scholarly journals Physiologically Based Pharmacokinetic Modeling of Rosuvastatin to Predict Transporter-Mediated Drug-Drug Interactions

2021 ◽  
Author(s):  
Nina Hanke ◽  
José David Gómez-Mantilla ◽  
Naoki Ishiguro ◽  
Peter Stopfer ◽  
Valerie Nock
Keyword(s):  
Drug Interactions ◽  
Pbpk Model ◽  
Open Systems ◽  
Whole Body ◽  
Good Prediction ◽  
Active Efflux ◽  
Physiologically Based Pharmacokinetic ◽  
Positron Emission ◽  
Physiologically Based

Abstract Purpose To build a physiologically based pharmacokinetic (PBPK) model of the clinical OATP1B1/OATP1B3/BCRP victim drug rosuvastatin for the investigation and prediction of its transporter-mediated drug-drug interactions (DDIs). Methods The Rosuvastatin model was developed using the open-source PBPK software PK-Sim®, following a middle-out approach. 42 clinical studies (dosing range 0.002–80.0 mg), providing rosuvastatin plasma, urine and feces data, positron emission tomography (PET) measurements of tissue concentrations and 7 different rosuvastatin DDI studies with rifampicin, gemfibrozil and probenecid as the perpetrator drugs, were included to build and qualify the model. Results The carefully developed and thoroughly evaluated model adequately describes the analyzed clinical data, including blood, liver, feces and urine measurements. The processes implemented to describe the rosuvastatin pharmacokinetics and DDIs are active uptake by OATP2B1, OATP1B1/OATP1B3 and OAT3, active efflux by BCRP and Pgp, metabolism by CYP2C9 and passive glomerular filtration. The available clinical rifampicin, gemfibrozil and probenecid DDI studies were modeled using in vitro inhibition constants without adjustments. The good prediction of DDIs was demonstrated by simulated rosuvastatin plasma profiles, DDI AUClast ratios (AUClast during DDI/AUClast without co-administration) and DDI Cmax ratios (Cmax during DDI/Cmax without co-administration), with all simulated DDI ratios within 1.6-fold of the observed values. Conclusions A whole-body PBPK model of rosuvastatin was built and qualified for the prediction of rosuvastatin pharmacokinetics and transporter-mediated DDIs. The model is freely available in the Open Systems Pharmacology model repository, to support future investigations of rosuvastatin pharmacokinetics, rosuvastatin therapy and DDI studies during model-informed drug discovery and development (MID3).

scholarly journals A Mechanistic, Enantioselective, Physiologically Based Pharmacokinetic Model of Verapamil and Norverapamil, Built and Evaluated for Drug–Drug Interaction Studies

Pharmaceutics ◽  
2020 ◽  
Vol 12 (6) ◽  
pp. 556 ◽  
Author(s):  
Nina Hanke ◽  
Denise Türk ◽  
Dominik Selzer ◽  
Sabrina Wiebe ◽  
Éric Fernandez ◽  
...  
Keyword(s):  
Drug Interaction ◽  
Pharmacokinetic Model ◽  
Competitive Inhibition ◽  
Open Systems ◽  
Whole Body ◽  
Physiologically Based Pharmacokinetic ◽  
Physiologically Based ◽  
Drug Drug Interaction ◽  
Enantioselective Metabolism

The calcium channel blocker and antiarrhythmic agent verapamil is recommended by the FDA for drug–drug interaction (DDI) studies as a moderate clinical CYP3A4 index inhibitor and as a clinical Pgp inhibitor. The purpose of the presented work was to develop a mechanistic whole-body physiologically based pharmacokinetic (PBPK) model to investigate and predict DDIs with verapamil. The model was established in PK-Sim®, using 45 clinical studies (dosing range 0.1–250 mg), including literature as well as unpublished Boehringer Ingelheim data. The verapamil R- and S-enantiomers and their main metabolites R- and S-norverapamil are represented in the model. The processes implemented to describe the pharmacokinetics of verapamil and norverapamil include enantioselective plasma protein binding, enantioselective metabolism by CYP3A4, non-stereospecific Pgp transport, and passive glomerular filtration. To describe the auto-inhibitory and DDI potential, mechanism-based inactivation of CYP3A4 and non-competitive inhibition of Pgp by the verapamil and norverapamil enantiomers were incorporated based on in vitro literature. The resulting DDI performance was demonstrated by prediction of DDIs with midazolam, digoxin, rifampicin, and cimetidine, with 21/22 predicted DDI AUC ratios or Ctrough ratios within 1.5-fold of the observed values. The thoroughly built and qualified model will be freely available in the Open Systems Pharmacology model repository to support model-informed drug discovery and development.

scholarly journals Physiologically-Based Pharmacokinetic Modeling for Drug-Drug Interactions of Procainamide and N-Acetylprocainamide with Cimetidine, an Inhibitor of rOCT2 and rMATE1, in Rats

Pharmaceutics ◽  
2019 ◽  
Vol 11 (3) ◽  
pp. 108 ◽  
Author(s):  
Yoo-Seong Jeong ◽  
Anusha Balla ◽  
Kwang-Hoon Chun ◽  
Suk-Jae Chung ◽  
Han-Joo Maeng
Keyword(s):  
Urinary Excretion ◽  
Drug Interactions ◽  
Pbpk Model ◽  
Systemic Exposure ◽  
Renal Elimination ◽  
Physiologically Based Pharmacokinetic ◽  
Pharmacokinetic Interactions ◽  
Physiologically Based

Previous observations demonstrated that cimetidine decreased the clearance of procainamide (PA) and/or N-acetylprocainamide (NAPA; the primary metabolite of PA) resulting in the increased systemic exposure and the decrease of urinary excretion. Despite an abundance of in vitro and in vivo data regarding pharmacokinetic interactions between PA/NAPA and cimetidine, however, a mechanistic approach to elucidate these interactions has not been reported yet. The primary objective of this study was to construct a physiological model that describes pharmacokinetic interactions between PA/NAPA and cimetidine, an inhibitor of rat organic cation transporter 2 (rOCT2) and rat multidrug and toxin extrusion proteins (rMATE1), by performing extensive in vivo and in vitro pharmacokinetic studies for PA and NAPA performed in the absence or presence of cimetidine in rats. When a single intravenous injection of PA HCl (10 mg/kg) was administered to rats, co-administration of cimetidine (100 mg/kg) significantly increased systemic exposure and decreased the systemic (CL) and renal (CLR) clearance of PA, and reduced its tissue distribution. Similarly, cimetidine significantly decreased the CLR of NAPA formed by the metabolism of PA and increased the AUC of NAPA. Considering that these drugs could share similar renal secretory pathways (e.g., via rOCT2 and rMATE1), a physiologically-based pharmacokinetic (PBPK) model incorporating semi-mechanistic kidney compartments was devised to predict drug-drug interactions (DDIs). Using our proposed PBPK model, DDIs between PA/NAPA and cimetidine were successfully predicted for the plasma concentrations and urinary excretion profiles of PA and NAPA observed in rats. Moreover, sensitivity analyses of the pharmacokinetics of PA and NAPA showed the inhibitory effects of cimetidine via rMATE1 were probably important for the renal elimination of PA and NAPA in rats. The proposed PBPK model may be useful for understanding the mechanisms of interactions between PA/NAPA and cimetidine in vivo.

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.

Plasma concentration profiles for hepatotoxic pyrrolizidine alkaloid senkirkine in humans extrapolated from rat data sets using a simplified physiologically based pharmacokinetic model

2021 ◽  
Vol 15 ◽  
Author(s):  
Yusuke Kamiya ◽  
Tomonori Miura ◽  
Airi Kato ◽  
Norie Murayama ◽  
Makiko Shimizu ◽  
...  
Keyword(s):  
Plasma Concentration ◽  
Human Plasma ◽  
In Silico ◽  
Pbpk Model ◽  
Pyrrolizidine Alkaloid ◽  
Water Soluble ◽  
Food Plants ◽  
Physiologically Based Pharmacokinetic ◽  
Physiologically Based

Aim: The main aim of the current study was to obtain forward dosimetry assessments of pyrrolizidine alkaloid senkirkine plasma and liver concentrations by setting up a human physiologically based pharmacokinetic (PBPK) model based on the limited information available. Background: The risks associated with plant-derived pyrrolizidine alkaloids as natural toxins have been assessed. Objective: The pyrrolizidine alkaloid senkirkine was investigated because it was analyzed in a European transcriptomics study of natural hepatotoxins and in a study of the alkaloidal constituents of traditional Japanese food plants Petasites japonicus. The in silico human plasma and liver concentrations of senkirkine were modeled using doses reported for acute-term toxicity in humans. Methods: Using a simplified PBPK model established using rat pharmacokinetic data, forward dosimetry was conducted. Since in vitro rat and human intrinsic hepatic clearances were similar; an allometric scaling approach was applied to rat parameters to create a human PBPK model. Results: After oral administration of 1.0 mg/kg in rats in vivo, water-soluble senkirkine was absorbed and cleared from plasma to two orders of magnitude below the maximum concentration in 8 h. Human in silico senkirkine plasma concentration curves were generated after virtual daily oral administrations of 3.0 mg/kg senkirkine (the dose involved in an acute fatal hepatotoxicity case). A high concentration of senkirkine in the culture medium caused in vitro hepatotoxicity as evidenced by lactate dehydrogenase leakage from human hepatocyte-like HepaRG cells. Conclusion: Higher virtual concentrations of senkirkine in human liver and plasma than those in rat plasma were estimated using the current rat and human PBPK models. Current simulations suggest that if P. japonicus (a water-soluble pyrrolizidine alkaloid-producing plant) is ingested daily as food, hepatotoxic senkirkine could be continuously present in human plasma and liver.

scholarly journals 1396. Predictions of Isavuconazonium Sulfate Dosage in Patients Aged 6 Months: <18 Years by Physiologically Based Pharmacokinetic Modeling

2018 ◽  
Vol 5 (suppl_1) ◽  
pp. S429-S430 ◽  
Author(s):  
Amit Desai ◽  
Laura Kovanda ◽  
Christopher Lademacher ◽  
William Hope ◽  
Michael Neely ◽  
...  
Keyword(s):  
Clinical Trials ◽  
Steady State ◽  
Allometric Scaling ◽  
Pbpk Model ◽  
Whole Body ◽  
Target Range ◽  
Independent Contractor ◽  
Physiologically Based Pharmacokinetic ◽  
Physiologically Based ◽  
Research Grant

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 &lt;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 &lt;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 &gt;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.

scholarly journals Prediction of Cyclosporin-Mediated Drug Interaction Using Physiologically Based Pharmacokinetic Model Characterizing Interplay of Drug Transporters and Enzymes

2020 ◽  
Vol 21 (19) ◽  
pp. 7023
Author(s):  
Yiting Yang ◽  
Ping Li ◽  
Zexin Zhang ◽  
Zhongjian Wang ◽  
Li Liu ◽  
...  
Keyword(s):  
Drug Interaction ◽  
Pbpk Model ◽  
Drug Disposition ◽  
Organic Anion ◽  
Whole Body ◽  
Efflux Transporters ◽  
Cytochrome P450 Enzymes ◽  
Control Drug ◽  
Physiologically Based Pharmacokinetic ◽  
Physiologically Based

Uptake transporter organic anion transporting polypeptides (OATPs), efflux transporters (P-gp, BCRP and MRP2) and cytochrome P450 enzymes (CYP450s) are widely expressed in the liver, intestine or kidney. They coordinately work to control drug disposition, termed as “interplay of transporters and enzymes”. Cyclosporine A (CsA) is an inhibitor of OATPs, P-gp, MRP2, BCRP and CYP3As. Drug–drug interaction (DDI) of CsA with victim drugs occurs via disordering interplay of transporters and enzymes. We aimed to establish a whole-body physiologically-based pharmacokinetic (PBPK) model which predicts disposition of CsA and nine victim drugs including atorvastatin, cerivastatin, pravastatin, rosuvastatin, fluvastatin, simvastatin, lovastatin, repaglinide and bosentan, as well as drug–drug interactions (DDIs) of CsA with nine victim drugs to investigate the integrated effect of enzymes and transporters in liver, intestinal and kidney on drug disposition. Predictions were compared with observations. Most of the predictions were within 0.5–2.0 folds of observations. Atorvastatin was represented to investigate individual contributions of transporters and CYP3As to atorvastatin disposition and their integrated effect. The contributions to atorvastatin disposition were hepatic OATPs >> hepatic CYP3A > intestinal CYP3As ≈ efflux transporters (P-gp/BCRP/MRP2). The results got the conclusion that the developed PBPK model characterizing the interplay of enzymes and transporters was successfully applied to predict the pharmacokinetics of 10 OATP substrates and DDIs of CsA with 9 victim drugs.

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