Interaction potential between clarithromycin and individual statins-A systematic review

Statin-Associated Liver Dysfunction and Muscle Injury: epidemiology, Mechanisms, and Management Strategies

Surveillance of drug safety is an important aspect in the routine medical care. Adverse events caused by real-world drug utilization has become one of the leading causes of death and an urgent issue in the field of toxicology. Cardiovascular disease is now the leading cause of fatal diseases in most countries, especially in the elderly population who often suffer from multiple diseases and need long-term multidrug therapy. Among which, statins have been widely used to lower bad cholesterol and regress coronary plaque mainly in patients with hyperlipidemia and atherosclerotic cardiovascular diseases (ASCVD). Although the real-world benefits of statins are significant, different degrees and types of adverse drug reactions (ADR) such as liver dysfunction and muscle injury, have a great impact on the original treatment regimens as well as the quality of life. This review describes the epidemiology, mechanisms, early identification and post-intervention of statin-associated liver dysfunction and muscle injury based on the updated clinical evidence. It provides systematic and comprehensive guidance and necessary supplement for the clinical safety of statin use in cardiovascular diseases.

Identifying Drug-Drug Interactions in Spontaneous Reports Utilizing Signal Detection and Biological Plausibility Aspects

Translational approaches can benefit post-marketing drug safety surveillance through the growing availability of systems pharmacology data. Here, we propose a novel Bayesian framework for identifying drug-drug interaction (DDI) signals and differentiating between individual drug and drug combination signals. This framework is coupled with a systems pharmacology approach for automated biological plausibility assessment. Integrating statistical and biological evidence, our method achieves a 16.5% improvement (AUC: from 0.620 to 0.722) with drug-target-adverse event associations, 16.0% (AUC: from 0.580 to 0.673) with drug enzyme, and 15.0% (AUC: from 0.568 to 0.653) with drug transporter information. Applying this approach to detect potential DDI signals of QT prolongation and rhabdomyolysis within the FDA Adverse Event Reporting System (FAERS), we emphasize the significance of systems pharmacology in enhancing statistical signal detection in pharmacovigilance. Our study showcases the promise of data-driven biological plausibility assessment in the context of challenging post-marketing DDI surveillance.

Genetic Determinants of Response to Statins in Cardiovascular Diseases

Despite extensive efforts to identify patients with cardiovascular disease (CVD) who could most benefit from the treatment approach, patients vary in their benefit from therapy and propensity for adverse drug events. Genetic variability in individual responses to drugs (pharmacogenetics) is considered an essential determinant in responding to a drug. Thus, understanding these pharmacogenomic relationships has led to a substantial focus on mechanisms of disease and drug response. In turn, understanding the genomic and molecular bases of variables that might be involved in drug response is the main step in personalized medicine. There is a growing body of data evaluating drug-gene interactions in recent years, some of which have led to FDA recommendations and detection of markers to predict drug responses (e.g., genetic variant in VKORC1 and CYP2C9 genes for prediction of drug response in warfarin treatment). Also, statins are widely prescribed drugs for the prevention of CVD. Atorvastatin, fluvastatin, rosuvastatin, simvastatin, and lovastatin are the most common statins used to manage dyslipidemia. This review provides an overview of the current knowledge on the pharmacogenetics of statins, which are being used to treat cardiovascular diseases.

Statins-From Fungi to Pharmacy

Statins have been used in the treatment of hyperlipidemia, both as monotherapy and in combination therapy. Natural fermentation processes of fungi such as Monascus spp., Penicillium spp., Aspergillus terreus, and Pleurotus ostreatus have given rise to natural statins. Compactin (mevastatin), the original naturally occurring statin, is the primary biotransformation substrate in the manufacturing process of marketed drugs. Statins are classified into natural, semi-synthetic derivatives of natural statins, and synthetic ones. Synthetic statins differ from natural statins in their structural composition, with the only common feature being the HMG-CoA-like moiety responsible for suppressing HMG-CoA reductase. Statins do not differ significantly regarding their pleiotropic and adverse effects, but their characteristics depend on their pharmacokinetic parameters and chemical properties. This paper focuses on describing the processes of obtaining natural statins, detailing the pharmacokinetics of available statins, divided into natural and synthetic, and indicating their pleiotropic effects.

Macrolide and Ketolide Antibiotics Inhibit the Cytotoxic Effect of Trastuzumab Emtansine in HER2-Positive Breast Cancer Cells: Implication of a Potential Drug-ADC Interaction in Cancer Chemotherapy

Macrolides are widely used for the long-term treatment of infections and chronic inflammatory diseases. The pharmacokinetic features of macrolides include extensive tissue distribution because of favorable membrane permeability and accumulation within lysosomes. Trastuzumab emtansine (T-DM1), a HER2-targeting antibody-drug conjugate (ADC), is catabolized in the lysosomes, where Lys-SMCC-DM1, a potent cytotoxic agent, is processed by proteinase degradation and subsequently released from the lysosomes to the cytoplasm through the lysosomal membrane transporter SLC46A3, resulting in an antitumor effect. We recently demonstrated that erythromycin and clarithromycin inhibit SLC46A3 and attenuate the cytotoxicity of T-DM1; however, the effect of other macrolides and ketolides has not been determined. In this study, we evaluated the effect of macrolide and ketolide antibiotics on T-DM1 cytotoxicity in a human breast cancer cell line, KPL-4. Macrolides used in the clinic, such as roxithromycin, azithromycin, and josamycin, as well as solithromycin, a ketolide under clinical development, significantly attenuated T-DM1 cytotoxicity in addition to erythromycin and clarithromycin. Of these, azithromycin was the most potent inhibitor of T-DM1 efficacy. These antibiotics significantly inhibited the transport function of SLC46A3 in a concentration-dependent manner. Moreover, these compounds extensively accumulated in the lysosomes at the levels estimated to be 0.41-13.6 mM when cells were incubated with them at a 2 μM concentration. The immunofluorescence staining of trastuzumab revealed that azithromycin and solithromycin inhibit the degradation of T-DM1 in the lysosomes. These results suggest that the attenuation of T-DM1 cytotoxicity by macrolide and ketolide antibiotics involves their lysosomal accumulation and results in their greater lysosomal concentrations to inhibit the SLC46A3 function and T-DM1 degradation. This suggests a potential drug-ADC interaction during cancer chemotherapy.

Evaluation of the Selectivity of Several Organic Anion Transporting Polypeptide 1B Biomarkers Using Relative Activity Factor Method

In recent years, some endogenous substrates of organic anion transporting polypeptide 1B (OATP1B) have been identified and characterized as potential biomarkers to assess OATP1B-mediated clinical drug-drug interactions (DDIs). However, quantitative determination of their selectivity to OATP1B is still limited. In this study, we developed a relative activity factor (RAF) method to determine the relative contribution of hepatic uptake transporters OATP1B1, OATP1B3, OATP2B1, and sodium-taurocholate co-transporting polypeptide (NTCP) on hepatic uptake of several OATP1B biomarkers, including coproporphyrin I (CPI), coproporphyrin I CPIII, and sulfate conjugates of bile acids: glycochenodeoxycholic acid sulfate (GCDCA-S), glycodeoxycholic acid sulfate (GDCA-S), and taurochenodeoxycholic acid sulfate (TCDCA-S). RAF values for OATP1B1, OATP1B3, OATP2B1, and NTCP were determined in cryopreserved human hepatocytes and transporter transfected cells using pitavastatin, cholecystokinin, resveratrol-3-O-β-D-glucuronide, and taurocholic acid (TCA) as reference compounds, respectively. OATP1B1-specific pitavastatin uptake in hepatocytes was measured in the absence and presence of 1 µM estropipate, whereas NTCP-specific TCA uptake was measured in the presence of 10 µM rifampin. Our studies suggested that CPI was a more selective biomarker for OATP1B1 than CPIII, whereas GCDCA-S and TCDCA-S were more selective to OATP1B3. OATP1B1 and OATP1B3 equally contributed to hepatic uptake of GDCA-S. The mechanistic static model, incorporating the fraction transported of CPI/III estimated by RAF and in vivo elimination data, predicted several perpetrator interactions with CPI/III. Overall, RAF method combined with pharmacogenomic and DDI studies is a useful tool to determine the selectivity of transporter biomarkers and facilitate the selection of appropriate biomarkers for DDI evaluation. SIGNIFICANCE STATEMENT: The authors developed a new relative activity factor (RAF) method to quantify the contribution of hepatic uptake transporters organic anion transporting polypeptide (OATP)1B1, OATP1B3, OATP2B1, and sodium taurocholate co-transporting polypeptide (NTCP) on several OATP1B biomarkers and evaluated their predictive value on drug-drug interactions (DDI). These studies suggest that the RAF method is a useful tool to determine the selectivity of transporter biomarkers. This method combined with pharmacogenomic and DDI studies will mechanistically facilitate the selection of appropriate biomarkers for DDI prediction.

Antibiotics and Lipid-Modifying Agents: Potential Drug-Drug Interactions and Their Clinical Implications

Evidence-based prescribing requires taking into consideration the many aspects of optimal drug administration (e.g., dosage, comorbidities, co-administered drugs, etc.). A key issue is the administration of drugs for acute disorders that may potentially interfere with previously prescribed long-term medications. Initiating an antibiotic for an acute bacterial infection constitutes a common example. Hence, appropriate knowledge and awareness of the potential DDIs of antibiotics would lead to proper adjustments, thus preventing over- or under-treatment. For example, some statins, which are the most prescribed lipid-modifying agent (LMA), can lead to clinically important drug-drug interactions (DDIs) with the concurrent administration of antibiotics, e.g., macrolides. This review discusses the clinically significant DDIs of antibiotics associated with co-administrated lipid-lowering therapy and highlights common cases where regimen modifications may or may not be necessary.

Rhabdomyolysis caused by interaction between rosuvastatin and vadadustat: a case control study

BACKGROUND

Rhabdomyolysis is a potentially life-threatening disease caused by melting or necrosis of skeletal muscle cells and leakage of muscle components into the bloodstream. It has been reported that the interaction of the HMG-CoA reductase inhibitor rosuvastatin with the renal anemia drug vadadustat increases the blood concentration of rosuvastatin in vitro. In this study, we report a case of suspected rhabdomyolysis caused by the drug interaction of rosuvastatin and vadadustat in clinical practice.

CASE PRESENTATION

A 62-year-old male with medical records of hypertension, myocardial infarction, chronic renal failure, renal anemia, dyslipidemia, and alcoholic liver disease. The patient had been diagnosed with chronic kidney disease (CKD) at the Department of Nephrology, and treated by outpatient care with renal support therapy for the past two years. On X-63 day, his prescription was rosuvastatin (10 mg/day) and a continuous erythrocyte-stimulating agent, epoetin beta pegol (genetical recombination, 100 μg). X-Day 0, blood tests revealed creatine phosphokinase (CPK) 298 U/L, serum creatinine (SCr) 5.26 mg/dL, and hemoglobin (Hb) 9.5 g/dL; thus, the prescription was changed from epoetin beta pegol 100 μg to vadadustat 300 mg/day. On X + day 80, a prescription for a diuretic (azosemide 15 mg/day) was added for swelling of the lower extremities. On X + day 105, we found CPK 16,509 U/L, SCr 6.51 mg/dL, and Hb 9.5 g/dL. The patient was diagnosed as rhabdomyolysis and hospitalized. After hospitalization, rosuvastatin and vadadustat were discontinued and we administered intravenous fluids. Thereafter, CPK and SCr values of the patient improved. On X + day 122, CPK improved to 29 U/L, SCr to 2.6 mg/dL, and Hb to 9.6 g/dL, and he was discharged on X + day 124. At discharge, rosuvastatin 2.5 mg/day was resumed. A blood test on X + day 133 showed CPK 144 U/L and SCr 4.2 mg/dL.

CONCLUSION

We experienced a case of rhabdomyolysis caused by drug interactions between rosuvastatin and vadadustat.

Drug-Drug Interaction Surveillance Study: Comparing Self-Controlled Designs in Five Empirical Examples in Real-World Data

Self-controlled designs, specifically the case-crossover (CCO) and the self-controlled case series (SCCS), are increasingly utilized to generate real-world evidence (RWE) on drug-drug interactions (DDIs). Although these designs share the advantages and limitations of within-individual comparison, they also have design-specific assumptions. It is not known to what extent the differences in assumptions lead to different results in RWE DDI analyses. Using a nationwide US commercial healthcare insurance database (2006-2016), we compared the CCO and SCCS designs, as they are implemented in DDI studies, within five DDI-outcome examples: (1) simvastatin + clarithromycin and muscle-related toxicity; (2) atorvastatin + valsartan, and muscle-related toxicity; and (3-5) dabigatran + P-glycoprotein inhibitor (clarithromycin, amiodarone, and verapamil) and bleeding. Analyses were conducted within person-time exposed to the object drug (statins and dabigatran) and adjusted for bias associated with the inhibiting drugs via control groups of individuals unexposed to the object drug. The designs yielded similar estimates in most examples, with SCCS displaying better statistical efficiency. With both designs, results varied across sensitivity analyses, particularly in CCO analyses with small number of exposed individuals. Analyses in controls revealed substantial bias that may be differential across DDI-exposed and control individuals. Thus, both designs showed no association between amiodarone or verapamil and bleeding in dabigatran-exposed but revealed strong positive associations in controls. Overall, bias adjustment via a control group had a larger impact on results than the choice of a design, highlighting the importance and challenges of appropriate control group selection for adequate bias control in self-controlled analyses of DDIs.

Bioluminescence Measurement of Time-Dependent Dynamic Changes of CYP-Mediated Cytotoxicity in CYP-Expressing Luminescent HepG2 Cells

We sought to develop a cell-based cytotoxicity assay using human hepatocytes, which reflect the effects of drug-metabolizing enzymes on cytotoxicity. In this study, we generated luminescent human hepatoblastoma HepG2 cells using the mouse artificial chromosome vector, in which click beetle luciferase alone or luciferase and major drug-metabolizing enzymes (CYP2C9, CYP2C19, CYP2D6, and CYP3A4) are expressed, and monitored the time-dependent changes of CYP-mediated cytotoxicity expression by bioluminescence measurement. Real-time bioluminescence measurement revealed that compared with CYP-non-expressing cells, the luminescence intensity of CYP-expressing cells rapidly decreased when the cells were treated with low concentrations of aflatoxin B1 or primaquine, which exhibits cytotoxicity in the presence of CYP3A4 or CYP2D6, respectively. Using kinetics data obtained by the real-time bioluminescence measurement, we estimated the time-dependent changes of 50% inhibitory concentration (IC₅₀) values in the aflatoxin B1- and primaquine-treated cell lines. The first IC₅₀ value was detected much earlier and at a lower concentration in primaquine-treated CYP-expressing HepG2 cells than in primaquine-treated CYP-non-expressing cells, and the decrease of IC₅₀ values was much faster in the former than the latter. Thus, we successfully monitored time- and concentration-dependent dynamic changes of CYP-mediated cytotoxicity expression in CYP-expressing luminescent HepG2 cells by means of real-time bioluminescence measurement.

Rabeprazole-amoxicillin dual therapy as first-line treatment for H pylori eradication in special patients: A retrospective, real-life study

BACKGROUND

The currently recommended quadruple regimens for Helicobacter pylori infection might not be appropriate for every patient, especially in elderly patients or those with multiple comorbidities.

OBJECTIVE

To evaluate the efficacy and safety of rabeprazole-amoxicillin dual therapy in H pylori-positive elderly patients or those with multiple comorbidities.

METHODS

From November 2013 to May 2017, the clinical data of H pylori-positive patients ≥60 years old or with multiple comorbidities were collected and reviewed. All patients were given rabeprazole 10 mg three times a day and amoxicillin 1000 mg thrice a day (RA dual therapy) for 14 days as first-line treatment. H pylori eradication was evaluated by ¹³ C-urea breath test 6 weeks after treatment. Adverse effects were recorded.

RESULTS

A total of 198 patients were enrolled, including 116 elderly patients and 82 patients with multiple comorbidities. Successful eradication was achieved in 90.9% (180/198, 95% CI: 86.1%-94.2%) patients. Adverse effects, which were mainly mild (referring to skin rash, abdominal pain, and diarrhea), occurred in 22 patients (22/198, 11.1%) and resolved spontaneously.

CONCLUSION

Dual therapy composed of rabeprazole and amoxicillin as a first-line treatment appears to be effective and safe for H pylori infection in elderly patients or those with multiple comorbidities. Additional studies are needed to optimize the regimen.