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Physiologically Based Pharmacokinetic Modeling for Prediction of 5-FU Pharmacokinetics in Cancer Patients with Hepatic Impairment After 5-FU and Capecitabine Administration

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Abstract

Purpose

5-fluorouracil (5-FU) and its prodrug capecitabine are commonly prescribed anti-tumor medications. We aimed to establish physiologically based pharmacokinetic (PBPK) models of capecitabine-metabolites and 5-FU-metabolites to describe their pharmacokinetics in tumor and plasma of cancer patients with liver impairment.

Methods

Models including the cancer compartment were developed in PK-Sim® and MoBi® and evaluated by R programming language with 25 oral capecitabine and 18 intravenous 5-FU studies for cancer patients with and without liver impairment.

Results

The PBPK models were constructed successfully as most simulated Cmax and AUClast were within two-fold error of observed values. The simulated alterations of tumor 5-FU Cmax and AUClast in cancer patients with severe liver injury compared with normal liver function were 1.956 and 3.676 after oral administration of capecitabine, but no significant alteration was observed after intravenous injection of 5-FU. Besides, 5-FU concentration in tumor tissue increases with higher tumor blood flow but not tumor size. Sensitivity analysis revealed that dihydropyrimidine dehydrogenase (DPD) and other metabolic enzymes′ activity, capecitabine intestinal permeability and plasma protein scale factor played a vital role in tumor and plasma 5-FU pharmacokinetics.

Conclusions

PBPK model prediction suggests no dosage adaption of capecitabine or 5-FU is required for cancer patients with hepatic impairment but it would be reduced when the toxic reaction is observed. Furthermore, tumor blood flow rate rather than tumor size is critical for 5-FU concentration in tumor. In summary, these models could predict pharmacokinetics of 5-FU in tumor in cancer patients with varying characteristics in different scenarios.

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Data Availability

Data available on request from the authors, Yu Wang (Email:21919028@zju.edu.cn) or Su Zeng (Email:zengsu@zju.edu.cn).

Abbreviations

5′-DFCR:

5′-deoxy-5-fluorocytidine

5′-DFUR:

5′-deoxy-5-fluorouridine

5-FU:

5-fluorouracil

FUH2 :

Fluorodihydrouracil

FUPA:

α-fluoro-β-ureidopropionic acid

FBAL:

α-fluoro-β-alanine

CES:

Carboxylesterase

CDA:

Cytidine deaminase

TP:

Thymidine phosphorylase

DPD:

Dihydropyrimidine dehydrogenase

DHP:

Dihydropyrimidase

BUP:

β-ureidopropionase

OPRT:

Orotate phosphoribosyltransferase

CP-B:

Child-Pugh B

CP-C:

Child-Pugh C

GOF:

Goodness-of-fit

GMFE:

Geometric mean fold-error

AUClast :

Area under the plasma concentration–time curve from time zero to the time of the last quantifiable concentration

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Acknowledgements

This work was financially supported by the National Natural Science Foundation of China [grant numbers 81973394].

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Authors and Affiliations

  1. Institute of Drug Metabolism and Pharmaceutical Analysis, Zhejiang Province Key Laboratory of Anti-Cancer Drug Research, Cancer Center of Zhejiang University, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310006, China

    Yu Wang, Haihong Hu, Lushan Yu & Su Zeng

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  1. Yu Wang
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  2. Haihong Hu
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  3. Lushan Yu
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  4. Su Zeng
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Contributions

Yu Wang collected data, conducted analysis, develop the model and wrote the manuscript; Haihong Hu collected data and conducted analysis; Su Zeng and Lushan Yu critically revised the manuscript; Su Zeng also contributed to conception design.

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Correspondence to Su Zeng.

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Wang, Y., Hu, H., Yu, L. et al. Physiologically Based Pharmacokinetic Modeling for Prediction of 5-FU Pharmacokinetics in Cancer Patients with Hepatic Impairment After 5-FU and Capecitabine Administration. Pharm Res 40, 2177–2194 (2023). https://doi.org/10.1007/s11095-023-03585-y

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