Retrospective Evaluation of Drug-Drug Interactions With Erlotinib and Gefitinib Use in the Military Health System.

Background: Erlotinib and gefitinib are epidermal growth factor receptor-tyrosine kinase inhibitors approved for non-small cell lung cancer treatment by the US Food and Drug Administration. Drug-drug interactions (DDIs) with these agents are vague and poorly understood. Because DDIs can have an effect on clinical outcomes, we aimed to identify drugs that interact with erlotinib or gefitinib and describe their clinical manifestations. Methods: A retrospective analysis was performed on the health records of patients in the US Department of Defense Cancer Registry (retrieved September 2021), Comprehensive Ambulatory/Professional Encounter Records, and Pharmacy Data Transaction Service database (both retrieved May 2022). Patients' medical history, diagnoses, and demographics were extracted and analyzed for differences in adverse effects when these agents were used alone vs concomitantly with other prescription drugs. Patients' diagnoses and prescription drug use were extracted to compare completed vs discontinued treatment groups, identify medications commonly co-administered with erlotinib or gefitinib, and evaluate DDIs with antidepressants. Results: Of 387 patients using erlotinib, 264 completed treatments; 28 of 33 patients using gefitinib completed treatment. The P value for erlotinib discontinuation when used alone vs concomitantly was < .001, and the P value for gefitinib discontinuation was .06. Patients who took erlotinib or gefitinib concomitantly with a greater number of prescription drugs had a higher rate of treatment discontinuation than those who received fewer medications. Patients in the completed group received 1 to 75 prescription drugs, and those in the completed group were prescribed 3 to 103. Those who discontinued treatment had more diagnosed medical issues than those who completed treatment. Conclusions: This review cannot conclude that concomitant use with prescription drug(s) resulted in erlotinib or gefitinib discontinuation. There were no significant DDIs determined between erlotinib or gefitinib and antidepressants.

Pre-clinical drug-drug interactions (DDIs) of gefitinib with/without losartan and selective serotonin reuptake inhibitors (SSRIs): citalopram, fluoxetine, fluvoxamine, paroxetine, sertraline, and venlafaxine.

Objective: To evaluate drug-drug interactions (DDIs) between gefitinib with/without losartan and selective serotonin reuptake inhibitors (SSRIs). Methods: In vitro supersomes were used to identify CYP isoenzymes (CYP1A2, 2C9, 2C19, 2D6, and 3A4) involved in drug metabolism, and in vitro pooled cryopreserved primary human hepatocytes were employed to investigate DDIs. Results: The isoenzymes that showed drug degradation are listed in parentheses beside the respective drug: gefitinib (CYP2D6, 3A4, 1A2, 2C9, and 2C19), losartan (CYP2C9 and 3A4), citalopram (CYP2D6, 2C19, 3A4, and 2C9), fluoxetine (CYP2D6, 2C9, and 2C19), fluvoxamine (CYP2D6, 2C9, and 2C19), paroxetine (CYP2D6, 3A4, and 2C9), sertraline (CYP2D6, 2C9, 2C19, 1A2, and 3A4), and venlafaxine (CYP2D6 and 2C19).DDIs from human hepatocytes assays revealed that gefitinib had significant metabolic changes in (1:1) combination with paroxetine or sertraline (p-value â€‹= â€‹0.042 and 0.025 respectively) and (1:1:1) combination with losartan and fluoxetine, fluvoxamine, paroxetine, or sertraline (p-value â€‹= â€‹0.009, 0.027, 0.048, and 0.037 respectively). Losartan showed significant changes in (1:1:1) combination with gefitinib and fluoxetine or sertraline (p-value â€‹= â€‹0.026 and 0.008 respectively). Fluoxetine, fluvoxamine, and paroxetine underwent significant changes in (1:1:1) combination with gefitinib and losartan (p-value â€‹= â€‹0.003, 0.022, and 0.046 respectively). Sertraline had significant changes within all combinations: DDIs with gefitinib alone and in combination with gefitinib and losartan (p-value â€‹= â€‹0.009 and 0.008 respectively). Citalopram and venlafaxine appeared to be unaffected by any combination. Conclusion: The study provides a clear proof-of concept for in vitro metabolic DDI testing. While identifying compounds by their inhibition potential can help better predict their metabolism, it cannot resolve problems that arise from DDIs since the overall degree of effectiveness is unknown. As shown in this study, gefitinib has been identified as a weak CYP2C19 and 2D6 inhibitor, however, gefitinib can have significant DDIs with sertraline. Furthermore, multiple drug combinations (1:1:1) can change the significance of previously determined DDIs in (1:1) combination. Thus, in vitro assays can potentially provide better guidance for multidrug regimens with minimal risk for DDIs.

Pre-clinical drug-drug interaction (DDI) of gefitinib or erlotinib with Cytochrome P450 (CYP) inhibiting drugs, fluoxetine and/or losartan.

OBJECTIVE: To evaluate drug-drug interactions (DDIs) between gefitinib or erlotinib with fluoxetine, and/or losartan. METHODS: Human pooled microsomes, supersomes, and cryopreserved human hepatocytes were used to monitor DDIs in vitro. RED (Rapid Equilibrium Dialysis) protein binding was employed to investigate other pharmacokinetics. RESULTS: Gefitinib is significantly metabolized by Cytochrome P450 (CYP) 2D6 and CYP3A4, with less than 80% of the drug remaining. Erlotinib is significantly metabolized by CYP3A4, CYP2D6, and CYP1A2. Although gefitinib and erlotinib were metabolized by the same CYP isoenzymes, the metabolites formed from degradation of the two drugs were different.Fluoxetine inhibited CYP2D6 and CYP3A4 metabolism of gefitinib with an IC50 of 65.12 ± 1.88 µM and 4.11 ± 2.26 µM, respectively. Fluoxetine also inhibited CYP2D6 and CYP3A4 metabolism of erlotinib with an IC50 of 7.06 ± 1.54 µM and 4.57 ± 1.22 µM, respectively.For hepatocytes, fluoxetine affected the metabolism of gefitinib or erlotinib, while losartan had no effect. Gefitinib and erlotinib inhibited the metabolism of fluoxetine and losartan. Two-drug combinations involving gefitinib or erlotinib with fluoxetine or losartan yielded insignificant (p-value ≥ 0.05) differences in metabolism. However, combinations involving three drugs yielded significant degrees of inhibition (p-value ≤ 0.05). Three drug combinations involving fluoxetine and losartan with gefitinib or erlotinib yielded significant degrees of inhibition of the metabolism of gefitinib, but not for that of erlotinib. CONCLUSION: As could be predicted by previous studies involving the inhibitory effect of fluoxetine on CYP3A4 and CYP2D6, and studies involving CYP metabolism of gefitinib and erlotinib, the tests performed here confirmed that fluoxetine has an inhibitory effect on metabolism of gefitinib or erlotinib by the main CYP isoenzymes involved. This study suggests a variable inhibitory effect of fluoxetine particularly on CYP2D6 activity towards gefitinib or erlotinib; erlotinib metabolism is less affected. Likewise, the combination of fluoxetine and losartan does not significantly affect hepatocyte metabolism of erlotinib, but does for that of gefitinib. The results presented in this study thus indicate a need for DDI assays to involve multiple drugs to properly study multidrug regimens.

Differential CYP 2D6 metabolism alters primaquine pharmacokinetics.

Primaquine (PQ) metabolism by the cytochrome P450 (CYP) 2D family of enzymes is required for antimalarial activity in both humans (2D6) and mice (2D). Human CYP 2D6 is highly polymorphic, and decreased CYP 2D6 enzyme activity has been linked to decreased PQ antimalarial activity. Despite the importance of CYP 2D metabolism in PQ efficacy, the exact role that these enzymes play in PQ metabolism and pharmacokinetics has not been extensively studied in vivo. In this study, a series of PQ pharmacokinetic experiments were conducted in mice with differential CYP 2D metabolism characteristics, including wild-type (WT), CYP 2D knockout (KO), and humanized CYP 2D6 (KO/knock-in [KO/KI]) mice. Plasma and liver pharmacokinetic profiles from a single PQ dose (20 mg/kg of body weight) differed significantly among the strains for PQ and carboxy-PQ. Additionally, due to the suspected role of phenolic metabolites in PQ efficacy, these were probed using reference standards. Levels of phenolic metabolites were highest in mice capable of metabolizing CYP 2D6 substrates (WT and KO/KI 2D6 mice). PQ phenolic metabolites were present in different quantities in the two strains, illustrating species-specific differences in PQ metabolism between the human and mouse enzymes. Taking the data together, this report furthers understanding of PQ pharmacokinetics in the context of differential CYP 2D metabolism and has important implications for PQ administration in humans with different levels of CYP 2D6 enzyme activity.