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Drug–Drug Interactions (Volume II)

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A special issue of Pharmaceutics (ISSN 1999-4923). This special issue belongs to the section "Pharmacokinetics and Pharmacodynamics".

Deadline for manuscript submissions: closed (28 February 2022) | Viewed by 35262

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Prof. Dr. Dong Hyun Kim

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Department of Pharmacology and PharmacoGenomics Research Center, Inje University College of Medicine, Inje University, Busan 47392, Republic of Korea
Interests: drug–drug interaction; metabolomics; drug metabolism and pharmacokinetics
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Prof. Dr. Sangkyu Lee

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College of Pharmacy and Research Institute of Pharmaceutical Sciences, Kyungpook National University, Daegu, Republic of Korea
Interests: proteomics; drug metabolism; mass spectrometry
Special Issues, Collections and Topics in MDPI journals

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Dear Colleagues,

Drug–drug interactions (DDIs) cause one drug to affect other drugs, leading to a reduced drug efficacy or an increased toxicity of the affected drugs. In some cases, drug interactions are reported to cause severe adverse drug reactions that are life-threatening to the patient. Traditionally, DDIs have been evaluated around the selective action of drugs on specific CYP enzymes. The interaction of drugs based on CYPs is still very important for drug interactions but, recently, other important mechanisms have also been studied as contributing to the drug interactions, such as drug transporter- or UDP-glucuronyltransferase-mediated DDI. In addition, the novel mechanism to regulate DDI can also be suggested. In the case of the substance to be interacted, not only the DDI, but also the herb– or food–drug interactions have been reported to be clinically relevant in terms of adverse side effects. Reporting examples of drug interactions on a marketed drug or a new mechanism study will be very helpful for preventing the side effects of the patient taking them. This Special Issue has the aim of highlighting the current progress in the clinical or non-clinical interactions of commercial drugs and the elucidation of the mechanism of drug interactions.

Prof. Dr. Dong Hyun Kim
Prof. Dr. Sangkyu Lee
Guest Editors

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Keywords

drug–drug interaction
cytochrome P450
UDP-glucuronyltransferase
transporter
pharmacokinetics
pharmacogenetics
adverse drug interaction

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Drug–Drug Interactions in Pharmaceutics (15 articles)

Published Papers (10 papers)

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Research

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22 pages, 2676 KiB

Open AccessEditor’s ChoiceArticle

Physiologically Based Pharmacokinetic (PBPK) Modeling of Clopidogrel and Its Four Relevant Metabolites for CYP2B6, CYP2C8, CYP2C19, and CYP3A4 Drug–Drug–Gene Interaction Predictions

by Helena Leonie Hanae Loer, Denise Türk, José David Gómez-Mantilla, Dominik Selzer and Thorsten Lehr

Pharmaceutics 2022, 14(5), 915; https://doi.org/10.3390/pharmaceutics14050915 - 22 Apr 2022

Cited by 5 | Viewed by 4562

Abstract

The antiplatelet agent clopidogrel is listed by the FDA as a strong clinical index inhibitor of cytochrome P450 (CYP) 2C8 and weak clinical inhibitor of CYP2B6. Moreover, clopidogrel is a substrate of—among others—CYP2C19 and CYP3A4. This work presents the development of a whole-body physiologically based pharmacokinetic (PBPK) model of clopidogrel including the relevant metabolites, clopidogrel carboxylic acid, clopidogrel acyl glucuronide, 2-oxo-clopidogrel, and the active thiol metabolite, with subsequent application for drug–gene interaction (DGI) and drug–drug interaction (DDI) predictions. Model building was performed in PK-Sim^® using 66 plasma concentration-time profiles of clopidogrel and its metabolites. The comprehensive parent-metabolite model covers biotransformation via carboxylesterase (CES) 1, CES2, CYP2C19, CYP3A4, and uridine 5′-diphospho-glucuronosyltransferase 2B7. Moreover, CYP2C19 was incorporated for normal, intermediate, and poor metabolizer phenotypes. Good predictive performance of the model was demonstrated for the DGI involving CYP2C19, with 17/19 predicted DGI AUC_last and 19/19 predicted DGI C_max ratios within 2-fold of their observed values. Furthermore, DDIs involving bupropion, omeprazole, montelukast, pioglitazone, repaglinide, and rifampicin showed 13/13 predicted DDI AUC_last and 13/13 predicted DDI C_max ratios within 2-fold of their observed ratios. After publication, the model will be made publicly accessible in the Open Systems Pharmacology repository. Full article

(This article belongs to the Special Issue Drug–Drug Interactions (Volume II))

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11 pages, 2710 KiB

Open AccessArticle

The Intake of Coffee Increases the Absorption of Aspirin in Mice by Modifying Gut Microbiome

by Jeon-Kyung Kim, Min Sun Choi, Hye Hyun Yoo and Dong-Hyun Kim

Pharmaceutics 2022, 14(4), 746; https://doi.org/10.3390/pharmaceutics14040746 - 30 Mar 2022

Cited by 9 | Viewed by 3452

Abstract

The absorption of orally administered aspirin into the blood was affected by gastrointestinal environmental factors such as gut pH, digestive enzymes, and microbiota. The intake of coffee affects the pharmacological effects of aspirin. Therefore, we examined the gut microbiota-mediated effect of coffee bean extract (CBE) intake on the pharmacokinetics of aspirin in mice. The intake of CBE modified the gut microbiota composition and their α- and β-diversities: It decreased the Proteobacteria, Helicobacteriaceae, and Bacteroidaceae populations in the fecal microbiota composition, while the S24-7_f (Muribaculaceae) and Lactobacillaceae populations increased. The fecal aspirin-hydrolyzing activities of humans and mice to salicylic acid were 0.045 ± 0.036 μmole/h/g and 0.032 ± 0.003 μmole/h/g, respectively. However, CBE treatment significantly suppressed the aspirin-hydrolyzing activity in mice. Furthermore, the area under the serum concentration–time curves (AUCs) of aspirin and salicylic acid were 0.265 ± 0.050 µg·h/mL and 16.224 ± 5.578 µg·h/mL in CBE-treated mice, respectively, and 0.248 ± 0.042 µg·h/mL and 10.756 ± 2.071 µg·h/mL in control mice, respectively. Moreover, CBE treatment suppressed the multidrug resistance protein 4 (Mrp4) expression in the intestines of mice, while the P-glycoprotein (P-gp), breast cancer resistance protein (BCRP) expression was not affected. Furthermore, the CBE-treated mouse fecal lysate suppressed Mrp4 expression in Caco-2 cells compared to that of vehicle-treated mice, while CBE treatment did not affect Mrp4 expression. Oral gavage of caffeine also suppressed the Mrp4 expression in the intestines of mice. These findings suggest that intake of coffee can increase the absorption of aspirin by modifying the gut microbiome. Full article

(This article belongs to the Special Issue Drug–Drug Interactions (Volume II))

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16 pages, 1745 KiB

Open AccessEditor’s ChoiceArticle

Interaction of Antifungal Drugs with CYP3A- and OATP1B-Mediated Venetoclax Elimination

by Eric D. Eisenmann, Dominique A. Garrison, Zahra Talebi, Yan Jin, Josie A. Silvaroli, Jin-Gyu Kim, Alex Sparreboom, Michael R. Savona, Alice S. Mims and Sharyn D. Baker

Pharmaceutics 2022, 14(4), 694; https://doi.org/10.3390/pharmaceutics14040694 - 23 Mar 2022

Cited by 7 | Viewed by 2898

Abstract

Venetoclax, a BCL-2 inhibitor used to treat certain hematological cancers, exhibits low oral bioavailability and high interpatient pharmacokinetic variability. Venetoclax is commonly administered with prophylactic antifungal drugs that may result in drug interactions, of which the underlying mechanisms remain poorly understood. We hypothesized that antifungal drugs may increase venetoclax exposure through inhibition of both CYP3A-mediated metabolism and OATP1B-mediated transport. Pharmacokinetic studies were performed in wild-type mice and mice genetically engineered to lack all CYP3A isoforms, or OATP1B2 that received venetoclax alone or in combination with ketoconazole or micafungin. In mice lacking all CYP3A isoforms, venetoclax AUC was increased by 1.8-fold, and pretreatment with the antifungal ketoconazole further increased venetoclax exposure by 1.6-fold, despite the absence of CYP3A. Ensuing experiments demonstrated that the deficiency of OATP1B-type transporters is also associated with increases in venetoclax exposure, and that many antifungal drugs, including micafungin, posaconazole, and isavuconazole, are inhibitors of this transport mechanism both in vitro and in vivo. These studies have identified OATP1B-mediated transport as a previously unrecognized contributor to the elimination of venetoclax that is sensitive to inhibition by various clinically-relevant antifungal drugs. Additional consideration is warranted when venetoclax is administered together with agents that inhibit both CYP3A-mediated metabolism and OATP1B-mediated transport. Full article

(This article belongs to the Special Issue Drug–Drug Interactions (Volume II))

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19 pages, 889 KiB

Open AccessArticle

Prevalence and Severity of Potential Drug–Drug Interactions in Patients with Multiple Sclerosis with and without Polypharmacy

by Paula Bachmann, Niklas Frahm, Jane Louisa Debus, Pegah Mashhadiakbar, Silvan Elias Langhorst, Barbara Streckenbach, Julia Baldt, Felicita Heidler, Michael Hecker and Uwe Klaus Zettl

Pharmaceutics 2022, 14(3), 592; https://doi.org/10.3390/pharmaceutics14030592 - 08 Mar 2022

Cited by 7 | Viewed by 2979

Abstract

Polypharmacy (PP) is a common problem in modern medicine, especially known to affect patients with chronic diseases such as multiple sclerosis (MS). With an increasing number of drugs taken, the risk of potential drug–drug interactions (pDDIs) is rising. This study aims to assess the prevalence and clinical relevance of polypharmacy and pDDIs in patients with MS. Pharmacological data of 627 patients with MS were entered into two drug–drug-interaction databases to determine the number and severity of pDDIs for each patient. The patients were divided into those with and without PP (total PP and prescription medication PP (Rx PP)). Of the 627 patients included, 53.3% and 38.6% had total PP and Rx PP, respectively. On average, every patient took 5.3 drugs. Of all patients, 63.8% had at least one pDDI with a mean of 4.6 pDDIs per patient. Less than 4% of all pDDIs were moderately severe or severe. Medication schedules should be checked for inappropriate medication and for possible interacting drugs to prevent pDDIs. Physicians as well as pharmacists should be more sensitive towards the relevance of pDDIs and know how they can be detected and avoided. Full article

(This article belongs to the Special Issue Drug–Drug Interactions (Volume II))

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12 pages, 1059 KiB

Open AccessArticle

Verification of the “Upward Variation in the Reporting Odds Ratio Scores” to Detect the Signals of Drug–Drug Interactions

by Yoshihiro Noguchi, Shunsuke Yoshizawa, Keisuke Aoyama, Satoaki Kubo, Tomoya Tachi and Hitomi Teramachi

Pharmaceutics 2021, 13(10), 1531; https://doi.org/10.3390/pharmaceutics13101531 - 22 Sep 2021

Cited by 11 | Viewed by 1967

Abstract

The reporting odds ratio (ROR) is easy to calculate, and there have been several examples of its use because of its potential to speed up the detection of drug–drug interaction signals by using the “upward variation of ROR score”. However, since the validity of the detection method is unknown, this study followed previous studies to investigate the detection trend. The statistics models (the Ω shrinkage measure and the “upward variation of ROR score”) were compared using the verification dataset created from the Japanese Adverse Drug Event Report database (JADER). The drugs registered as “suspect drugs” in the verification dataset were considered as the drugs to be investigated, and the target adverse event in this study was Stevens–Johnson syndrome (SJS), as in previous studies. Of 3924 pairs that reported SJS, the number of positive signals detected by the Ω shrinkage measure and the “upward variation of ROR score” (Model 1, the Susuta Model, and Model 2) was 712, 2112, 1758, and 637, respectively. Furthermore, 1239 positive signals were detected when the Haldane–Anscombe 1/2 correction was applied to Model 2, the statistical model that showed the most conservative detection trend. This result indicated the instability of the positive signal detected in Model 2. The ROR scores based on the frequency-based statistics are easily inflated; thus, the use of the “upward variation of ROR scores” to search for drug–drug interaction signals increases the likelihood of false-positive signal detection. Consequently, the active use of the “upward variation of ROR scores” is not recommended, despite the existence of the Ω shrinkage measure, which shows a conservative detection trend. Full article

(This article belongs to the Special Issue Drug–Drug Interactions (Volume II))

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13 pages, 1504 KiB

Open AccessArticle

Assessing CYP2C8-Mediated Pharmaceutical Excipient-Drug Interaction Potential: A Case Study of Tween 80 and Cremophor EL−35

by Chengming Wen, Haoyang Hu, Wenwen Zhang, Xin Liu, Xuehua Jiang and Ling Wang

Pharmaceutics 2021, 13(9), 1492; https://doi.org/10.3390/pharmaceutics13091492 - 17 Sep 2021

Cited by 4 | Viewed by 2027

Abstract

Pharmaceutical excipients (PEs) are substances included in drug formulations. Recent studies have revealed that some PEs can affect the activity of metabolic enzymes and drug transporters; however, the effects of PEs on CYP2C8 and its interaction potential with drugs remain unclear. In this study, we evaluated the effects of Tween 80 and EL−35 on CYP2C8 in vitro and further investigated their impacts on the PK of paclitaxel (PTX) in rats after single or multiple doses. The in vitro study indicated that Tween 80 and EL−35 inhibited CYP2C8 activity in human and rat liver microsomes. EL−35 also decreased the expression of CYP2C8 in HepG2 cells. In the in vivo study, Tween 80 did not alter the PK of PTX after single or multiple doses, whereas EL−35 administered for 14 days significantly increased the AUC and MRT of PTX. Further analysis indicated that multiple-dose EL−35 reduced the expression of Cyp2c22 and production of 6-OH-PTX in the rat liver. Our study suggested that short-term exposure to both PEs did not affect the PK of PTX in rats, but multiple doses of EL−35 increased the AUC and MRT of PTX by downregulating the hepatic expression of Cyp2c22. Such effects should be taken into consideration during drug formulation and administration. Full article

(This article belongs to the Special Issue Drug–Drug Interactions (Volume II))

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13 pages, 1466 KiB

Open AccessArticle

Structure-Functional Analysis of Human Cytochrome P450 2C8 Using Directed Evolution

by Rowoon Lee, Vitchan Kim, Youngjin Chun and Donghak Kim

Pharmaceutics 2021, 13(9), 1429; https://doi.org/10.3390/pharmaceutics13091429 - 09 Sep 2021

Cited by 5 | Viewed by 1920

Abstract

The human genome includes four cytochrome P450 2C subfamily enzymes, and CYP2C8 has generated research interest because it is subject to drug–drug interactions and various polymorphic outcomes. To address the structure-functional complexity of CYP2C8, its catalytic activity was studied using a directed evolution analysis. Consecutive rounds of random mutagenesis and screening using 6-methoxy-luciferin produced two mutants, which displayed highly increased luciferase activity. Wild-type and selected mutants were expressed on a large scale and purified. The expression levels of the D349Y and D349Y/V237A mutants were ~310 and 460 nmol per liter of culture, respectively. The steady-state kinetic analysis of paclitaxel 6α-hydroxylation showed that the mutants exhibited a 5–7-fold increase in k_cat values and a 3–5-fold increase in catalytic efficiencies (k_cat/K_M). In arachidonic acid epoxidation, two mutants exhibited a 30–150-fold increase in k_cat values and a 40–110-fold increase in catalytic efficiencies. The binding titration analyses of paclitaxel and arachidonic acid showed that the V237A mutation had a lower K_d value, indicating a tighter substrate-binding affinity. The structural analysis of CYP2C8 indicated that the D349Y mutation was close enough to the putative binding domain of the redox partner; the increase in catalytic activity could be partially attributed to the enhancement of the P450 coupling efficiency or electron transfer. Full article

(This article belongs to the Special Issue Drug–Drug Interactions (Volume II))

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Review

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27 pages, 405 KiB

Open AccessReview

Drug-Drug Interactions of Direct Oral Anticoagulants (DOACs): From Pharmacological to Clinical Practice

by Nicola Ferri, Elisa Colombo, Marco Tenconi, Ludovico Baldessin and Alberto Corsini

Pharmaceutics 2022, 14(6), 1120; https://doi.org/10.3390/pharmaceutics14061120 - 24 May 2022

Cited by 33 | Viewed by 7725

Abstract

The direct oral anticoagulants (DOACs), dabigatran, rivaroxaban, apixaban, and edoxaban, are becoming the most commonly prescribed drugs for preventing ischemic stroke in patients with non-valvular atrial fibrillation (NVAF) and for the treatment and prevention of venous thromboembolism (VTE). Rivaroxaban was also recently approved for the treatment of patients with a recent acute coronary syndrome (ACS). Their use demonstrated to have a favorable risk-benefit profile, with significant reductions in stroke, intracranial hemorrhage, and mortality compared to warfarin, but with increased gastrointestinal bleeding. Nevertheless, their safety profile is compromised in multimorbidity patients requiring contemporary administration of several drugs. Comorbidity and polypharmacy have a high prevalence in elderly patients, who are also more susceptible to bleeding events. The combination of multiple treatments can cause relevant drug–drug interactions (DDIs) by affecting the exposure or the pharmacological activities of DOACs. Although important differences of the pharmacokinetic (PK) properties can be observed between DOACs, all of them are substrate of P-glycoprotein (P-gp) and thus may interact with strong inducers or inhibitors of this drug transporter. On the contrary, rivaroxaban and, to a lower extent, apixaban, are also susceptible to drugs altering the cytochrome P450 isoenzyme (CYP) activities. In the present review, we summarize the potential DDI of DOACs with several classes of drugs that have been reported or have characteristics that may predict clinically significant DDIs when administered together with DOACs. Possible strategies, including dosage reduction, avoiding concomitant administration, or different time of treatment, will be also discussed to reduce the incidence of DDI with DOACs. Considering the available data from specific clinical trials or registries analysis, the use of DOACs is associated with fewer clinically relevant DDIs than warfarin, and their use represents an acceptable clinical choice. Nevertheless, DDIs can be significant in certain patient conditions so a careful evaluation should be made before prescribing a specific DOAC. Full article

(This article belongs to the Special Issue Drug–Drug Interactions (Volume II))

17 pages, 319 KiB

Open AccessReview

Magnitude of Drug–Drug Interactions in Special Populations

by Sara Bettonte, Mattia Berton and Catia Marzolini

Pharmaceutics 2022, 14(4), 789; https://doi.org/10.3390/pharmaceutics14040789 - 04 Apr 2022

Cited by 5 | Viewed by 2248

Abstract

Drug–drug interactions (DDIs) are one of the most frequent causes of adverse drug reactions or loss of treatment efficacy. The risk of DDIs increases with polypharmacy and is therefore of particular concern in individuals likely to present comorbidities (i.e., elderly or obese individuals). These special populations, and the population of pregnant women, are characterized by physiological changes that can impact drug pharmacokinetics and consequently the magnitude of DDIs. This review compiles existing DDI studies in elderly, obese, and pregnant populations that include a control group without the condition of interest. The impact of physiological changes on the magnitude of DDIs was then analyzed by comparing the exposure of a medication in presence and absence of an interacting drug for the special population relative to the control population. Aging does not alter the magnitude of DDIs as the related physiological changes impact the victim and perpetrator drugs to a similar extent, regardless of their elimination pathway. Conversely, the magnitude of DDIs can be changed in obese individuals or pregnant women, as these conditions impact drugs to different extents depending on their metabolic pathway. Full article

(This article belongs to the Special Issue Drug–Drug Interactions (Volume II))

27 pages, 428 KiB

Open AccessReview

The Overview on the Pharmacokinetic and Pharmacodynamic Interactions of Triazoles

by Andrzej Czyrski, Matylda Resztak, Paweł Świderski, Jan Brylak and Franciszek K. Główka

Pharmaceutics 2021, 13(11), 1961; https://doi.org/10.3390/pharmaceutics13111961 - 19 Nov 2021

Cited by 21 | Viewed by 3834

Abstract

Second generation triazoles are widely used as first-line drugs for the treatment of invasive fungal infections, including aspergillosis and candidiasis. This class, along with itraconazole, voriconazole, posaconazole, and isavuconazole, is characterized by a broad range of activity, however, individual drugs vary considerably in safety, tolerability, pharmacokinetics profiles, and interactions with concomitant medications. The interaction may be encountered on the absorption, distribution, metabolism, and elimination (ADME) step. All triazoles as inhibitors or substrates of CYP isoenzymes can often interact with many drugs, which may result in the change of the activity of the drug and cause serious side effects. Drugs of this class should be used with caution with other agents, and an understanding of their pharmacokinetic profile, safety, and drug-drug interaction profiles is important to provide effective antifungal therapy. The manuscript reviews significant drug interactions of azoles with other medications, as well as with food. The PubMed and Google Scholar bases were searched to collect the literature data. The interactions with anticonvulsants, antibiotics, statins, kinase inhibitors, proton pump inhibitors, non-nucleoside reverse transcriptase inhibitors, opioid analgesics, benzodiazepines, cardiac glycosides, nonsteroidal anti-inflammatory drugs, immunosuppressants, antipsychotics, corticosteroids, biguanides, and anticoagulants are presented. We also paid attention to possible interactions with drugs during experimental therapies for the treatment of COVID-19. Full article

(This article belongs to the Special Issue Drug–Drug Interactions (Volume II))

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