Drug–drug interactions in patients receiving tyrosine kinase inhibitors

Keller, Kristine L.; Franquiz, Miguel; Duffy, Alison; Trovato, James A.

doi:10.1177/1078155216682311

Cited by 22 publications

(15 citation statements)

References 17 publications

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“…In the study by Keller (Keller, Franquiz, Duffy, & Trovato, ), 244 interactions (44.7% severe) were identified in 356 patients on treatment with tyrosine kinase inhibitors. Authors used the same method as in our study: review of the technical data sheet and query of databases such as Micromedex Solutions®.…”

Section: Discussionmentioning

confidence: 99%

“…Several interventions have demonstrated the benefits associated with the participation of the pharmacist in the care of patients receiving oral chemotherapy (Backes, Griesbach, Wilhelm, & Plank, ; Vu, Wilson, Modlin, Kaster, & Mancini, ). Given the frequency of potential drug interactions identified in the literature, patients can benefit significantly from pharmaceutical interventions focused on the prevention and management of drug interactions associated with OADs (Keller et al, ).…”

Section: Discussionmentioning

confidence: 99%

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Drug interactions with oral antineoplastic drugs: The role of the pharmacist

et al. 2018

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The main objective of the study is to determine the pharmacist detection of drug‐drug and drug‐food interactions in patients receiving oral antineoplastic drugs (OADs). Descriptive, prospective study in a tertiary‐care teaching hospital. The study population included patients who received OADs from the Outpatient Pharmacy of the hospital. The study population was attended by a pharmacist who checked potential interactions. The severity of interactions was evaluated using the summary of product characteristics of each drug and three different databases. We included 219 patients with a total of 736 concomitant medications. A total of 34 drug‐drug or food‐drug interactions were recorded. The most common interaction detected was between erlotinib and ranitidine (major interaction). In 19 of the 34 interactions detected in the experimental group, the pharmacist prevented them from reaching the patient. Interactions were resolved by drug suspensions, drug changes, or changes in schedules always according to the attending physician or the patient. In the remaining 15 interactions, the doctor was not contacted because the interactions were considered to be of little relevance or because they only required surveillance. Hospital pharmacist can improve the patient's safety and the efficiency of oral cytostatic treatment by detecting and preventing drug‐drug and drug‐food interactions.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Drug interactions with oral antineoplastic drugs: The role of the pharmacist

et al. 2018

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“…Indeed, a recent study indicated that 97.1% of patients receiving treatment with TKIs were using at least one other drug simultaneously, with a median of 4 concurrent medications, and 47.4% experienced at least one potential TKI-mediated DDI [ 28 ]. In another study, 44.7% of the potential DDIs identified involving TKIs were considered severe [ 29 ]. Interestingly, most available data in this field have investigated TKIs as victims in DDIs [ 30 , 31 , 32 , 33 ], and conclusive information on their role as perpetrators in DDIs is generally lacking.…”

Section: Tyrosine Kinase Inhibitors (Tkis)mentioning

confidence: 99%

Role of OATP1B1 and OATP1B3 in Drug-Drug Interactions Mediated by Tyrosine Kinase Inhibitors

Garrison¹,

Talebi²,

Eisenmann³

et al. 2020

Pharmaceutics

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Failure to recognize important features of a drug’s pharmacokinetic characteristics is a key cause of inappropriate dose and schedule selection, and can lead to reduced efficacy and increased rate of adverse drug reactions requiring medical intervention. As oral chemotherapeutic agents, tyrosine kinase inhibitors (TKIs) are particularly prone to cause drug-drug interactions as many drugs in this class are known or suspected to potently inhibit the hepatic uptake transporters OATP1B1 and OATP1B3. In this article, we provide a comprehensive overview of the published literature and publicly-available regulatory documents in this rapidly emerging field. Our findings indicate that, while many TKIs can potentially inhibit the function of OATP1B1 and/or OATP1B3 and cause clinically-relevant drug-drug interactions, there are many inconsistencies between regulatory documents and the published literature. Potential explanations for these discrepant observations are provided in order to assist prescribing clinicians in designing safe and effective polypharmacy regimens, and to provide researchers with insights into refining experimental strategies to further predict and define the translational significance of TKI-mediated drug-drug interactions.

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“…Consequently, CYP3A4 activity may influence KI clearance and, hence, dosage and response. Moreover, clinically significant drug-drug interactions have been reported for several KIs when simultaneously dosed with CYP3A4 inhibitors or inducers (Duckett and Cameron, 2010;Keller et al, 2018). In addition, the CYP3A4catalyzed biotransformation of several KIs (e.g., erlotinib, dasatinib, gefitinib, and lapatinib) is known to result in the formation of reactive metabolites capable of covalently binding to cellular macromolecules (Duckett and Cameron, 2010).…”

Section: Introductionmentioning

confidence: 99%

Computational Prediction of the Site(s) of Metabolism and Binding Modes of Protein Kinase Inhibitors Metabolized by CYP3A4

Nair

Miners

2019

Drug Metab Dispos

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Protein kinase inhibitors (KIs), which are mainly biotransformed by CYP3A4-catalyzed oxidation, represent a rapidly expanding class of drugs used primarily for the treatment of cancer. Ligand-and structure-based methods were applied here to investigate whether computational approaches may be used to predict the site(s) of metabolism (SOM) of KIs and to identify amino acids within the CYP3A4 active site involved in KI binding. A data set of the experimentally determined SOMs of 31 KIs known to undergo biotransformation by CYP3A4 was collated. The structure-based (molecular docking) approach employed three CYP3A4 X-ray crystal structures to account for structural plasticity of this enzyme. Docking pose and SOM predictivity were influenced by the X-ray crystal template used for docking and the scoring function used for ranking binding poses. The best prediction of SOM (77%) was achieved using the substrate (bromoergocryptine)-bound X-ray crystal template together with the potential of mean force score. Binding interactions of KIs with CYP3A4 active site residues were generally similar to those observed for other substrates of this enzyme. The ligand-based molecular superposition approach, using bromoergocryptine from the X-ray cocrystal structure as a template, poorly predicted (42%) the SOM of KIs, although predictivity improved to 71% when the docked conformation of sorafenib was used as the template. Among the web-based approaches examined, all web servers provided excellent predictivity, with one web server predicting the SOM of 87% of the data set molecules. Computational approaches may be used to predict the SOM of KIs, and presumably other classes of CYP3A4 substrates, but predictivity varies between methods.

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Drug–drug interactions in patients receiving tyrosine kinase inhibitors

Cited by 22 publications

References 17 publications

Drug interactions with oral antineoplastic drugs: The role of the pharmacist

Drug interactions with oral antineoplastic drugs: The role of the pharmacist

Role of OATP1B1 and OATP1B3 in Drug-Drug Interactions Mediated by Tyrosine Kinase Inhibitors

Computational Prediction of the Site(s) of Metabolism and Binding Modes of Protein Kinase Inhibitors Metabolized by CYP3A4

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