scholarly journals Application of Physiologically Based Pharmacokinetic Modeling to Evaluate the Drug–Drug and Drug–Disease Interactions of Apatinib

2021 ◽  
Vol 12 ◽  
Author(s):  
Hongrui Liu ◽  
Yiqun Yu ◽  
Nan Guo ◽  
Xiaojuan Wang ◽  
Bing Han ◽  
...  
Keyword(s):  
Single Dose ◽  
Healthy Volunteers ◽  
Kinase Inhibitors ◽  
Growth Factor Receptor ◽  
Moderate Increase ◽  
Pbpk Models ◽  
Physiologically Based Pharmacokinetic ◽  
Vascular Epidermal Growth Factor ◽  
Physiologically Based ◽  
Cyp3a4 Inhibitors

Aim: Apatinib is an orally administered vascular epidermal growth factor receptor (VEGFR)-tyrosine kinase inhibitors approved for the treatment of advanced gastric adenocarcinoma or gastric esophageal junction adenocarcinoma. Apatinib is predominantly metabolized by CYP3A4/5, followed by CYP2D6. The present study aimed to evaluate the potential drug–drug interaction (DDI) and drug–disease interaction (DDZI) risks of apatinib in Chinese volunteers.Methods: Modeling and simulation were conducted using Simcyp Simulator. The input parameters required for modeling were obtained from literature research or experiments. Then, the developed physiologically based pharmacokinetic (PBPK) models were applied to evaluate single-dose DDI potential in Chinese healthy volunteers with weak and moderate CYP3A inhibitors, strong CYP2D6 inhibitors, as well as CYP3A4 inducers. The DDZI potential was also predicted in patients with hepatic or renal impairment.Results: The developed PBPK models accurately assessed apatinib pharmacokinetics following single-dose administration in Chinese healthy volunteers and cancer patients. The DDI simulation showed 2–4-fold changes in apatinib exposures by moderate CYP3A4 inhibitors and CYP3A4 inducers. A moderate increase of apatinib exposure (1.25–2-fold) was found with strong CYP2D6 inhibitor. In the DDZI simulation with hepatic impairment, the AUC of apatinib was significantly increased by 2.25-fold and 3.04-fold for Child–Pugh B and Child–Pugh C, respectively, with slightly decreased Cmax by 1.54 and 1.67-fold, respectively.Conclusion: The PBPK models developed in the present study would be highly beneficial to quantitatively predict the pharmacokinetic changes of apatinib under different circumstances, which might be difficult to evaluate clinically, so as to avoid some risks in advance.

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 Models of Probenecid and Furosemide to Predict Transporter Mediated Drug-Drug Interactions

2020 ◽  
Vol 37 (12) ◽  
Author(s):  
Hannah Britz ◽  
Nina Hanke ◽  
Mitchell E. Taub ◽  
Ting Wang ◽  
Bhagwat Prasad ◽  
...  
Keyword(s):  
Plasma Concentration ◽  
Organic Anion ◽  
Plasma Concentrations ◽  
Whole Body ◽  
Time Profiles ◽  
Pbpk Models ◽  
Physiologically Based Pharmacokinetic ◽  
Concentration Time ◽  
Anion Transporter ◽  
Physiologically Based

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.

scholarly journals Personalise Dose Regimen of Vitamin D3 Using Physiologically-Based Pharmacokinetic Modelling

2020 ◽  
Author(s):  
Zhonghui Huang ◽  
Tao You
Keyword(s):  
Vitamin D ◽  
Dose Regimen ◽  
Population Heterogeneity ◽  
Plasma Vitamin ◽  
Simple Explanation ◽  
Pbpk Models ◽  
Physiologically Based Pharmacokinetic ◽  
Physiologically Based ◽  
Non Linear ◽  
Baseline Levels

AbstractBackground and AimVitamin D3 (i.e. cholecalciferol) produces an active metabolite 25-hydroxyvitamin D3 (i.e. 25(OH)D3) to promote intestinal calcium absorption. Given high population heterogeneity in 25(OH)D3 plasma concentration profiles, vitamin D3 dose regimen needs to be personalised. The objective of this study is to establish a model that accurately predicts 25(OH)D3 pharmacokinetics (PK) on an individual level to enable selection of an appropriate dose regimen for anyone.MethodsPlasma or serum concentrations of Vitamin D3 and 25(OH)D3 from different trials were compiled together. We then developed a series of Physiologically-Based Pharmacokinetic (PBPK) models for vitamin D3 and 25(OH)D3 in a stepwise manner to select the best model to optimally recapitulate the 10μg and 100μg daily dose data. Each arm of the clinical trials was simulated individually. Model predictions were qualified with PK data at other doses.ResultsFrom data exploration, we observed an interesting phenomenon: the increase in plasma 25(OH)D3 after repeat dosing was negatively correlated with 25(OH)D3 baseline levels. Our final model assumes a first-order vitamin D3 absorption, linear vitamin D3 elimination and a non-linear 25(OH)D3 elimination which is described with an Emax function. This model offers a simple explanation to the apparent paradox: the negative correlation might arise from the non-linear 25(OH)D3 elimination process. The model was also able to accurately predict plasma 25(OH)D3 after repeat dosing at daily doses other than 10μg and 100μg, which was reassuring.ConclusionsWe developed a PBPK model to recapitulate PK of plasma vitamin D3 and 25(OH)D3. A personalised vitamin D3 supplementation protocol requires measurement of 25(OH)D3 baseline levels. This should be tested in the clinics for each individual.

scholarly journals Development and Evaluation of Physiologically Based Pharmacokinetic Drug–Disease Models for Predicting Rifampicin Exposure in Tuberculosis and Cirrhosis Populations

Pharmaceutics ◽  
2019 ◽  
Vol 11 (11) ◽  
pp. 578
Author(s):  
Muhammad F. Rasool ◽  
Sundus Khalid ◽  
Abdul Majeed ◽  
Hamid Saeed ◽  
Imran Imran ◽  
...  
Keyword(s):  
Model Development ◽  
Drug Dose ◽  
Disease Models ◽  
Healthy Population ◽  
Albumin Concentration ◽  
Pbpk Models ◽  
Physiologically Based Pharmacokinetic ◽  
Physiologically Based ◽  
Novel Drug ◽  
Pharmacokinetic Drug

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.

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