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Establishment of a fexofenadine population pharmacokinetic (PK)–pharmacodynamic (PD) model and exploration of dosing regimens through simulation

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Abstract

Purpose

Fexofenadine is an antihistamine drug used to treat various allergic diseases. Despite long-term clinical application, research and knowledge on setting dosage regimen based on quantitative pharmacometrics prediction are still very lacking. This study aimed to explore the dosing regimen of fexofenadine through establishment of a fexofenadine population pharmacokinetic (PK)–pharmacodynamic (PD) model and model simulation. We also assessed whether ATP-binding cassette-subfamily-B-member-1 (ABCB1) gene polymorphism is associated with interindividual variability in fexofenadine PKs.

Methods

For this study, the results of fexofenadine bioequivalence study on healthy Korean males and previously reported PK and PD results were used. Based on these data, a fexofenadine population PK–PD model was established.

Results

ABCB1 gene polymorphisms were not significantly correlated with interindividual PK diversity of fexofenadine. This result suggests that considering ABCB1 gene polymorphisms would not be significantly beneficial in individualized therapy using fexofenadine. The established model well explained the PK–PD outcomes of fexofenadine at various doses in healthy adults. Model simulation revealed that the maximum PD (Rmax) values at approximately 200–4000 mg doses of fexofenadine did not differ largely (approximately 10%); however, fivefold to eightfold differences were noted between Rmax and the subsequent minimum PD (Rmin) values. Moreover, the degree of decrease in the average fexofenadine PDs in the steady–state according to increase in the dosing interval (6–24 h) for same dose was within 5%, whereas the difference between Rmax and Rmin for prolonging PD response was as large as 7%. This result suggests that effective therapy for allergy could involve increasing oral dosage of fexofenadine and reducing dosing interval to prolong the PD effect.

Conclusion

Our findings can provide a clearer direction for personalized therapy using fexofenadine in clinical setting through qualitative–quantitative predictions.

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Data availability

All data and related materials are accessible in this manuscript and supplementary materials.

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Acknowledgements

This work was supported by a Research promotion program of SCNU.

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Authors and Affiliations

Authors

Contributions

S-HJ: Conceptualization, investigation, methodology, writing—original draft, writing—review and editing, software, data analysis, and visualization; J-HJ: investigation, methodology, writing—review and editing, software, and data analysis; and Y-BL: conceptualization, methodology, writing—review and editing, and supervision.

Corresponding author

Correspondence to Yong-Bok Lee.

Ethics declarations

Conflict of interest

All authors (J.H. Jang, S.H. Jeong, and Y.B. Lee) have no conflicts of interest relevant to this study to disclose.

Human and animal rights

This study protocol was thoroughly reviewed and approved by the Institutional Review Board of the Institute of Bioequivalence and Bridging Study, Chonnam National University, Gwangju, Republic of Korea. The bioequivalence study permit number was as follows: 926; 04.22.2006.

Consent to participate

All subjects provided written informed consent prior to their participation in bioequivalence and pharmacokinetic studies.

Consent for publication

All data were anonymized and participants were informed that the results of this study may be subject to publication and presentation in meetings.

Clinical trial registration

The clinical study protocol used in this study was thoroughly reviewed and approved by the Institutional Review Board of the Institute of Bioequivalence and Bridging Study, Chonnam National University, Gwangju, Republic of Korea. The bioequivalence study permit numbers are as follows: 926; 04.22.2006.

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Jang, JH., Jeong, SH. & Lee, YB. Establishment of a fexofenadine population pharmacokinetic (PK)–pharmacodynamic (PD) model and exploration of dosing regimens through simulation. J. Pharm. Investig. 53, 427–441 (2023). https://doi.org/10.1007/s40005-023-00615-0

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