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DOI 10.3389/fphar.2022.1065130

Медицинская библиотека · Frontiers in pharmacology · 2022

Potential drug-drug interaction of olverembatinib (HQP1351) using physiologically based pharmacokinetic models.

Yu Zhiheng, Lei Zihan, Yao Xueting, Wang Hengbang, Zhang Miao, Hou Zhe, Li Yafen, Zhao Yangyu, Li Haiyan, Liu Dongyang, Zhai Yifan

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Аннотация

Olverembatinib (HQP1351) is a third-generation BCR-ABL tyrosine kinase inhibitor for the treatment of chronic myeloid leukemia (CML) (including T315I-mutant disease), exhibits drug-drug interaction (DDI) potential through cytochrome P450 (CYP) enzymes CYP3A4, CYP2C9, CYP2C19, CYP1A2, and CYP2B6. A physiologically-based pharmacokinetic (PBPK) model was constructed based on physicochemical and in vitro parameters, as well as clinical data to predict 1) potential DDIs between olverembatinib and CYP3A4 and CYP2C9 inhibitors or inducers 2), effects of olverembatinib on the exposure of CYP1A2, CYP2B6, CYP2C9, CYP2C19, and CYP3A4 substrates, and 3) pharmacokinetics in patients with liver function injury. The PBPK model successfully described observed plasma concentrations of olverembatinib from healthy subjects and patients with CML after a single administration, and predicted olverembatinib exposure increases when co-administered with itraconazole (strong CYP3A4 inhibitor) and decreases with rifampicin (strong CYP3A4 inducer), which were validated by observed data. The predicted results suggest that 1) strong, moderate, and mild CYP3A4 inhibitors (which have some overlap with CYP2C9 inhibitors) may increase olverembatinib exposure by approximately 2.39-, 1.80- to 2.39-, and 1.08-fold, respectively; strong, and moderate CYP3A4 inducers may decrease olverembatinib exposure by approximately 0.29-, and 0.35- to 0.56-fold, respectively 2); olverembatinib, as a "perpetrator," would have no or limited impact on CYP1A2, CYP2B6, CYP2C9, CYP2C19, and CYP3A4 enzyme activity 3); systemic exposure of olverembatinib in liver function injury with Child-Pugh A, B, C may increase by 1.22-, 1.79-, and 2.13-fold, respectively. These simulations inform DDI risk for olverembatinib as either a "victim" or "perpetrator".

Для цитирования: Yu Zhiheng, Lei Zihan, Yao Xueting, Wang Hengbang, Zhang Miao, Hou Zhe, Li Yafen, Zhao Yangyu, Li Haiyan, Liu Dongyang, Zhai Yifan. Potential drug-drug interaction of olverembatinib (HQP1351) using physiologically based pharmacokinetic models.. Frontiers in pharmacology. 2022. DOI: 10.3389/fphar.2022.1065130.
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