AUTHOR=Zhang Hong , Li Qingmei , Zhu Xiaoxue , Wu Min , Li Cuiyun , Li Xiaojiao , Liu Chengjiao , Shen Zhenwei , Ding Yanhua , Hua Shucheng
TITLE=Association of Variability and Pharmacogenomics With Bioequivalence of Gefitinib in Healthy Male Subjects
JOURNAL=Frontiers in Pharmacology
VOLUME=9
YEAR=2018
URL=https://www.frontiersin.org/journals/pharmacology/articles/10.3389/fphar.2018.00849
DOI=10.3389/fphar.2018.00849
ISSN=1663-9812
ABSTRACT=Objective: The aim of the study was to explore the association of pharmacokinetic variability and pharmacogenomics with the bioequivalence of orally administered gefitinib (Iressa®, AstraZeneca) provided by three sponsors in healthy subjects.
Methods: The study designs were randomized, open-label, and two-period crossover studies in both fasting and fed healthy subjects. In one fasting study, the sample size was enlarged from 30 to 60 for the failing study. Each study subject received a 250-mg gefitinib tablet with a 21-day washout. The plasma concentrations were measured using LC-MS/MS, and pharmacokinetic parameters were determined by noncompartmental methods. Genetic analyses of CYP3A4, CYP3A5, and CYP2D6 alleles were carried out by the polymerase chain reaction (PCR).
Results: Two hundred and sixty healthy male subjects were enrolled. The median maximum plasma concentration (Tmax) was 4–5 h, and the mean elimination half-life (t1/2) was 18–26 h. The maximum plasma concentration (Cmax) and area under the curve (AUC) increased but Tmax and t1/2 were unaffected by the intake of high-fat food. Three fed and two fasting studies achieved a plausible bioequivalence. The intake of high-fat food decreased the intra-subject variability significantly. In addition, CYP2D6 was associated with gefitinib exposure and may contribute to the high inter-subject variability, but it did not influence the bioequivalence result.
Conclusions: Gefitinib is well tolerated, and the bioequivalence is easier to achieve under fed conditions compared to fasting conditions. The 90% confidence interval (CI) of geometric mean ratio (GMR) can be narrowed when the sample size is enlarged without changing the formulation-related technology.