Comparative pharmacokinetic interaction profiles of pravastatin, simvastatin, and atorvastatin when coadministered with cytochrome P450 inhibitors

Transporter-Mediated Hepatic Uptake Plays an Important Role in the Pharmacokinetics and Drug-Drug Interactions of Montelukast

Montelukast, a leukotriene receptor antagonist commonly prescribed for treatment of asthma, is primarily metabolized by cytochrome P450 (CYP)2C8, and has been suggested as a probe substrate for investigating CYP2C8 activity in vivo. We evaluated the quantitative role of hepatic uptake transport in its pharmacokinetics and drug-drug interactions (DDIs). Montelukast was characterized with significant active uptake in human hepatocytes, and showed affinity towards organic anion transporting polypeptides (OATPs) in transfected cell systems. Single-dose rifampicin, an OATP inhibitor, decreased montelukast clearance in rats and monkeys. Clinical DDIs of montelukast were evaluated using physiologically based pharmacokinetic modeling; and simulation of the interactions with gemfibrozil-CYP2C8 and OATP1B1/1B3 inhibitor, clarithromycin-CYP3A and OATP1B1/1B3 inhibitor, and itraconazole-CYP3A inhibitor, implicated OATPs-CYP2C8-CYP2C8 interplay as the primary determinant of montelukast pharmacokinetics. In conclusion, hepatic uptake plays a key role in the pharmacokinetics of montelukast, which should be taken into account when interpreting clinical interactions.

Clinical Pharmacist Patient-Safety Initiative to Reduce Against-Label Prescribing of Statins With Cyclosporine

BACKGROUND

Against-label prescribing of statins with interacting drugs, such as cyclosporine, represents an important patient safety concern.

OBJECTIVE

To implement and evaluate the effectiveness of a clinical pharmacist patient-safety initiative to minimize against-label prescribing of statins with cyclosporine.

METHODS

Kaiser Permanente Colorado clinical pharmacists identified patients receiving both cyclosporine and against-label statin through prescription claims data. Academic detailing on this interaction was provided to health care providers. Clinical pharmacists collaborated with physicians to facilitate conversion to on-label statin. Conversion rates along with changes in low-density lipoprotein cholesterol (LDL-C) were assessed.

RESULTS

Of the 157 patients identified as taking cyclosporine, 48 were receiving concurrent statin therapy. Of these 48 patients, 33 (69%) were on an against-label statin regimen; 25 (76%) of these patients were converted to on-label statin. Overall, patients converted to on-label statin had a mean LDL-C prior to conversion of 82.9 (±26.4) mg/dL and mean LDL-C after conversion of 90.7 (±31.2) mg/dL ( P = 0.21). In all, 17 patients (68%) were switched to pravastatin 20 mg daily and 8 patients (32%) to rosuvastatin 5 mg daily. In patients converted to pravastatin 20 mg daily, the mean LDL-C was 13.5 mg/dL higher than prior to conversion ( P = 0.066). In patients converted to rosuvastatin 5 mg daily, the mean LDL-C was 3.8 mg/dL lower than prior to conversion ( P = 0.73).

CONCLUSION

Utilizing a patient-safety-centered approach, clinical pharmacists were able to reduce the number of patients on against-label statin with cyclosporine while maintaining a comparable level of LDL-C control.

Rational prescribing: the principles of drug selection

Prescribing is the most important tool used by physicians to cure illness, relieve symptoms and prevent future disease. It is also a complex intellectual task that requires formulation of an appropriate treatment regimen from the many thousands available, taking into account the infinite variation in the patients they encounter. Unfortunately, the selection of a medicine and dosage regimen is sometimes suboptimal, leading to poor patient outcomes (eg treatment failure, avoidable adverse reactions). This article will highlight some of the common prescribing errors and will develop a rational approach that includes making a diagnosis, estimating prognosis, establishing the goals of therapy, selecting the most appropriate treatment and monitoring the effects of the treatment.

Pediatric Statin Administration: Navigating a Frontier with Limited Data

Increasingly, children and adolescents with dyslipidemia qualify for pharmacologic intervention. As they are for adults, 3-hydroxy-3-methyl-glutaryl-coenzyme A reductase inhibitors (statins) are the mainstay of pediatric dyslipidemia treatment when lifestyle modifications have failed. Despite the overall success of these drugs, the magnitude of variability in dose-exposure-response profiles contributes to adverse events and treatment failure. In children, the cause of treatment failures remains unclear. This review describes the updated guidelines for screening and management of pediatric dyslipidemia and statin disposition pathway to assist the provider in recognizing scenarios where alterations in dosage may be warranted to meet patients' specific needs.

Pharmacokinetic Interactions Between Isavuconazole and the Drug Transporter Substrates Atorvastatin, Digoxin, Metformin, and Methotrexate in Healthy Subjects

This article summarizes 4 phase 1 trials that explored interactions between the novel, triazole antifungal isavuconazole and substrates of the drug transporters breast cancer resistance protein (BCRP), multidrug and toxin extrusion protein‐1 (MATE1), organic anion transporters 1/3 (OAT1/OAT3), organic anion‐transporting polypeptide 1B1 (OATP1B1), organic cation transporters 1/2 (OCT1/OCT2), and P‐glycoprotein (P‐gp). Healthy subjects received single doses of atorvastatin (20 mg; OATP1B1 and P‐gp substrate), digoxin (0.5 mg; P‐gp substrate), metformin (850 mg; OCT1, OCT2, and MATE1 substrate), or methotrexate (7.5 mg; BCRP, OAT1, and OAT3 substrate) in the presence and absence of clinical doses of isavuconazole (200 mg 3 times a day for 2 days; 200 mg once daily thereafter). Coadministration with isavuconazole increased mean area under the plasma concentration‐time curves (90% confidence interval) of atorvastatin, digoxin, and metformin to 137% (129, 145), 125% (117, 134),  and 152% (138, 168) and increased mean maximum plasma concentrations to 103% (88, 121), 133% (119, 149), and 123% (109, 140), respectively. Methotrexate parameters were unaffected by isavuconazole. There were no serious adverse events. These findings indicate that isavuconazole is a weak inhibitor of P‐gp, as well as OCT1, OCT2, MATE1, or a combination thereof but not of BCRP, OATP1B1, OAT1, or OAT3.

RHB-104 triple antibiotics combination in culture is bactericidal and should be effective for treatment of Crohn's disease associated with Mycobacterium paratuberculosis

BACKGROUND

Mycobacterium avium subspecies paratuberculosis (MAP) has been implicated as an etiological agent of Crohn's disease (CD), a debilitating chronic inflammatory bowel disease. Clarithromycin (CLA), clofazimine (CLO), rifabutin (RIF) and other antibiotics have been used individually or in combinations with other drugs to treat mycobacterial diseases including CD. The treatment has varied by regimen, dosage, and duration, resulting in conflicting outcomes and additional suffering to the patients. RHB-104, a drug formula with active ingredients composed of (63.3 %) CLA, (6.7 %) CLO, and (30 %) RIF, has been recently subjected to investigation in an FDA approved Phase III clinical trial to treat patients with moderate to severe CD. In this study, we determined the efficacy of RHB-104 active ingredients against MAP strains isolated from the blood, tissue, and milk of CD patients. Based on fluorescence quenching technology using the Bactec MGIT Para-TB medium, we determined the minimum inhibitory concentration (MIC) of CLA, CLO, RIF individually and in dual and triple combinations against 16 MAP clinical strains and 19 other mycobacteria.

RESULTS

The MIC of all drugs against 35 different mycobacteria ranged between 0.25-20 μg/mL. However, the MIC of RHB-104 active ingredients regimen was the lowest at 0.25-10 μg/mL compared to the MIC of the other drugs at 0.5-20 μg/mL. The components of RHB-104 active ingredients at their individual concentrations or in dual combinations were not effective against all microorganisms compared to the triple combinations at MIC level. The MIC of CLA-CLO, CLA-RIF, and CLO-RIF regimens ranged between 0.5-1.25 μg/mL compared to 0.25 μg/mL of bactericidal effect of the triple combination.

CONCLUSION

The data clearly demonstrated that lower concentrations of the triple combination of RHB-104 active ingredients provided synergistic anti-MAP growth activity compared to individual or dual combinations of the drugs. Consequently, this is favorable and should lead to tolerable dosage that is desirable for long-term treatment of CD and Mycobacterium avium complex disease.

Drug therapies for HIV-related metabolic disorders

INTRODUCTION

Human immunodeficiency virus (HIV) has become a chronic disease often associated with dyslipidaemia and insulin resistance. Combination antiretroviral therapy (cART) may contribute to metabolic disturbances, eventually leading to increased cardiovascular disease (CVR) in this population. Escalating interventions to decrease CVR include promoting a healthy lifestyle, such as quitting smoking, diet and regular exercise. If they do not achieve the goals, a change of cART should be considered, followed by or used concomitantly with the use of chemical therapies.

AREAS COVERED

The aim of this article is to review the available drug therapies for the treatment of metabolic disorders in HIV-infected patients and to examine their safety and effectiveness in this population. A review of the literature was conducted, highlighting the most relevant articles.

EXPERT OPINION

Switching strategies can be useful but its expected benefit is not high. Therefore, chemical intervention is often needed. Statins have been proven to reduce CVR in the general population and in HIV-infected patients. Simvastatin is contraindicated in patients treated with boosted PI due to interactions; atorvastatin is safe at submaximal dose and needs close monitoring, while pravastatin lacks lipid-lowering potency, and rosuvastatin and pitavastatin are safe. Ezetimibe and fibrates are also safe and effective in HIV-infected patients and can be used in combination with statins. The management of glucose homeostatic disorders in HIV-infected patients follows the same guidelines as in the general population. However, there are specific considerations with respect to the interactions of particular medications with cART. When drug therapy is needed, metformin is the first-line drug. Decisions regarding second- and third-line drugs should be carefully individualized.

Appropriate risk criteria for OATP inhibition at the drug discovery stage based on the clinical relevancy between OATP inhibitors and drug-induced adverse effect

DDI could be caused by the inhibition of OATP-mediated hepatic uptakes. The aim of this study is to set the risk criteria for the compounds that would cause DDI via OATP inhibition at the drug discovery stage. The IC₅₀ values of OATP inhibitors for human OATP-mediated atorvastatin uptake were evaluated in the expression system. In order to set the risk criteria for OATP inhibition, the relationship was clarified between OATP inhibitory effect and severe adverse effects of OATP substrates, rhabdomyolysis, hyperbilirubinemia and jaundice. Rhabdomyolysis would be caused in the atorvastatin AUC more than 9-fold of that at a minimum therapeutic dose. The atorvastatin AUC was 6- to 9-fold increased with the OATP inhibitors of which IC₅₀ values were ≤1 μmol/L. Hyperbilirubinemia and jaundice would be caused with the OATP inhibitors of which IC₅₀ values were ≤6 μmol/L. This investigation showed that the compounds with IC₅₀ of ≤1 μmol/L would have high risk for OATP-mediated DDI that would cause severe side effects. Before the detailed analysis based on the dosage, unbound fraction in blood and effective concentration to evaluate the clinical DDI potency, this criteria enable high throughput screening and optimize lead compounds at the drug discovery stage.

Drug safety of macrolide and quinolone antibiotics in a tertiary care hospital: administration of interacting co-medication and QT prolongation

PURPOSE

Some macrolide and quinolone antibiotics (MQABs) are associated with QT prolongation and life-threatening torsade de pointes (TdP) arrhythmia. MQAB may also inhibit cytochrome P450 isoenzymes and thereby cause pharmacokinetic drug interactions (DDIs). There is limited data on the frequency and management of such risks in clinical practice. We aimed to quantify co-administration of MQAB with interacting drugs and associated adverse drug reactions.

METHODS

We conducted an observational study within our pharmacoepidemiological database derived from electronic medical records of a tertiary care hospital. Among all users of MQAB associated with TdP, we determined the prevalence of additional QT-prolonging drugs and risk factors and identified contraindicated co-administrations of simvastatin, atorvastatin, or tizanidine. Electrocardiographic (ECG) monitoring and associated adverse events were validated in medical records.

RESULTS

Among 3444 administered courses of clarithromycin, erythromycin, azithromycin, ciprofloxacin, levofloxacin, or moxifloxacin, there were 1332 (38.7 %) with concomitant use of additional QT-prolonging drugs. Among those, we identified seven cases of drug-related QT prolongation, but 49.1 % had no ECG monitoring. Of all MQAB users, 547 (15.9 %) had hypokalemia. Forty-four MQAB users had contraindicated co-administrations of simvastatin, atorvastatin, or tizanidine and three of those related adverse drug reactions.

CONCLUSION

In the studied real-life setting, we found a considerable number of MQAB users with additional risk factors for TdP but no ECG monitoring. However, adverse drug reactions were rarely found, and costs vs. benefits of ECG monitoring have to be weighted. In contrast, avoidable risk factors and selected contraindicated pharmacokinetic interactions are clear targets for implementation as automated alerts in electronic prescribing systems.

Quantification of pravastatin acid, lactone and isomers in human plasma by UHPLC-MS/MS and its application to a pediatric pharmacokinetic study

An ultra high pressure liquid chromatography-tandem mass spectrometric (UHPLC-MS/MS) method for the simultaneous quantitation of pravastatin and major metabolites, 3'α-hydroxy-pravastatin, pravalactone and 3'α-hydroxy-pravalactone, in human plasma has been developed and validated. Aliquots of (100μL) plasma in EDTA were diluted in pH 4.5 (0.1M buffer) to stabilize the analytes and subjected to hydrophilic lipophilic balance (HLB) solid phase extraction on 96 well μelution plates. Extracted samples were evaporated to dryness and reconstituted in pH 4.5 buffer. Chromatographic separation was performed on a Cortecs™ C18 column (2.1×100mm, 1.8μm), using gradient elution with a blend of acetonitrile and 10mM methylammonium acetate buffer (pH 4.5) at a flow rate of 0.4mL/min. Mass spectrometric detection was performed using multiple reaction monitoring (MRM) switching between positive/negative electrospay ionization (ESI). Pravastatin, 3'α-hydroxy-pravastatin, and internal standards [(2)H3]-pravastatin, and [(2)H3]-3'α-hydroxy-pravastatin were monitored in negative ESI mode at ion transitions m/z 423.2→321.1 and 426.2→321.1, respectively. Positive ESI mode was used for the detection of pravalactone, 3'α-hydroxy-pravalactone, and internal standards [(2)H3]-pravalactone, and [(2)H3]-3'α-hydroxy-pravalactone at ion transitions m/z 438.2→183.1 and 441.2→269.1 respectively. The method was linear for all analytes in the concentration range 0.5-200nM with intra- and inter-day precisions (as relative standard deviation) of ≤5.2% and accuracy (as relative error) of ≤8.0% at all quality control levels. The method was successfully applied to the investigation of pharmacokinetic properties of pravastatin and its metabolites in children after an oral dose of 20-40mg.

Biochemistry of Statins

Cardiovascular disease (CVD) is the leading cause of morbidity and mortality worldwide. Elevated blood lipids may be a major risk factor for CVD. Due to consistent and robust association of higher low-density lipoprotein (LDL)-cholesterol levels with CVD across experimental and epidemiologic studies, therapeutic strategies to decrease risk have focused on LDL-cholesterol reduction as the primary goal. Current medication options for lipid-lowering therapy include statins, bile acid sequestrants, a cholesterol-absorption inhibitor, fibrates, nicotinic acid, and omega-3 fatty acids, which all have various mechanisms of action and pharmacokinetic properties. The most widely prescribed lipid-lowering agents are the HMG-CoA reductase inhibitors, or statins. Since their introduction in the 1980s, statins have emerged as the one of the best-selling medication classes to date, with numerous trials demonstrating powerful efficacy in preventing cardiovascular outcomes (Kapur and Musunuru, 2008 [1]). The statins are commonly used in the treatment of hypercholesterolemia and mixed hyperlipidemia. This chapter focuses on the biochemistry of statins including their structures, pharmacokinetics, and mechanism of actions as well as the potential adverse reactions linked to their clinical uses.

Evaluation of Ketoconazole and Its Alternative Clinical CYP3A4/5 Inhibitors as Inhibitors of Drug Transporters: The In Vitro Effects of Ketoconazole, Ritonavir, Clarithromycin, and Itraconazole on 13 Clinically-Relevant Drug Transporters

Ketoconazole is a potent CYP3A4/5 inhibitor and, until recently, recommended by the Food and Drug Administration (FDA) and the European Medicines Agency as a strong CYP3A4/5 inhibitor in clinical drug-drug interaction (DDI) studies. Ketoconazole sporadically causes liver injury or adrenal insufficiency. Because of this, the FDA and European Medicines Agency recommended suspension of ketoconazole use in DDI studies in 2013. The FDA specifically recommended use of clarithromycin or itraconazole as alternative strong CYP3A4/5 inhibitors in clinical DDI studies, but many investigators have also used ritonavir as an alternative. Although the effects of these clinical CYP3A4/5 inhibitors on other CYPs are largely established, reports on the effects on the broad range of drug transporter activities are sparse. In this study, the inhibitory effects of ketoconazole, clarithromycin, ritonavir, and itraconazole (and its CYP3A4-inhibitory metabolites, hydroxy-, keto-, and N-desalkyl itraconazole) toward 13 drug transporters (OATP1B1, OATP1B3, OAT1, OAT3, OCT1, OCT2, MATE1, MATE2-K, P-gp, BCRP, MRP2, MRP3, and BSEP) were systematically assessed in transporter-expressing HEK-293 cell lines or membrane vesicles. In vitro findings were translated into clinical context with the basic static model approaches outlined by the FDA in its 2012 draft guidance on DDIs. The results indicate that, like ketoconazole, the alternative clinical CYP3A4/5 inhibitors ritonavir, clarithromycin, and itraconazole each have unique transporter inhibition profiles. None of the alternatives to ketoconazole provided a clean inhibition profile toward the 13 drug transporters evaluated. The results provide guidance for the selection of clinical CYP3A4/5 inhibitors when transporters are potentially involved in a victim drug's pharmacokinetics.

Identification and Mechanistic Investigation of Drug-Drug Interactions Associated With Myopathy: A Translational Approach

Myopathy is a group of muscle diseases that can be induced or exacerbated by drug–drug interactions (DDIs). We sought to identify clinically important myopathic DDIs and elucidate their underlying mechanisms. Five DDIs were found to increase the risk of myopathy based on analysis of observational data from the Indiana Network of Patient Care. Loratadine interacted with simvastatin (relative risk 95% confidence interval [CI] = [1.39, 2.06]), alprazolam (1.50, 2.31), ropinirole (2.06, 5.00), and omeprazole (1.15, 1.38). Promethazine interacted with tegaserod (1.94, 4.64). In vitro investigation showed that these DDIs were unlikely to result from inhibition of drug metabolism by CYP450 enzymes or from inhibition of hepatic uptake via the membrane transporter OATP1B1/1B3. However, we did observe in vitro synergistic myotoxicity of simvastatin and desloratadine, suggesting a role in loratadine–simvastatin interaction. This interaction was epidemiologically confirmed (odds ratio 95% CI = [2.02, 3.65]) using the data from the US Food and Drug Administration Adverse Event Reporting System.

A population-based analysis of the risk of drug interaction between clarithromycin and statins for hospitalisation or death

Background

Clarithromycin, known as a potent inhibitor of the cytochrome P450 isoenzyme CYP3A, may increase the plasma concentration of statins metabolized by this pathway; therefore, increase the risk of interaction with statins in reference to pharmacokinetic studies. This study aimed to characterize whether the concomitant use of a statin with clarithromycin is associated with serious outcomes among adult persons.

Methods

Health claims data of adult persons in the Regional Sickness Fund of Burgenland, Austria, who filled a prescription for clarithromycin between July 1, 2009 and June 30, 2012 were reviewed retrospectively. We assumed that the risk of hospitalisation increases acutely with the indication for taking an antibiotic, whereas statin use can be considered a chronic exposure with a low constant effect on hospitalisation. When defining the population as persons taking clarithromycin and the use of statins as the exposure we could achieve a comparable effect in both groups from the acute condition on hospitalisation. Therefore, we defined exposed patients as those who had overlapping treatment with a statin and unexposed controls as those who had filled a prescription for clarithromycin without concomitant statin therapy. Outcome was defined as a composite of hospital admission or death within 30 days after starting clarithromycin. We used generalised linear regression to model an association between outcome and exposure to statins.

Results

Among 28,484 prescriptions of clarithromycin, 2317 persons were co-exposed to statins. Co-administration of CYP3A4 metabolized statins and clarithromycin was associated with a 2.11 fold increased risk of death or hospitalisation (95 % confidence interval [CI]: 1.79–2.48). This effect was explained by age, evidence of cardiovascular disease, diabetes mellitus and utilization of other antibiotics (multivariable adjusted risk ratio: 1.02, 95 % CI: 0.85–1.22). The sensitivity analyses did not change the significance of effect.

Conclusions

The risk for hospitalisation or death in persons receiving clarithromycin increases with age and cardiovascular disease but is not causally associated with statin-clarithromycine co-administration.

Electronic supplementary material

The online version of this article (doi:10.1186/s12944-015-0134-y) contains supplementary material, which is available to authorized users.

Consensus guidelines for optimising antifungal drug delivery and monitoring to avoid toxicity and improve outcomes in patients with haematological malignancy, 2014

Antifungal agents may be associated with significant toxicity or drug interactions leading to sub-therapeutic antifungal drug concentrations and poorer clinical outcomes for patients with haematological malignancy. These risks may be minimised by clinical assessment, laboratory monitoring, avoidance of particular drug combinations and dose modification. Specific measures, such as the optimal timing of oral drug administration in relation to meals, use of pre-hydration and electrolyte supplementation may also be required. Therapeutic drug monitoring (TDM) of antifungal agents is warranted, especially where non-compliance, non-linear pharmacokinetics, inadequate absorption, a narrow therapeutic window, suspected drug interaction or unexpected toxicity are encountered. Recommended indications for voriconazole and posaconazole TDM in the clinical management of haematology patients are provided. With emerging knowledge regarding the impact of pharmacogenomics upon metabolism of azole agents (particularly voriconazole), potential applications of pharmacogenomic evaluation to clinical practice are proposed.

Physiologically based pharmacokinetic modeling of disposition and drug-drug interactions for atorvastatin and its metabolites

Atorvastatin is the most commonly used of all statins to lower cholesterol. Atorvastatin is extensively metabolized in both gut and liver to produce several active metabolites. The purpose of the present study is to develop a physiologically based pharmacokinetic (PBPK) model for atorvastatin and its two primary metabolites, 2-hydroxy-atorvastatin acid and atorvastatin lactone, using in vitro and in vivo data. The model was used to predict the pharmacokinetic profiles and drug-drug interaction (DDI) effect for atorvastatin and its metabolites in different DDI scenarios. The predictive performance of the model was assessed by comparing predicted results to observed data after coadministration of atorvastatin with different medications such as itraconazole, clarithromycin, cimetidine, rifampin and phenytoin. This population based PBPK model was able to describe the concentration-time profiles of atorvastatin and its two metabolites reasonably well in the absence or presence of those drugs at different dose regimens. The predicted maximum concentration (Cmax), area under the concentration-time curve (AUC) values and between-phase ratios were in good agreement with clinically observed data. The model has also revealed the importance of different metabolic pathways on the disposition of atorvastatin metabolites. This PBPK model can be utilized to assess the safety and efficacy of atorvastatin in the clinic. This study demonstrated the feasibility of applying PBPK approach to predict the DDI potential of drugs undergoing complex metabolism.

Drug-drug interactions that interfere with statin metabolism

INTRODUCTION

Lipid-lowering drugs, especially hydroxymethylglutaryl-CoA reductase inhibitors (statins), are widely used in the treatment and prevention of atherosclerotic diseases. The benefits of statins are well documented. However, myotoxic side effects, which can sometimes be severe, including myopathy or rhabdomyolysis, have been associated with the use of statins. In some cases, this toxicity is associated with pharmacokinetic alterations. Potent inhibitors of CYP 3A4 significantly increase plasma concentrations of the active forms of simvastatin, lovastatin and atorvastatin. Fluvastatin is metabolized by CYP2C9, while pravastatin, rosuvastatin and pitavastatin are not susceptible to inhibition by any CYP.

AREAS COVERED

This review discusses the pharmacokinetic aspects of the drug-drug interaction with statins and genetic polymorphisms in CYPs, which are involved in the metabolism of statins, and highlights the importance of establishing a system utilizing electronic medical information practically to avoid adverse drug reactions.

EXPERT OPINION

An understanding of the mechanisms underlying statin interactions will help to minimize drug interactions and develop statins that are less prone to adverse interactions. Quantitatively analyzed information for the low-density lipoprotein cholesterol lowering effects of statin based on electronic medical records may be useful for avoiding the adverse effect of statins.

Co-medication of statins with contraindicated drugs

Background

The concomitant use of cytochrome P450 3A4 (CYP3A4) metabolized statins (simvastatin, lovastatin, and atorvastatin) with CYP3A4 inhibitors has been shown to increase the rate of adverse events.

Objective

This study was performed to describe the co-medication prevalence of CYP3A4-metabolized statins with contraindicated drugs.

Methods

The patients aged 40 or older receiving CYP3A4-metabolized statin prescriptions in 2009 were identified using the national patient sample from a Korea Health Insurance Review and Assessment Service database. Contraindicated co-medication was defined as prescription periods of statins and contraindicated drugs overlapping by at least one day. Co-medication patterns were classified into 3 categories as follows: co-medication in the same prescription, co-medication by the same medical institution, and co-medication by different medical institutions. The proportion of co-medication was analyzed by age, gender, co-morbidities, and the statin’s generic name.

Results

A total of 2,119,401 patients received CYP3A4-metabolized statins and 60,254 (2.84%) patients were co-medicated with contraindicated drugs. The proportion of co-medication was 4.6%, 2.2%, and 1.8% in simvastatin, lovastatin, and atorvastatin users, respectively. The most frequent combination was atorvastatin-itraconazole, followed by simvastatin-clarithromycin and simvastatin-itraconazole. Among the co-medicated patients, 85.3% were prescribed two drugs by different medical institutions.

Conclusion

The proportion of co-medication of statins with contraindicated drugs was relatively lower than that of previous studies; however, the co-medication occurring by different medical institutions was not managed appropriately. There is a need to develop an effective system and to conduct outcomes research confirming the association between co-medication and the risk of unfavorable clinical outcomes.

Clarithromycin substantially increases steady-state bosentan exposure in healthy volunteers

AIMS

The aim of this study was to assess the effect of the cytochrome P450 (CYP) 3A4 and organic anion-transporting polypeptide (OATP) 1B1 inhibitor clarithromycin on the pharmacokinetics of bosentan. We also aimed to evaluate the impact of CYP2C9 and SLCO1B1 (encoding for OATP1B1) genotypes and their combination.

METHODS

We assessed the effect of the OATP and CYP3A inhibitor clarithromycin on bosentan pharmacokinetics at steady state and concurrently quantified changes of CYP3A activity using midazolam as a probe drug. Sixteen healthy volunteers received therapeutic doses of bosentan (125 mg twice daily) for 14 days and clarithromycin (500 mg twice daily) concomitantly for the last 4 days, and bosentan pharmacokinetics was assessed on days 1, 10 and 14.

RESULTS

Clarithromycin significantly increased bosentan area under the plasma concentration-time curve of the dosing interval 3.7-fold and peak concentration 3.8-fold in all participants irrespective of the genotype. Clarithromycin also reduced CYP3A activity (midazolam clearance) in all participants; however, these changes were not correlated to the changes of bosentan clearance.

CONCLUSIONS

Clarithromycin substantially increases the exposure to bosentan, suggesting that dose reductions may be necessary.

Absence of a significant pharmacokinetic interaction between atorvastatin and fenofibrate: a randomized, crossover, study of a fixed-dose formulation in healthy Mexican subjects

Several clinical trials have substantiated the efficacy of the co-administration of statins like atorvastatin (ATO) and fibrates. Without information currently available about the interaction between the two drugs, a pharmacokinetic study was conducted to investigate the effect when both drugs were co-administered. The purpose of this study was to investigate the pharmacokinetic profile of tablets containing ATO 20 mg, or the combination of ATO 20 mg with fenofibrate (FNO) 160 mg administered to healthy Mexican volunteers. This was a randomized, two-period, two-sequence, crossover study; 36 eligible subjects aged between 20-50 years were included. Blood samples were collected up to 96 h after dosing, and pharmacokinetic parameters were obtained by non-compartmental analysis. Adverse events were evaluated based on subject interviews and physical examinations. Area under the concentration-time curve (AUC) and maximum plasma drug concentration (Cmax) were measured for ATO as the reference and ATO and FNO as the test product for bioequivalence design. The estimation computed (90% confidence intervals) for ATO and FNO combination versus ATO for Cmax, AUC0-t and AUC0-∞, were 102,09, 125,95, and 120,97%, respectively. These results suggest that ATO and FNO have no relevant clinical-pharmacokinetic drug interaction.

A pharmacokinetic drug-drug interaction model of simvastatin and verapamil in humans

BACKGROUND

Verapamil is a calcium channel blocker commonly used in treatments of hypertension. Verapamil and its active metabolite, norverapamil, are known to be CYP3A4 inhibitors. Co-administration of verapamil with CYP3A4 substrates can alter the pharmacokinetics of the substrates. Simvastatin, a commonly used HMG-CoA reductase inhibitor for the treatment of hypercholesterolemia is extensively metabolized by CYP3A4. Therefore, concomitant use of simvastatin and verapamil can increase simvastatin plasma concentration levels, resulting in a higher risk of rhabdomyolysis, a serious adverse drug reaction. Even though, pharmacokinetic data regarding the interaction between both drugs have been published, their use is limited to semiquantitative applications. Therefore, we aimed to develop a mathematical model describing drug-drug interaction between simvastatin and verapamil in humans.

METHODS

Eligible pharmacokinetic interaction study between simvastatin and verapamil in humans was selected from PubMed database. The concentration-time courses from this study were digitally extracted and used for model development.

RESULTS

The drug-drug interaction between simvastatin and verapamil was modeled simultaneously with a two compartment model for verapamil with its active metabolite, norverapamil and a one compartment model for simvastatin with its active form, simvastatin hydroxy acid. The effects of verapamil and norverapamil on pharmacokinetics of simvastatin and its active form, simvastatin hydroxy acid were described by Michaelis-Menten equation. Simulated simvastatin and simvastatin hydroxy acid concentrations obtained from the final model produced a good fit to the dataset from a literature. The final model adequately describes pharmacokinetic interaction between simvastatin and verapamil which can be helpful in prediction of rhabdomyolysis in patients with concurrent use of these drugs.

A pharmacokinetic drug-drug interaction model of simvastatin and clarithromycin in humans

BACKGROUND

Simvastatin is a HMG-CoA reductase Inhibitor and a substrate of CYP3A4. Clarithromycin is a commonly used macrolide antibiotics and a potent inhibitor of CYP3A4. When co-administered with simvastatin, clarithromycin can significantly increase simvastatin plasma concentration levels, thereby, increase the risk of rhabdomyolysis. At present, pharmacokinetic data of the interaction between both drugs are available. However, they are being used for semi-quantitative application only, not for quantitative prediction. We aimed to develop a mathematical model describing a drug-drug interaction between simvastatin and clarithromycin in humans.

METHODS

Selected pharmacokinetic interaction study was obtained from PubMed search. Concentration-time course data were subsequently extracted and used for model development. Compartmental pharmacokinetic interaction model was developed using Advanced Continuous Simulating Language Extreme (ACSLX), a FORTRAN language-based computer program.

RESULTS

The drug-drug interaction between simvastatin and clarithromycin was modeled simultaneously with a parent-metabolite model for clarithromycin and a one-compartment model for simvastatin linked to its active form, simvastatin hydroxy acid. The simulated simvastatin concentrations obtained from the final model displayed satisfactory goodness of fit to the data from the literature.

CONCLUSION

Our model could successfully describe concentration-time course of simvastatin-clarithromycin interaction. The resulting interaction model can be able to use for further development of a quantitative model predicting rhabdomyolysis occurrence in patients concurrently receiving simvastatin and clarithromycin.

Managing dyslipidemia in HIV/AIDS patients: challenges and solutions

Human immunodeficiency virus (HIV) is a chronic disease associated with dyslipidemia and insulin resistance. In addition, the administration of combination antiretroviral therapy is associated with an increase in the incidence of metabolic risk factors (insulin resistance, lipoatrophy, dyslipidemia, and abnormalities of fat distribution in HIV patients). HIV dyslipidemia is a common problem, and associated with an increase in incidence of cardiovascular disease. Further challenges in the management of HIV dyslipidemia are the presence of diabetes and metabolic syndrome, nonalcoholic fatty liver disease, hypothyroidism, chronic kidney disease, the risk of diabetes associated with statin administration, age and ethnicity, and early menopause in females. Dyslipidemia in patients with HIV is different from the normal population, due to the fact that HIV increases insulin resistance and HIV treatment not only may induce dyslipidemia but also may interact with lipid-lowering medication. The use of all statins (apart from simvastatin and lovastatin) is safe and effective in HIV dyslipidemia, and the addition of ezetimibe, fenofibrate, fish oil, and niacin can be used in statin-unresponsive HIV dyslipidemia. The management of dyslipidemia and cardiovascular disease risks associated with HIV is complex, and a certain number of patients may require management in specialist clinics run by specialist physicians in lipid disorders. Future research is needed to address best strategies in the management of hyperlipidemia with HIV infection.

Development and Application of a Mechanistic Pharmacokinetic Model for Simvastatin and its Active Metabolite Simvastatin Acid Using an Integrated Population PBPK Approach

PURPOSE

To develop a population physiologically-based pharmacokinetic (PBPK) model for simvastatin (SV) and its active metabolite, simvastatin acid (SVA), that allows extrapolation and prediction of their concentration profiles in liver (efficacy) and muscle (toxicity).

METHODS

SV/SVA plasma concentrations (34 healthy volunteers) were simultaneously analysed with NONMEM 7.2. The implemented mechanistic model has a complex compartmental structure allowing inter-conversion between SV and SVA in different tissues. Prior information for model parameters was extracted from different sources to construct appropriate prior distributions that support parameter estimation. The model was employed to provide predictions regarding the effects of a range of clinically important conditions on the SV and SVA disposition.

RESULTS

The developed model offered a very good description of the available plasma SV/SVA data. It was also able to describe previously observed effects of an OATP1B1 polymorphism (c.521 T > C) and a range of drug-drug interactions (CYP inhibition) on SV/SVA plasma concentrations. The predicted SV/SVA liver and muscle tissue concentrations were in agreement with the clinically observed efficacy and toxicity outcomes of the investigated conditions.

CONCLUSIONS

A mechanistically sound SV/SVA population model with clinical applications (e.g., assessment of drug-drug interaction and myopathy risk) was developed, illustrating the advantages of an integrated population PBPK approach.

A Neuromuscular Approach to Statin-Related Myotoxicity

Approximately 95% of statin-treated patients tolerate this form of cholesterol management without any adverse effects. However, given their efficacy in reducing low density lipoproteins and cardiovascular events large numbers of patients are selected for statin therapy. Therefore muscle complications are, in fact, quite common. Limited understanding of the underlying pathophysiology has hampered physicians' ability to identify patients at risk for developing statin myotoxicity. A growing number of published case reports/series have implicated statins in the exacerbation of both acquired and genetic myopathies. A clinical management algorithm is presented which outlines a variety of co-morbidities which can potentiate the adverse effects of statins on muscle. In addition, a rational approach to the selection of those patients most likely to benefit from skeletal muscle biopsy is discussed. Ongoing work will define the extent to which statin-intolerant patients represent carriers of recessive metabolic myopathies or pre-symptomatic acquired myopathies. The expanding importance of pharmacogenomics will undoubtedly be realized in the field of statin myopathy research within the next few years. Such critical information is needed to establish more definitive management and diagnostic strategies.

Pharmacokinetic non-interaction analysis in a fixed-dose formulation in combination of atorvastatin and ezetimibe

Recent clinical research has shown that atorvastatin (ATO) in combination with cholesterol absorption inhibitor ezetimibe (EZE) significantly reduces LDL-C level in patients with hypercholesterolemia, showing a superior lipid-lowering efficacy compared to statin alone. With no information currently available on the interaction between the two drugs, a pharmacokinetic study was conducted to investigate the influence of EZE on ATO and conversely when the two drugs were coadministered. The purpose of this study was to investigate the presence of differences in the pharmacokinetic profiles of capsules containing ATO 80 mg, EZE 10 mg or the combination of both 80/10 mg administered to healthy Mexican volunteers. This was a randomized, three-period, six-sequences crossover study. 36 eligible subjects aged between 20 to 50 years were included. Blood samples were collected up to 96 h after dosing, and pharmacokinetic parameters were obtained by non-compartmental analysis. Adverse events were evaluated based on subject interviews and physical examinations. Area under the concentration-time curve (AUC) and maximum plasma drug concentration (C_max) were measured for each drug alone or together and tested for bioequivalence-based hypothesis. The estimation computed (90% confidence intervals) for AUC and C_max, were 96.04% (85.88–107.42%) and 97.04% (82.36–114.35%), respectively for ATO–EZE combination versus ATO alone, while 84.42% (77.19–92.32%) and 95.60% (82.43–110.88%), respectively, for ATO–EZE combination versus EZE alone were estimated. These results suggest that ATO and EZE have no relevant pharmacokinetic drug–drug interaction.

Avoiding patient morbidity: Updated statin drug interactions and risks for patient harm

Almost 50% of serious adverse events with statin therapy are attributed to unfavorable drug-drug combinations. This article reviews updated FDA warnings on capping the dose of simvastatin, recent package insert labeling changes of particular statins that address combinations with potent cytochrome P450 inhibitors, and current renal dosing recommendations for statins.

Pravastatin sodium

Pravastatin sodium is an [HMG-CoA] reductase inhibitor and is a lipid-regulating drug. This monograph includes the description of the drug: nomenclature, formulae, elemental composition, solubility, appearance, and partition coefficient. The uses and the methods that have been reported for the synthesis of this drug are described. The physical methods that were used to characterize the drug are the X-ray powder diffraction pattern, thermal methods, melting point, and differential scanning calorimetry. This chapter also contains the following spectra of the drug: the ultraviolet spectrum, the vibrational spectrum, the nuclear magnetic resonance spectra, and the mass spectrum. The compendial methods of analysis include the British Pharmacopoeia and the United States Pharmacopoeia methods. Other methods of analysis that are included in this profile are spectrophotometric, electrochemical, polarographic, voltammetric and chromatographic, and immunoassay methods. The chapter also contains the pharmacokinetics, metabolism, stability, and articles that reviewed pravastatin sodium manufacturing, characterization, and analysis. One hundred and sixty-two references are listed at the end of this comprehensive profile.

Biological products for the treatment of psoriasis: therapeutic targets, pharmacodynamics and disease-drug-drug interaction implications

Psoriasis is a chronic inflammatory skin disease condition that involves altered expression of a broad spectrum of proinflammatory cytokines which are associated with activation of T cells and proliferation of keratinocytes. Currently approved biological products for psoriasis treatment fall into two main classes: cytokine modulators and biologics targeting T cells. In psoriatic patients, elevated levels of proinflammatory cytokines are observed. Elevated proinflammatory cytokines can suppress some cytochrome P450 (CYP) enzymes, and the treatment of psoriasis with biological products can reduce proinflammatory cytokine levels. Therefore, the exposure of CYP substrate drugs is anticipated to be affected by the psoriasis disease resulting in a higher exposure than in healthy state (named disease-drug interaction) as well as by the biological treatments due to disease improvements resulting in a decrease in exposure (named disease-drug-drug interaction, disease-DDI). However, the quantitative impact on CYP substrate exposure due to disease or due to treatment with biological products remains to be evaluated. The objective of the current review is to provide an overview of the therapeutic targets and cytokine-related pharmacodynamic effects of biological products in psoriasis treatment with a particular focus on their implications for disease-DDI. The clinical study design considerations for psoriasis disease-DDI evaluation are also discussed.

[Rhabdomyolysis and severe hepatotoxicity due to a drug-drug interaction between ritonavir and simvastatin. Could we use the most cost-effective statin in all human immunodeficiency virus-infected patients?]

INTRODUCTION

Drugs like statins may induce rhabdomyolysis. Simvastatin and lovastatin have a high hepatic metabolism and their potential toxicity could be increased by interactions with other drugs that reduce their metabolism.

PATIENTS AND METHODS

A case-report is presented of an HIV-infected patient treated with antiretroviral drugs who developed a rhabdomyolysis-induced renal failure and liver toxicity when simvastatin was substituted for atorvastatin. A literature review is also presented.

RESULTS

The patient required hospital admission and showed a favorable response after hydration and urine alkalinization. There were 4 additional cases published of which there was one death.

CONCLUSIONS

Drug-drug interactions can increase the risk of statin induced rhabdomyolysis. In order to evaluate them properly, physicians at all levels of clinical care should be aware of all drugs prescribed to their patients and the contraindicated combinations.

Pharmacokinetic drug-drug interactions between 1,4-dihydropyridine calcium channel blockers and statins: factors determining interaction strength and relevant clinical risk management

Background

Coadministration of 1,4-dihydropyridine calcium channel blockers (DHP-CCBs) with statins (or 3-hydroxy-3-methylglutaryl-coenzyme A [HMG-CoA] reductase inhibitors) is common for patients with hypercholesterolemia and hypertension. To reduce the risk of myopathy, in 2011, the US Food and Drug Administration (FDA) Drug Safety Communication set a new dose limitation for simvastatin, for patients taking simvastatin concomitantly with amlodipine. However, there is no such dose limitation for atorvastatin for patients receiving amlodipine. The combination pill formulation of amlodipine/atorvastatin is available on the market. There been no systematic review of the pharmacokinetic drug–drug interaction (DDI) profile of DHP-CCBs with statins, the underlying mechanisms for DDIs of different degree, or the corresponding management of clinical risk.

Methods

The relevant literature was identified by performing a PubMed search, covering the period from January 1987 to September 2013. Studies in the field of drug metabolism and pharmacokinetics that described DDIs between DHP-CCB and statin or that directly compared the degree of DDIs associated with cytochrome P450 (CYP)3A4-metabolized statins or DHP-CCBs were included. The full text of each article was critically reviewed, and data interpretation was performed.

Results

There were three circumstances related to pharmacokinetic DDIs in the combined use of DHP-CCB and statin: 1) statin is comedicated as the precipitant drug (pravastatin–nimodipine and lovastatin–nicardipine); 2) statin is comedicated as the object drug (isradipine–lovastatin, lacidipine–simvastatin, amlodipine–simvastatin, benidipine-simvastatin, azelnidipine– simvastatin, lercanidipine–simvastatin, and amlodipine–atorvastatin); and 3) mutual interactions (lercanidipine–fluvastatin). Simvastatin has an extensive first-pass effect in the intestinal wall, whereas atorvastatin has a smaller intestinal first-pass effect. The interaction with simvastatin seems mainly driven by CYP3A4 inhibition at the intestinal level, whereas the interaction with atorvastatin is more due to hepatic CYP3A4 inhibition. The interaction of CYP3A4 inhibitor with simvastatin has been more pronounced compared with atorvastatin. From the current data, atorvastatin seems to be a safer CYP3A4-statin for comedication with DHP-CCB. There is no convincing evidence that amlodipine is an unusual DHP-CCB, either as a precipitant drug or as an object drug, from the perspective of CYP3A4-mediated drug metabolism. Amlodipine may have interactions with CYP3A5 in addition to CYP3A4, which may explain its particular characteristics in comparison with other DHP-CCBs. The degree of DDIs between the DHP-CCB and statin and the clinical outcome depends on many factors, such as the kind of statin, physicochemical proprieties of the DHP-CCB, the dose of either the precipitant drug or the object drug, the sex of the patient (eg, isradipine–lovastatin), route of drug administration (eg, oral versus intravenous nicardipine–lovastatin), the administration schedule (eg, nonconcurrent dosing method versus concurrent dosing method), and the pharmacogenetic status (eg, CYP3A5-nonexpressers versus CYP3A5-expressers).

Conclusion

Clinical professionals should enhance risk management regarding the combination use of two classes of drugs by increasing their awareness of the potential changes in therapeutic efficacy and adverse drug reactions, by rationally prescribing alternatives, by paying attention to dose adjustment and the administration schedule, and by review of the appropriateness of physician orders. Further study is needed – the DDIs between DHP-CCBs and statins have not all been studied in humans, from either a pharmacokinetic or a clinical perspective; also, the strength of the different pharmacokinetic interactions of DHP-CCBs with statins should be addressed by systematic investigations.

Cytochrome P450 and ischemic heart disease: current concepts and future directions

INTRODUCTION

The P450 enzymes (P450s) mediate the biotransformation of several drugs, steroid hormones, eicosanoids, cholesterol, vitamins, fatty acids and bile acids, many of which affect cardiovascular homeostasis. Experimental studies have demonstrated that several P450s modulate important steps in the pathogenesis of ischemic heart disease (IHD).

AREAS COVERED

This article discusses the current knowledge on i) the expression of P450s in cardiovascular and renal tissues; ii) the role of P450s in the pathophysiology of IHD, in particular the modulation of blood pressure and cardiac hypertrophy, coronary arterial tone, ischemia-reperfusion injury and the metabolism of cardiovascular drugs; iii) the available evidence from observational studies on the association between P450 gene polymorphisms and risk of myocardial infarction (MI); and iv) suggestions for further research in this area.

EXPERT OPINION

P450s exert important modulatory effects in experimental models of IHD and MI. However, observational studies have provided conflicting results on the association between P450 genetic polymorphisms and MI. Further, adequately powered studies are required to ascertain the biological and clinical impact of P450s on clinical IHD end-points, that is, fatal and nonfatal MI, revascularization and long-term outcomes post MI. Pharmacogenetic substudies of recently completed cardiovascular clinical trials might represent an alternative strategy in this context.

Lipid-lowering agents and hepatotoxicity

Lipid-lowering therapy is increasingly being used in patients for a variety of diseases, the most important being secondary prevention of cardiovascular disease. Many lipid-lowering drugs carry side effects that include elevations in hepatic function tests and liver toxicity. In many cases, these drugs are not prescribed or they are underprescribed because of fears of injury to the liver. This article attempts to review key trials with respect to the hepatotoxicity of these drugs. Recommendations are also provided with respect to the selection of low-risk patients and strategies to lower the risk of hepatotoxicity when prescribing these medications.

Drug interactions with statins

The 3-hydroxy-3-methylglutaryl coenzyme A (HMG-CoA) reductase inhibitors (statins) are generally well tolerated as monotherapy. Statins are associated with two important adverse effects, asymptomatic elevation in liver enzymes and myopathy. Myopathy is most likely to occur when statins are administered with other drugs. Statins are substrates of multiple drug transporters (including OAT- -P1B1, BCRP and MDR1) and several cytochrome P450 (CYP) enzymes (including CYP3A4, CYP2C8, CYP2C19, and CYP2C9). Possible adverse effects of statins can occur due to interactions in concomitant use of drugs that substantially inhibit or induce their methabolic pathway. This review summarizes the most important interactions of statins.

Adherence to drug label recommendations for avoiding drug interactions causing statin-induced myopathy--a nationwide register study

PURPOSE

To investigate the extent to which clinicians avoid well-established drug-drug interactions that cause statin-induced myopathy. We hypothesised that clinicians would avoid combining erythromycin or verapamil/diltiazem respectively with atorvastatin or simvastatin. In patients with statin-fibrate combination therapy, we hypothesised that gemfibrozil was avoided to the preference of bezafibrate or fenofibrate. When combined with verapamil/diltiazem or fibrates, we hypothesized that the dispensed doses of atorvastatin/simvastatin would be decreased.

METHODS

Cross-sectional analysis of nationwide dispensing data. Odds ratios of interacting erythromycin, verapamil/diltiazem versus respective prevalence of comparator drugs doxycycline, amlodipine/felodipine in patients co-dispensed interacting statins simvastatin/atorvastatin versus patients unexposed (pravastatin/fluvastatin/rosuvastatin) was calculated. For fibrates, OR of gemfibrozil versus fenofibrate/bezafibrate in patients co-dispensed any statin was assessed.

RESULTS

OR of interacting erythromycin versus comparator doxycycline did not differ between patients on interacting and comparator statins either in patients dispensed high or low statin doses (adjusted OR 0.87; 95% CI 0.60-1.25 and 0.92; 95% CI 0.69-1.23). Interacting statins were less common among patients dispensed verapamil/diltiazem as compared to patients on amlodipine/felodipine (OR high dose 0.62; CI 0.56-0.68 and low dose 0.63; CI 0.58-0.68). Patients on any statin were to a lesser extent dispensed gemfibrozil compared to patients not dispensed a statin (OR high dose 0.65; CI 0.55-0.76 and low dose 0.70; CI 0.63-0.78). Mean DDD (SD) for any statin was substantially higher in patients co-dispensed gemfibrozil 178 (149) compared to patients on statin monotherapy 127 (93), (p<0.001).

CONCLUSIONS

Prescribers may to some extent avoid co-prescription of statins with calcium blockers and fibrates with an increased risk of myopathy. We found no evidence for avoiding co-prescriptions of statins and antibiotics with an increased risk of statin-induced adverse drug reactions. Co-prescription of statins and gemfibrozil is paradoxically associated with a marked increased statin dose, further aggravating the risk for severe myopathy.

Simvastatin inhibits smoke-induced airway epithelial injury: implications for COPD therapy

Chronic obstructive pulmonary disease (COPD) is the third leading cause of death. The statin drugs may have therapeutic potential in respiratory diseases such as COPD, but whether they prevent bronchial epithelial injury is unknown. We hypothesised that simvastatin attenuates acute tobacco smoke-induced neutrophilic lung inflammation and airway epithelial injury. Spontaneously hypertensive rats were given simvastatin (20 mg·kg(-1) i.p.) daily for either 7 days prior to tobacco smoke exposure and during 3 days of smoke exposure, or only during tobacco smoke exposure. Pretreatment with simvastatin prior to and continued throughout smoke exposure reduced the total influx of leukocytes, neutrophils and macrophages into the lung and airways. Simvastatin attenuated tobacco smoke-induced cellular infiltration into lung parenchymal and airway subepithelial and interstitial spaces. 1 week of simvastatin pretreatment almost completely prevented smoke-induced denudation of the airway epithelial layer, while simvastatin given only concurrently with the smoke exposure had no effect. Simvastatin may be a novel adjunctive therapy for smoke-induced lung diseases, such as COPD. Given the need for statin pretreatment there may be a critical process of conditioning that is necessary for statins' anti-inflammatory effects. Future work is needed to elucidate the mechanisms of this statin protective effect.

A semi-physiologically-based pharmacokinetic model characterizing mechanism-based auto-inhibition to predict stereoselective pharmacokinetics of verapamil and its metabolite norverapamil in human

Verapamil and its major metabolite norverapamil were identified to be both mechanism-based inhibitors and substrates of CYP3A and reported to have non-linear pharmacokinetics in clinic. Metabolic clearances of verapamil and norverapmil as well as their effects on CYP3A activity were firstly measured in pooled human liver microsomes. The results showed that S-isomers were more preferential to be metabolized than R-isomers for both verapamil and norverapamil, and their inhibitory effects on CYP3A activity were also stereoselective with S-isomers more potent than R-isomers. A semi-physiologically based pharmacokinetic model (semi-PBPK) characterizing mechanism-based auto-inhibition was developed to predict the stereoselective pharmacokinetic profiles of verapamil and norverapamil following single or multiple oral doses. Good simulation was obtained, which indicated that the developed semi-PBPK model can simultaneously predict pharmacokinetic profiles of S-verapamil, R-verapamil, S-norverapamil and R-norverapamil. Contributions of auto-inhibition to verapamil and norverapamil accumulation were also investigated following the 38th oral dose of verapamil sustained-release tablet (240mg once daily). The predicted accumulation ratio was about 1.3-1.5 fold, which was close to the observed data of 1.4-2.1-fold. Finally, the developed semi-PBPK model was further applied to predict drug-drug interactions (DDI) between verapamil and other three CYP3A substrates including midazolam, simvastatin, and cyclosporine A. Successful prediction was also obtained, which indicated that the developed semi-PBPK model incorporating auto-inhibition also showed great advantage on DDI prediction with CYP3A substrates.

Transporters and drug-drug interactions: important determinants of drug disposition and effects

Uptake and efflux transporters determine plasma and tissue concentrations of a broad variety of drugs. They are localized in organs such as small intestine, liver, and kidney, which are critical for drug absorption and elimination. Moreover, they can be found in important blood-tissue barriers such as the blood-brain barrier. Inhibition or induction of drug transporters by coadministered drugs can alter pharmacokinetics and pharmacodynamics of the victim drugs. This review will summarize in particular clinically observed drug-drug interactions attributable to inhibition or induction of intestinal export transporters [P-glycoprotein (P-gp), breast cancer resistance protein (BCRP)], to inhibition of hepatic uptake transporters [organic anion transporting polypeptides (OATPs)], or to inhibition of transporter-mediated [organic anion transporters (OATs), organic cation transporter 2 (OCT2), multidrug and toxin extrusion proteins (MATEs), P-gp] renal secretion of xenobiotics. Available data on the impact of nutrition on transport processes as well as genotype-dependent, transporter-mediated drug-drug interactions will be discussed. We will also present and discuss data on the variable extent to which information on the impact of transporters on drug disposition is included in summaries of product characteristics of selected countries (SPCs). Further work is required regarding a better understanding of the role of the drug metabolism-drug transport interplay for drug-drug interactions and on the extrapolation of in vitro findings to the in vivo (human) situation.

How to avoid statin hepatotoxicity in patients with obesity and liver disease? Focus on the combination of ursodeoxycholic acid and atorvastatin

Obese patients demonstrate the combination of dyslipidemia (DLP) and elevated transaminase levels, as a manifestation of non-alcohol fatty liver disease (NAFLD). Therefore, statins should be administered with care in this clinical group. In the real-world clinical practice, obese patients with high cardiovascular risk and concomitant NAFLD often receive low, inadequately effective doses of statins, due to the fear of their adverse effects on the hepatic function. An alternative method of DLP treatment is a combination of statins with ursodeoxycholic acid (UDCA). The need for a long-term combination treatment with statins and UDCA stresses the importance of the problem of drug interaction and the mechanisms of drug metabolism. Even high doses of atorvastatin are safe and well tolerated. The most severe adverse effects – myopathy and rhabdomyolysis – are very rare. Currently, there is no available evidence of adverse clinical effects of the combination of UDCA and atorvastatin. Presented results emphasise the need for a wider use of new therapeutic strategies in patients with DLP, obesity, and NAFLD. The combination of UDCA and statins is safe and effective. It facilitates not only the achievement of target lipid levels, but also the improvement in the hepatic function.

Importance of multi-p450 inhibition in drug-drug interactions: evaluation of incidence, inhibition magnitude, and prediction from in vitro data

Drugs that are mainly cleared by a single enzyme are considered more sensitive to drug-drug interactions (DDIs) than drugs cleared by multiple pathways. However, whether this is true when a drug cleared by multiple pathways is coadministered with an inhibitor of multiple P450 enzymes (multi-P450 inhibition) is not known. Mathematically, simultaneous equipotent inhibition of two elimination pathways that each contribute half of the drug clearance is equal to equipotent inhibition of a single pathway that clears the drug. However, simultaneous strong or moderate inhibition of two pathways by a single inhibitor is perceived as an unlikely scenario. The aim of this study was (i) to identify P450 inhibitors currently in clinical use that can inhibit more than one clearance pathway of an object drug in vivo and (ii) to evaluate the magnitude and predictability of DDIs caused by these multi-P450 inhibitors. Multi-P450 inhibitors were identified using the Metabolism and Transport Drug Interaction Database. A total of 38 multi-P450 inhibitors, defined as inhibitors that increased the AUC or decreased the clearance of probes of two or more P450s, were identified. Seventeen (45%) multi-P450 inhibitors were strong inhibitors of at least one P450, and an additional 12 (32%) were moderate inhibitors of one or more P450s. Only one inhibitor (fluvoxamine) was a strong inhibitor of more than one enzyme. Fifteen of the multi-P450 inhibitors also inhibit drug transporters in vivo, but such data are lacking on many of the inhibitors. Inhibition of multiple P450 enzymes by a single inhibitor resulted in significant (>2-fold) clinical DDIs with drugs that are cleared by multiple pathways such as imipramine and diazepam, while strong P450 inhibitors resulted in only weak DDIs with these object drugs. The magnitude of the DDIs between multi-P450 inhibitors and diazepam, imipramine, and omeprazole could be predicted using in vitro data with similar accuracy as probe substrate studies with the same inhibitors. The results of this study suggest that inhibition of multiple clearance pathways in vivo is clinically relevant, and the risk of DDIs with object drugs may be best evaluated in studies using multi-P450 inhibitors.