scholarly journals Model-based comparative analysis of rifampicin and rifabutin drug-drug interaction profile

2021 ◽  
Author(s):  
Vianney Tuloup ◽  
Mathilde France ◽  
Romain Garreau ◽  
Nathalie Bleyzac ◽  
Laurent Bourguignon ◽  
...  
Keyword(s):  
Cytochrome P450 ◽  
Drug Interaction ◽  
Comparative Analysis ◽  
Drug Interactions ◽  
Low Dose ◽  
Model Based ◽  
Staphylococcal Infections ◽  
Drug Drug Interaction

ABSTRACT: Rifamycins are widely used for treating mycobacterial and staphylococcal infections. Drug-drug interactions (DDI) caused by rifampicin (RIF) is a major issue. We used a model-based approach to predict the magnitude of DDI with RIF and rifabutin (RBT) for 217 cytochrome P450 (CYP) substrates. On average, DDI caused by low-dose RIF were twice more potent than those caused by RBT. Contrary to RIF, RBT appears unlikely to cause severe DDI, even with sensitive CYP substrates.

Pharmacokinetic Drug-drug Interaction of Antibiotics Used in Sepsis Care in China

2020 ◽  
Vol 21 ◽  
Author(s):  
Xuan Yu ◽  
Zixuan Chu ◽  
Jian Li ◽  
Rongrong He ◽  
Yaya Wang ◽  
...  
Keyword(s):  
Drug Interaction ◽  
Drug Interactions ◽  
Penicillin G ◽  
Literature Mining ◽  
Human Pharmacokinetics ◽  
P450 Enzyme ◽  
Drug Drug Interaction ◽  
Pharmacokinetic Drug ◽  
Sepsis Care

Background: Many antibiotics have a high potential for having an interaction with drugs, as perpetrator and/or victim, in critically ill patients, and particularly in sepsis patients. Methods: The aim of this review is to summarize the pharmacokinetic drug-drug interaction (DDI) of 45 antibiotics commonly used in sepsis care in China. Literature mining was conducted to obtain human pharmacokinetics/dispositions of the antibiotics, their interactions with drug metabolizing enzymes or transporters, and their associated clinical drug interactions. Potential DDI is indicated by a DDI index > 0.1 for inhibition or a treated-cell/untreated-cell ratio of enzyme activity being > 2 for induction. Results: The literature-mined information on human pharmacokinetics of the identified antibiotics and their potential drug interactions is summarized. Conclusion: Antibiotic-perpetrated drug interactions, involving P450 enzyme inhibition, have been reported for four lipophilic antibacterials (ciprofloxacin, erythromycin, trimethoprim, and trimethoprim-sulfamethoxazole) and three lipophilic antifungals (fluconazole, itraconazole, and voriconazole). In addition, seven hydrophilic antibacterials (ceftriaxone, cefamandole, piperacillin, penicillin G, amikacin, metronidazole, and linezolid) inhibit drug transporters in vitro. Despite no reported clinical PK drug interactions with the transporters, caution is advised in the use of these antibacterials. Eight hydrophilic antibacterials (all β-lactams; meropenem, cefotaxime, cefazolin, piperacillin, ticarcillin, penicillin G, ampicillin, and flucloxacillin), are potential victims of drug interactions due to transporter inhibition. Rifampin is reported to perpetrate drug interactions by inducing CYP3A or inhibiting OATP1B; it is also reported to be a victim of drug interactions, due to the dual inhibition of CYP3A4 and OATP1B by indinavir. In addition, three antifungals (caspofungin, itraconazole, and voriconazole) are reported to be victims of drug interactions because of P450 enzyme induction. Reports for other antibiotics acting as victims in drug interactions are scarce.

scholarly journals In vitro study on the effect of cornin on the activity of cytochrome P450 enzymes

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Qun Zhang ◽  
Zengqiang Qu ◽  
Yanqing Zhou ◽  
Jin Zhou ◽  
Junwei Yang ◽  
...  
Keyword(s):  
Cytochrome P450 ◽  
Drug Interaction ◽  
Liver Microsomes ◽  
In Vitro Study ◽  
Inhibitory Effect ◽  
Dependent Manner ◽  
Cytochrome P450 Enzymes ◽  
Drug Drug Interaction ◽  
Dose Dependent

Abstract Background Cornin is a commonly used herb in cardiology for its cardioprotective effect. The effect of herbs on the activity of cytochrome P450 enzymes (CYP450s) can induce adverse drug-drug interaction even treatment failure. Therefore, it is necessary to investigate the effect of cornin on the activity of CYP450s, which can provide more guidance for the clinical application of cornin. Methods Cornin (100 μM) was incubated with eight isoforms of CYP450s, including CYP1A2, 2A6, 3A4, 2C8, 2C9, 2C19, 2D6, and 2E1, in pooled human liver microsomes. The inhibition model and corresponding parameters were also investigated. Results Cornin exerted significant inhibitory effect on the activity of CYP3A4, 2C9, and 2E1 in a dose-dependent manner with the IC50 values of 9.20, 22.91, and 14.28 μM, respectively (p < 0.05). Cornin inhibited the activity of CYP3A4 non-competitively with the Ki value of 4.69 μM, while the inhibition of CYP2C9 and 2E1 by cornin was competitive with the Ki value of 11.31 and 6.54 μM, respectively. Additionally, the inhibition of CYP3A4 by cornin was found to be time-dependent with the KI/Kinact value of 6.40/0.055 min− 1·μM− 1. Conclusions The inhibitory effect of cornin on the activity of CYP3A4, 2C9, and 2E1 indicated the potential drug-drug interaction between cornin and drugs metabolized by these CYP450s, which needs further investigation and validation.

Comparison of eight screening tools to detect interactions between herbal supplements and oncology agents

2020 ◽  
Vol 26 (8) ◽  
pp. 1843-1849
Author(s):  
Faisal Shakeel ◽  
Fang Fang ◽  
Kelley M Kidwell ◽  
Lauren A Marcath ◽  
Daniel L Hertz
Keyword(s):  
Drug Interaction ◽  
Positive Predictive Value ◽  
Drug Interactions ◽  
Predictive Value ◽  
Screening Tools ◽  
Herbal Supplements ◽  
Interaction Detection ◽  
Natural Medicine ◽  
Interaction Screening ◽  
Drug Drug Interaction

Introduction Patients with cancer are increasingly using herbal supplements, unaware that supplements can interact with oncology treatment. Herb–drug interaction management is critical to ensure optimal treatment outcomes. Several screening tools exist to detect drug–drug interactions, but their performance to detect herb–drug interactions is not known. This study compared the performance of eight drug–drug interaction screening tools to detect herb–drug interaction with anti-cancer agents. Methods The herb–drug interaction detection performance of four subscription (Micromedex, Lexicomp, PEPID, Facts & Comparisons) and free (Drugs.com, Medscape, WebMD, RxList) drug–drug interaction tools was assessed. Clinical relevance of each herb–drug interaction was determined using Natural Medicine and each drug–drug interaction tool. Descriptive statistics were used to calculate sensitivity, specificity, positive predictive value, and negative predictive value. Linear regression was used to compare performance between subscription and free tools. Results All tools had poor sensitivity (<0.20) for detecting herb–drug interaction. Lexicomp had the highest positive predictive value (0.98) and best overall performance score (0.54), while Medscape was the best performing free tool (0.52). The worst subscription tools were as good as or better than the best free tools, and as a group subscription tools outperformed free tools on all metrics. Using an average subscription tool would detect one additional herb–drug interaction for every 10 herb–drug interactions screened by a free tool. Conclusion Lexicomp is the best available tool for screening herb–drug interaction, and Medscape is the best free alternative; however, the sensitivity and performance for detecting herb–drug interaction was far lower than for drug–drug interactions, and overall quite poor. Further research is needed to improve herb–drug interaction screening performance.

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