Kovanda, Astellas Pharma, Inc.: Employee, Salary. C. Lademacher, Astellas Pharma, Inc.: Employee, Salary. W. Hope, F2G: Grant Investigator and Scientific Advisor, Consulting fee and Research grant. Astellas: Grant Investigator and Investigator, Grant recipient and Research grant. Pfizer: Grant Investigator, Research support. Gilead: Consultant and Scientific Advisor, Consulting fee. P. Bonate, Astellas Pharma, Inc.: Employee, Salary. A. Edginton, Astellas Pharma Global Development, Inc.: Independent Contractor, Consulting fee.


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