scholarly journals Application of a PBPK model to elucidate the changes of systemic and liver exposures for rosuvastatin, carotegrast, and bromfenac followed by OATP inhibition in monkeys

Author(s):  
Yaofeng Cheng ◽  
Xiaomin Liang ◽  
Jia Hao ◽  
Congrong Niu ◽  
Yurong Lai
Keyword(s):  
Pharmaceutics ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 813
Author(s):  
Yoo-Seong Jeong ◽  
Min-Soo Kim ◽  
Nora Lee ◽  
Areum Lee ◽  
Yoon-Jee Chae ◽  
...  

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.


Author(s):  
Venkatesh Pilla Reddy ◽  
Adrian J. Fretland ◽  
Diansong Zhou ◽  
Shringi Sharma ◽  
Buyun Chen ◽  
...  

Abstract Purpose Limited information is available regarding the drug–drug interaction (DDI) potential of molecular targeted agents and rituximab plus cyclophosphamide, doxorubicin (hydroxydaunorubicin), vincristine (Oncovin), and prednisone (R-CHOP) therapy. The addition of the Bruton tyrosine kinase (BTK) inhibitor ibrutinib to R-CHOP therapy results in increased toxicity versus R-CHOP alone, including higher incidence of peripheral neuropathy. Vincristine is a substrate of P-glycoprotein (P-gp, ABCB1); drugs that inhibit P-gp could potentially cause increased toxicity when co-administered with vincristine through DDI. While the combination of the BTK inhibitor acalabrutinib and R-CHOP is being explored clinically, the DDI potential between these therapies is unknown. Methods A human mechanistic physiology-based pharmacokinetic (PBPK) model of vincristine following intravenous dosing was developed to predict potential DDI interactions with combination therapy. In vitro absorption, distribution, metabolism, and excretion and in vivo clinical PK parameters informed PBPK model development, which was verified by comparing simulated vincristine concentrations with observed clinical data. Results While simulations suggested no DDI between vincristine and ibrutinib or acalabrutinib in plasma, simulated vincristine exposure in muscle tissue was increased in the presence of ibrutinib but not acalabrutinib. Extrapolation of the vincristine mechanistic PBPK model to other P-gp substrates further suggested DDI risk when ibrutinib (area under the concentration–time curve [AUC] ratio: 1.8), but not acalabrutinib (AUC ratio: 0.92), was given orally with venetoclax or digoxin. Conclusion Overall, these data suggest low DDI risk between acalabrutinib and P-gp substrates with negligible increase in the potential risk of vincristine-induced peripheral neuropathy when acalabrutinib is added to R-CHOP therapy.


Author(s):  
Kun Wang ◽  
Xueting Yao ◽  
Miao Zhang ◽  
Dongyang Liu ◽  
Yuying Gao ◽  
...  

2020 ◽  
Vol 7 (Supplement_1) ◽  
pp. S669-S669
Author(s):  
Dung N Nguyen ◽  
Xiusheng Miao ◽  
Mindy Magee ◽  
Guoying Tai ◽  
Peter D Gorycki ◽  
...  

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)


2020 ◽  
Vol 93 ◽  
pp. 219-229 ◽  
Author(s):  
Ségolène Siméon ◽  
Katharina Brotzmann ◽  
Ciaran Fisher ◽  
Iain Gardner ◽  
Steve Silvester ◽  
...  

2015 ◽  
Vol 19 (2) ◽  
pp. 99 ◽  
Author(s):  
LiQin Zhu ◽  
JianWei Yang ◽  
Yuan Zhang ◽  
YongMing Wang ◽  
JianLei Zhang ◽  
...  

2016 ◽  
Vol 60 (8) ◽  
pp. 4860-4868
Author(s):  
Todd J. Zurlinden ◽  
Garrett J. Eppers ◽  
Brad Reisfeld

ABSTRACTRifapentine (RPT) is a rifamycin antimycobacterial and, as part of a combination therapy, is indicated for the treatment of pulmonary tuberculosis (TB) caused byMycobacterium tuberculosis. Although the results from a number of studies indicate that rifapentine has the potential to shorten treatment duration and enhance completion rates compared to other rifamycin agents utilized in antituberculosis drug regimens (i.e., regimens 1 to 4), its optimal dose and exposure in humans are unknown. To help inform such an optimization, a physiologically based pharmacokinetic (PBPK) model was developed to predict time course, tissue-specific concentrations of RPT and its active metabolite, 25-desacetyl rifapentine (dRPT), in humans after specified administration schedules for RPT. Starting with the development and verification of a PBPK model for rats, the model was extrapolated and then tested using human pharmacokinetic data. Testing and verification of the models included comparisons of predictions to experimental data in several rat tissues and time course RPT and dRPT plasma concentrations in humans from several single- and repeated-dosing studies. Finally, the model was used to predict RPT concentrations in the lung during the intensive and continuation phases of a current recommended TB treatment regimen. Based on these results, it is anticipated that the PBPK model developed in this study will be useful in evaluating dosing regimens for RPT and for characterizing tissue-level doses that could be predictors of problems related to efficacy or safety.


2018 ◽  
Vol 93 (2) ◽  
pp. 311-330 ◽  
Author(s):  
Sook-Jin Kim ◽  
Eun-Jeong Choi ◽  
Go-Wun Choi ◽  
Yong-Bok Lee ◽  
Hea-Young Cho

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