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A selective and robust UPLC-MS/MS method for the simultaneous quantitative determination of anlotinib, ceritinib and ibrutinib in rat plasma and its application to a pharmacokinetic study

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Abstract

A selective and robust UPLC-MS/MS method has been firstly developed for simultaneous determination of three anti-tumor tyrosine kinase inhibitors (anlotinib, ANL; ceritinib, CER; ibrutinib, IBR) in rat plasma using cost-effective protein precipitation extraction. LC separation was achieved on Waters XBrige C18 column (50 mm × 2.1 mm, 3.5 μm) under gradient conditions in a run time of 5 min. ESI+ was involved through mass spectrometry. Multiple reaction monitoring transitions were at m/z 408.2 → 339.2 for ANL, 558.2 → 433.2 for CER, 441.0 → 138.0 for IBR, 285.0 → 193.1 for diazepam (internal standard), respectively. The optimized method was validated based on US FDA guideline, EMEA guideline as well as Pharmacopoeia of the People’s Republic of China. The assay was linear in the range of 0.1–20 ng mL−1 for ANL, 2–1000 ng mL−1 for CER, 1–500 ng mL−1 for IBR. Intra- and inter-day accuracy and precision for all analytes were ≦13.84% and ≦12.56%, respectively. ANL, CER and IBR were sufficiently stable under most investigated conditions. The optimized method was successfully applied for a pharmacokinetic study after single oral gavage administration of mixture (ANL, CER and IBR) at dose of 6 mg kg−1, 25 mg kg−1 and 10 mg kg−1.

Graphical abstract: A selective and robust UPLC-MS/MS method for the simultaneous quantitative determination of anlotinib, ceritinib and ibrutinib in rat plasma and its application to a pharmacokinetic study

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Publication details

The article was received on 11 May 2019, accepted on 17 Jul 2019 and first published on 17 Jul 2019


Article type: Paper
DOI: 10.1039/C9AN00861F
Analyst, 2019, Advance Article

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    A selective and robust UPLC-MS/MS method for the simultaneous quantitative determination of anlotinib, ceritinib and ibrutinib in rat plasma and its application to a pharmacokinetic study

    P. Du, Y. Guan, Z. An, P. Li and L. Liu, Analyst, 2019, Advance Article , DOI: 10.1039/C9AN00861F

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