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 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 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.

Physiologically Based Pharmacokinetic Modeling of Salivary Concentrations for Noninvasive Biomonitoring of 2,4-Dichlorophenoxyacetic Acid (2,4-D)

2019 ◽  
Vol 172 (2) ◽  
pp. 330-343
Author(s):  
Alice A Han ◽  
Charles Timchalk ◽  
Zana A Carver ◽  
Thomas J Weber ◽  
Kimberly J Tyrrell ◽  
...  
Keyword(s):  
Pbpk Model ◽  
Pbpk Modeling ◽  
Dichlorophenoxyacetic Acid ◽  
Diffusion Limited ◽  
Physiologically Based Pharmacokinetic ◽  
Physiologically Based ◽  
Dynamic Time ◽  
2,4 Dichlorophenoxyacetic Acid

Abstract Saliva has become a favorable sample matrix for biomonitoring due to its noninvasive attributes and overall flexibility in collection. To ensure measured salivary concentrations reflect the exposure, a solid understanding of the salivary transport mechanism and relationships between salivary concentrations and other monitored matrices (ie, blood, urine) is needed. Salivary transport of a commonly applied herbicide, 2,4-dichlorophenoxyacetic acid (2,4-D), was observed in vitro and in vivo and a physiologically based pharmacokinetic (PBPK) model was developed to translate observations from the cell culture model to those in animal models and further evaluate 2,4-D kinetics in humans. Although apparent differences in experimental in vitro and in vivo saliva:plasma ratios (0.034 and 0.0079) were observed, simulations with the PBPK model demonstrated dynamic time and dose-dependent saliva:plasma ratios, elucidating key mechanisms affecting salivary transport. The model suggested that 2,4-D exhibited diffusion-limited transport to saliva and was additionally impacted by protein binding saturation and permeability across the salivary gland. Consideration of sampling times post-exposure and potential saturation of transport mechanisms are then critical aspects for interpreting salivary 2,4-D biomonitoring observations. This work utilized PBPK modeling in in vitro to in vivo translation to explore benefits and limitations of salivary analysis for occupational biomonitoring.

Drug-drug interaction (DDI) assessments of ruxolitinib, a dual substrate of CYP3A4 and CYP2C9, using a verified physiologically based pharmacokinetic (PBPK) model to support regulatory submissions

2019 ◽  
Vol 34 (2) ◽  
Author(s):  
Kenichi Umehara ◽  
Felix Huth ◽  
Yi Jin ◽  
Hilmar Schiller ◽  
Vassilios Aslanis ◽  
...  
Keyword(s):  
Dose Reduction ◽  
Dose Adjustment ◽  
Pbpk Model ◽  
Pbpk Modeling ◽  
Cyp Enzymes ◽  
Physiologically Based Pharmacokinetic ◽  
Physiologically Based ◽  
Cyp3a4 Inhibitors ◽  
Simulation Results

Abstract Ruxolitinib is mainly metabolized by cytochrome P450 (CYP) enzymes CYP3A4 and CYP2C9 followed by minor contributions of other hepatic CYP enzymes in vitro. A physiologically based pharmacokinetic (PBPK) model was established to evaluate the changes in the ruxolitinib systemic exposures with co-administration of CYP3A4 and CYP2C9 perpetrators. The fractions metabolized in the liver via oxidation by CYP enzymes (fm,CYP3A4 = 0.75, fm,CYP2C9 = 0.19, and fm,CYPothers = 0.06) for an initial ruxolitinib model based on in vitro data were optimized (0.43, 0.56, and 0.01, respectively) using the observed exposure changes of ruxolitinib (10 mg) with co-administered ketoconazole (200 mg). The reduced amount of fm,CYP3A4 was distributed to fm,CYP2C9. For the initial ruxolitinib model with co-administration of ketoconazole, the area under the curve (AUC) increase of 2.60-fold was over-estimated compared with the respective observation (1.91-fold). With the optimized fm values, the predicted AUC ratio was 1.82. The estimated AUC ratios of ruxolitinib by co-administration of the moderate CYP3A4 inhibitor erythromycin (500 mg) and the strong CYP3A4 inducer rifampicin (600 mg) were within a 20% error compared with the clinically observed values. The PBPK modeling results may provide information on the labeling, i.e. supporting a dose reduction by half for co-administration of strong CYP3A4 inhibitors. Furthermore, an AUC increase of ruxolitinib in the absence or presence of the dual CYP3A4 and CYP2C9 inhibitor fluconazole (100–400 mg) was prospectively estimated to be 1.94- to 4.31-fold. Fluconazole simulation results were used as a basis for ruxolitinib dose adjustment when co-administering perpetrator drugs. A ruxolitinib PBPK model with optimized fm,CYP3A4 and fm,CYP2C9 was established to evaluate victim DDI risks. The previous minimal PBPK model was supported by the FDA for the dose reduction strategy, halving the dose with the concomitant use of strong CYP3A4 inhibitors and dual inhibitors on CYP2C9 and CYP3A4, such as fluconazole at ≤200 mg. Fluconazole simulation results were used as supportive evidence in discussions with the FDA and EMA about ruxolitinib dose adjustment when co-administering perpetrator drugs. Thus, this study demonstrated that PBPK modeling can support characterizing DDI liabilities to inform the drug label and might help reduce the number of clinical DDI studies by simulations of untested scenarios, when a robust PBPK model is established.

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.

scholarly journals Development and Application of a Life-Stage Physiologically Based Pharmacokinetic (PBPK) Model to the Assessment of Internal Dose of Pyrethroids in Humans

2019 ◽  
Vol 173 (1) ◽  
pp. 86-99 ◽  
Author(s):  
Pankajini Mallick ◽  
Marjory Moreau ◽  
Gina Song ◽  
Alina Y Efremenko ◽  
Salil N Pendse ◽  
...  
Keyword(s):  
Blood Flow ◽  
Pbpk Model ◽  
Life Stage ◽  
Internal Exposure ◽  
Target Tissue ◽  
Physiologically Based Pharmacokinetic ◽  
Age Related ◽  
Physiologically Based

Abstract To address concerns around age-related sensitivity to pyrethroids, a life-stage physiologically based pharmacokinetic (PBPK) model, supported by in vitro to in vivo extrapolation (IVIVE) was developed. The model was used to predict age-dependent changes in target tissue exposure of 8 pyrethroids; deltamethrin (DLM), cis-permethrin (CPM), trans-permethrin, esfenvalerate, cyphenothrin, cyhalothrin, cyfluthrin, and bifenthrin. A single model structure was used based on previous work in the rat. Intrinsic clearance (CLint) of each individual cytochrome P450 or carboxylesterase (CES) enzyme that are active for a given pyrethroid were measured in vitro, then biologically scaled to obtain in vivo age-specific total hepatic CLint. These IVIVE results indicate that, except for bifenthrin, CES enzymes are largely responsible for human hepatic metabolism (>50% contribution). Given the high efficiency and rapid maturation of CESs, clearance of the pyrethroids is very efficient across ages, leading to a blood flow-limited metabolism. Together with age-specific physiological parameters, in particular liver blood flow, the efficient metabolic clearance of pyrethroids across ages results in comparable to or even lower internal exposure in the target tissue (brain) in children than that in adults in response to the same level of exposure to a given pyrethroid (Cmax ratio in brain between 1- and 25-year old = 0.69, 0.93, and 0.94 for DLM, bifenthrin, and CPM, respectively). Our study demonstrated that a life-stage PBPK modeling approach, coupled with IVIVE, provides a robust framework for evaluating age-related differences in pharmacokinetics and internal target tissue exposure in humans for the pyrethroid class of chemicals.

scholarly journals Physiologically Based Pharmacokinetic/Pharmacodynamic Modeling to Predict the Impact of CYP2C9 Genetic Polymorphisms, Co-Medication and Formulation on the Pharmacokinetics and Pharmacodynamics of Flurbiprofen

Pharmaceutics ◽  
2020 ◽  
Vol 12 (11) ◽  
pp. 1049
Author(s):  
Ioannis Loisios-Konstantinidis ◽  
Rodrigo Cristofoletti ◽  
Masoud Jamei ◽  
David Turner ◽  
Jennifer Dressman
Keyword(s):  
Genetic Polymorphisms ◽  
Pbpk Model ◽  
Dose Range ◽  
Absolute Bioavailability ◽  
Pharmacokinetics And Pharmacodynamics ◽  
Physiologically Based Pharmacokinetic ◽  
Physiologically Based ◽  
The Impact

Physiologically based pharmacokinetic/pharmacodynamic (PBPK/PD) models can serve as a powerful framework for predicting the influence as well as the interaction of formulation, genetic polymorphism and co-medication on the pharmacokinetics and pharmacodynamics of drug substances. In this study, flurbiprofen, a potent non-steroid anti-inflammatory drug, was chosen as a model drug. Flurbiprofen has absolute bioavailability of ~95% and linear pharmacokinetics in the dose range of 50–300 mg. Its absorption is considered variable and complex, often associated with double peak phenomena, and its pharmacokinetics are characterized by high inter-subject variability, mainly due to its metabolism by the polymorphic CYP2C9 (fmCYP2C9 ≥ 0.71). In this study, by leveraging in vitro, in silico and in vivo data, an integrated PBPK/PD model with mechanistic absorption was developed and evaluated against clinical data from PK, PD, drug-drug and gene-drug interaction studies. The PBPK model successfully predicted (within 2-fold) 36 out of 38 observed concentration-time profiles of flurbiprofen as well as the CYP2C9 genetic effects after administration of different intravenous and oral dosage forms over a dose range of 40–300 mg in both Caucasian and Chinese healthy volunteers. All model predictions for Cmax, AUCinf and CL/F were within two-fold of their respective mean or geometric mean values, while 90% of the predictions of Cmax, 81% of the predictions of AUCinf and 74% of the predictions of Cl/F were within 1.25 fold. In addition, the drug-drug and drug-gene interactions were predicted within 1.5-fold of the observed interaction ratios (AUC, Cmax ratios). The validated PBPK model was further expanded by linking it to an inhibitory Emax model describing the analgesic efficacy of flurbiprofen and applying it to explore the effect of formulation and genetic polymorphisms on the onset and duration of pain relief. This comprehensive PBPK/PD analysis, along with a detailed translational biopharmaceutic framework including appropriately designed biorelevant in vitro experiments and in vitro-in vivo extrapolation, provided mechanistic insight on the impact of formulation and genetic variations, two major determinants of the population variability, on the PK/PD of flurbiprofen. Clinically relevant specifications and potential dose adjustments were also proposed. Overall, the present work highlights the value of a translational PBPK/PD approach, tailored to target populations and genotypes, as an approach towards achieving personalized medicine.

scholarly journals Simulating Intestinal Transporter and Enzyme Activity in a Physiologically Based Pharmacokinetic Model for Tenofovir Disoproxil Fumarate

2017 ◽  
Vol 61 (7) ◽  
Author(s):  
Darren M. Moss ◽  
Paul Domanico ◽  
Melynda Watkins ◽  
Seonghee Park ◽  
Ryan Randolph ◽  
...  
Keyword(s):  
Enzyme Activity ◽  
Tenofovir Disoproxil Fumarate ◽  
Drug Exposure ◽  
Pbpk Model ◽  
Intestinal Transport ◽  
Pbpk Modeling ◽  
Time Curve ◽  
Physiologically Based Pharmacokinetic ◽  
Physiologically Based

ABSTRACT Tenofovir disoproxil fumarate (TDF), a prodrug of tenofovir, has oral bioavailability (25%) limited by intestinal transport (P-glycoprotein), and intestinal degradation (carboxylesterase). However, the influence of luminal pancreatic enzymes is not fully understood. Physiologically based pharmacokinetic (PBPK) modeling has utility for estimating drug exposure from in vitro data. This study aimed to develop a PBPK model that included luminal enzyme activity to inform dose reduction strategies. TDF and tenofovir stability in porcine pancrelipase concentrations was assessed (0, 0.48, 4.8, 48, and 480 U/ml of lipase; 1 mM TDF; 37°C; 0 to 30 min). Samples were analyzed using mass spectrometry. TDF stability and permeation data allowed calculation of absorption rates within a human PBPK model to predict plasma exposure following 6 days of once-daily dosing with 300 mg of TDF. Regional absorption of drug was simulated across gut segments. TDF was degraded by pancrelipase (half-lives of 0.07 and 0.62 h using 480 and 48 U/ml, respectively). Previously reported maximum concentration (C max; 335 ng/ml), time to C max (T max; 2.4 h), area under the concentration-time curve from 0 to 24 h (AUC0–24; 3,045 ng · h/ml), and concentration at 24 h (C 24; 48.3 ng/ml) were all within a 0.5-fold difference from the simulated C max (238 ng/ml), T max (3 h), AUC0–24 (3,036 ng · h/ml), and C 24 (42.7 ng/ml). Simulated TDF absorption was higher in duodenum and jejunum than in ileum (p<0.05). These data support that TDF absorption is limited by the action of intestinal lipases. Our results suggest that bioavailability may be improved by protection of drug from intestinal transporters and enzymes, for example, by coadministration of enzyme-inhibiting agents or nanoformulation strategies.

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