Atorvastatin glucuronidation is minimally and nonselectively inhibited by the fibrates gemfibrozil, fenofibrate, and fenofibric acid

SLCO1B1 Genetic Variation Influence on Atorvastatin Systemic Exposure in Pediatric Hypercholesterolemia

This clinical study examined the influence of SLCO1B1 c.521T>C (rs4149056) on plasma atorvastatin concentrations in pediatric hypercholesterolemia. The participants (8-21 years), including heterozygous (c.521T/C, n = 13), homozygous (c.521C/C, n = 2) and controls (c.521T/T, n = 13), completed a single-oral-dose pharmacokinetic study. Similar to in adults, the atorvastatin (AVA) area-under-concentration-time curve from 0 to 24 h (AUC0-24) was 1.7-fold and 2.8-fold higher in participants with c.521T/C and c.521C/C compared to the c.521T/T participants, respectively. The inter-individual variability in AVA exposure within these genotype groups ranged from 2.3 to 4.8-fold, indicating that additional factors contribute to the inter-individual variability in the AVA dose-exposure relationship. A multivariate model reinforced the SLCO1B1 c.521T>C variant as the central factor contributing to AVA systemic exposure in this pediatric cohort, accounting for ~65% of the variability in AVA AUC0-24. Furthermore, lower AVA lactone concentrations in participants with increased body mass index contributed to higher exposure within the c.521T/T and c.521T/C genotype groups. Collectively, these factors contributing to higher systemic exposure could increase the risk of toxicity and should be accounted for when individualizing the dosing of atorvastatin in eligible pediatric patients.

Drug-drug-gene interactions as mediators of adverse drug reactions to diclofenac and statins: a case report and literature review

Concomitant treatment with drugs that inhibit drug metabolising enzymes and/or transporters, such as commonly prescribed statins and nonsteroidal anti-inflammatory drugs (NSAIDs), has been associated with prolonged drug exposure and increased risk of adverse drug reactions (ADRs) due to drug-drug interactions. The risk is further increased in patients with chronic diseases/comorbidities who are more susceptible because of their genetic setup or external factors. In that light, we present a case of a 46-year-old woman who had been experiencing acute renal and hepatic injury and myalgia over two years of concomitant treatment with diclofenac, atorvastatin, simvastatin/fenofibrate, and several other drugs, including pantoprazole and furosemide. Our pharmacogenomic findings supported the suspicion that ADRs, most notably the multi-organ toxicity experienced by our patient, may be owed to drug-drug-gene interactions and increased bioavailability of the prescribed drugs due to slower detoxification capacity and decreased hepatic and renal elimination. We also discuss the importance of CYP polymorphisms in the biotransformation of endogenous substrates such as arachidonic acid and their modulating role in pathophysiological processes. Yet even though the risks of ADRs related to the above mentioned drugs are substantially evidenced in literature, pre-emptive pharmacogenetic analysis has not yet found its way into common clinical practice.

The Role of Structure and Biophysical Properties in the Pleiotropic Effects of Statins

Statins are a class of drugs used to lower low-density lipoprotein cholesterol and are amongst the most prescribed medications worldwide. Most statins work as a competitive inhibitor of 3-hydroxy-3-methyl-glutaryl-coenzyme A reductase (HMGR), but statin intolerance from pleiotropic effects have been proposed to arise from non-specific binding due to poor enzyme-ligand sensitivity. Yet, research into the physicochemical properties of statins, and their interactions with off-target sites, has not progressed much over the past few decades. Here, we present a concise perspective on the role of statins in lowering serum cholesterol levels, and how their reported interactions with phospholipid membranes offer a crucial insight into the mechanism of some of the more commonly observed pleiotropic effects of statin administration. Lipophilicity, which governs hepatoselectivity, is directly related to the molecular structure of statins, which dictates interaction with and transport through membranes. The structure of statins is therefore a clinically important consideration in the treatment of hypercholesterolaemia. This review integrates the recent biophysical studies of statins with the literature on the physiological effects and provides new insights into the mechanistic cause of statin pleiotropy, and prospective means of understanding the cholesterol-independent effects of statins.

Imbalance of Drug Transporter-CYP450s Interplay by Diabetes and Its Clinical Significance

The pharmacokinetics of a drug is dependent upon the coordinate work of influx transporters, enzymes and efflux transporters (i.e., transporter-enzyme interplay). The transporter-enzyme interplay may occur in liver, kidney and intestine. The influx transporters involving drug transport are organic anion transporting polypeptides (OATPs), peptide transporters (PepTs), organic anion transporters (OATs), monocarboxylate transporters (MCTs) and organic cation transporters (OCTs). The efflux transporters are P-glycoprotein (P-gp), multidrug/toxin extrusions (MATEs), multidrug resistance-associated proteins (MRPs) and breast cancer resistance protein (BCRP). The enzymes related to drug metabolism are mainly cytochrome P450 enzymes (CYP450s) and UDP-glucuronosyltransferases (UGTs). Accumulating evidence has demonstrated that diabetes alters the expression and functions of CYP450s and transporters in a different manner, disordering the transporter-enzyme interplay, in turn affecting the pharmacokinetics of some drugs. We aimed to focus on (1) the imbalance of transporter-CYP450 interplay in the liver, intestine and kidney due to altered expressions of influx transporters (OATPs, OCTs, OATs, PepTs and MCT6), efflux transporters (P-gp, BCRP and MRP2) and CYP450s (CYP3As, CYP1A2, CYP2E1 and CYP2Cs) under diabetic status; (2) the net contributions of these alterations in the expression and functions of transporters and CYP450s to drug disposition, therapeutic efficacy and drug toxicity; (3) application of a physiologically-based pharmacokinetic model in transporter-enzyme interplay.

Simultaneous analysis of the total plasma concentration of atorvastatin and its five metabolites and the unbound plasma concentration of atorvastatin: Application in a clinical pharmacokinetic study of single oral dose

Atorvastatin (ATV) and its two active metabolites, o-hydroxy atorvastatin acid (o-OH-ATV) and p-hydroxy atorvastatin acid (p-OH-ATV) are responsible for its HMG-CoA (3-hydroxy-3-methylglutaryl-coenzyme-A) reductase inhibitory activity, while its corresponding inactive lactone forms (LAC) are related to the manifestation of myopathy. The present study reports the development and validation of a method for the simultaneous analysis of ATV and its five metabolites (o-OH-ATV, p-OH-ATV, ATV-LAC, o-OH-ATV-LAC, p-OH-ATV-LAC) as total plasma concentration and ATV as unbound plasma concentration using UPLC-MS/MS. The method was applied in a pharmacokinetic study following administration of a single oral 20, 40 or 80 mg ATV dose in healthy volunteers (n = 15). ATV and its five metabolites were separated on a C18 column using as mobile phase a mixture of 0.2% formic acid and acetonitrile (55:45, v/v) at a flow of 0.4 mL/min. The method showed linearity from 25 pg/mL to 200 ng/mL plasma as total concentration and from 6.25 pg to 25 ng/mL plasma ultrafiltrate as ATV unbound concentration. The coefficients of variation and the relative standard errors of the accuracy and precision analyses were <15%. The method allowed quantification of plasma concentrations of ATV and its five metabolites up to 36 h after 20, 40 or 80 mg ATV administration. The pharmacokinetic parameters dose normalized to 20 mg are presented as follow (n = 15, mean): unbound fraction 9.38%, maximum plasma concentration 9.52 ng/mL, time to reach maximum plasma concentration 0.98 h, apparent total clearance 742.90 L/h, apparent distribution volume 9005 L, and AUC metabolite/ATV ratios 0.06 for p-OH-ATV, 0.94 for o-OH-ATV, 1.43 for ATV-LAC, 0.25 for p-OH-ATV-LAC and 1.75 for o-OH-ATV-LAC. In conclusion, the methods for simultaneous analysis of ATV and its five metabolites as total plasma concentration and ATV as the unbound plasma concentration showed sensitivity, linearity, precision and accuracy compatible with application in pharmacokinetic studies of single oral dose of 20, 40 or 80 mg ATV.

Physiologically-Based Pharmacokinetic Modeling of Atorvastatin Incorporating Delayed Gastric Emptying and Acid-to-Lactone Conversion

The drug-drug interaction profile of atorvastatin confirms that disposition is determined by cytochrome P450 (CYP) 3A4 and organic anion transporting polypeptides (OATPs). Drugs that affect gastric emptying, including dulaglutide, also affect atorvastatin pharmacokinetics (PK). Atorvastatin is a carboxylic acid that exists in equilibrium with a lactone form in vivo. The purpose of this work was to assess gastric acid-mediated lactone equilibration of atorvastatin and incorporate this into a physiologically-based PK (PBPK) model to describe atorvastatin acid, lactone, and their major metabolites. In vitro acid-to-lactone conversion was assessed in simulated gastric fluid and included in the model. The PBPK model was verified with in vivo data including CYP3A4 and OATP inhibition studies. Altering the gastric acid-lactone equilibrium reproduced the change in atorvastatin PK observed with dulaglutide. The model emphasizes the need to include gastric acid-lactone conversion and all major atorvastatin-related species for the prediction of atorvastatin PK.

Effects of Silymarin on the In Vivo Pharmacokinetics of Simvastatin and Its Active Metabolite in Rats

Herein, the effect of silymarin pretreatment on the pharmacokinetics of simvastatin in rats was evaluated. To ensure the accuracy of the results, a rapid and sensitive UPLC-MS/MS method was established for simultaneous quantification of simvastatin (SV) and its active metabolite simvastatin acid (SVA). This method was applied for studying the pharmacokinetic interactions in rats after oral co-administration of silymarin (45 mg/kg) and different concentrations of SV. The major pharmacokinetic parameters, including Cmax, tmax, t_1/2, mean residence time (MRT), elimination rate constant (λz) and area under the concentration-time curve (AUC_0-12h), were calculated using the non-compartmental model. The results showed that the co-administration of silymarin and SV significantly increased the Cmax and AUC_0-12h of SVA compared with SV alone, while there was no significant difference with regards to Tmax and t_1/2. However, SV pharmacokinetic parameters were not significantly affected by silymarin pretreatment. Therefore, these changes indicated that drug-drug interactions may occur after co-administration of silymarin and SV.

Assessment of the Risk of Rhabdomyolysis and Myopathy During Concomitant Treatment with Ticagrelor and Statins

The introduction of ticagrelor, one of the first directly-acting oral antiplatelet drugs, provided new possibilities in the prevention of thrombotic events in patients with acute coronary syndromes (ACS). Current guidelines recommend ticagrelor in dual antiplatelet therapy with aspirin over clopidogrel for prevention of stent thrombosis in patients with ACS. Moreover, in the management of ACS, lipid-lowering treatment with high-intensity statin therapy is advised for secondary prevention of cardiovascular events over the long term. Despite the apparent advantages of combined antiplatelet and lipid-lowering treatments, a possible interaction between statins and ticagrelor may lead to myopathy and rhabdomyolysis. In this review, relevant information was gathered on the ticagrelor-statin interaction that might lead to this life-threatening condition. This review focuses on the most widely used statins—simvastatin, atorvastatin, and rosuvastatin. Possible mechanisms of this interaction are discussed, including CYP3A4 isoenzymes, organic anion transporter polypeptide (OATPs), P-glycoprotein and glucuronidation. PubMed database was searched for relevant case reports and all data gathered from the introduction of ticagrelor to March 2018 are presented and discussed. In summary, co-administration of statins and ticagrelor was found to be relatively safe in routinely prescribed doses. However, caution should be exercised, especially in elder populations.

Prediction of atorvastatin plasmatic concentrations in healthy volunteers using integrated pharmacogenetics sequencing

AIM

To use variants found by next-generation sequencing to predict atorvastatin plasmatic concentration profiles (AUC) in healthy volunteers.

SUBJECTS & METHODS

A total of 60 healthy Mexican volunteers were enrolled in this study. We used variants with a predicted functional effect across 20 genes involved in atorvastatin metabolism to construct a regression model using a support vector approach with a radial basis function kernel to predict AUC refining it afterwards in order to explain a greater extent of the variance.

RESULTS

The final support vector regression model using 60 variants (including six novel variants) explained 94.52% of the variance in atorvastatin AUC.

CONCLUSION

An integrated analysis of several genes known to intervene in the different steps of metabolism is required to predict atorvastatin's AUC.

Characterization of Statin-Associated Myopathy Case Reports in Thailand Using the Health Product Vigilance Center Database

BACKGROUND

HMG-CoA reductase inhibitors [statins], a widely prescribed cholesterol-lowering therapy, are associated with muscle-related adverse events. While characteristics of such events are well documented in Western countries, little data exists for the Thai population.

OBJECTIVE

The aim of this study was to determine the characteristics of patients, type and dosing of statin, and to identify patterns of drug use that may be associated with such adverse events using the national pharmacovigilance database known as Thai Vigibase.

METHOD

Muscle-related adverse events involving statins in the Thai Vigibase from 1996 to December 2009 were identified. For each report, the following information was extracted: patient demographics, co-morbidities, detailed information of adverse event, detailed information of suspected drug, treatment and outcome, as well as causality assessment and quality of reports. Descriptive statistics were performed for all study variables.

RESULTS

A total of 198 cases of statin-associated muscle-related adverse events were identified. Mean age was 61.4 ± 12.4 years of age and 59.6% were female. Simvastatin, atorvastatin, rosuvastatin and cerivastatin were implicated as the suspected drug in 163 (82.3%), 24 (12.1%), 10 (5.1%) and 1 (0.5%) cases, respectively. Rhabdomyolysis accounted for 55.6% of all muscle-related adverse events. Drug interactions known to enhance such toxicity of statins were identified in 40.9% of the total set of reports. Similar to studies from Western countries, fibrates, HIV protease inhibitors, non-dihydropyridine calcium channel blockers, azole antifungals and macrolides were commonly found in such cases. Interestingly, colchicine has been identified as the second most common drug interaction in our database. Case fatality rates were 0.9, 1.6 and 16.7%, when there were 0, 1 and ≥2 interacting drugs, respectively.

CONCLUSIONS

Characteristics of muscle-related adverse events with statins in the Thai population showed some similarities and differences compared with Western countries. Such similarities included advanced age, female sex, certain co-morbidities and drug interactions. While the majority of interacting drugs are well known, a big proportion of cases of statin-colchicine interaction attributed to long-term use of colchicine in Thailand was noted and should be further investigated. Based on these results, an attempt to avoid dangerous and well-known drug interactions among statin users should be implemented nationwide.

Atorvastatin attenuation of ABCB1 expression is mediated by microRNA miR-491-3p in Caco-2 cells

AIM

Atorvastatin, a HMG-CoA reductase inhibitor, used in the treatment of hypercholesterolemia, has been previously shown to regulate ABCB1 expression in vivo and in vitro. We hypothesized that the statin could regulate gene expression of ABCB1 transporter via microRNAs.

METHODS

Expression of microRNAs and ABCB1 mRNA was examined in atorvastatin-treated and control cells using real-time PCR. miR-491-3P mimic and inhibitor were transfected in Caco-2 and ABCB1 expression was monitored by western blot and real-time PCR.

RESULTS

In HepG2 cells, none of the microRNAs predicted to target ABCB1 3'UTR was regulated by atorvastatin treatment. In agreement with this, ABCB1 3'UTR activity was not modulated in HepG-2 cells after 48h-treatment as measured by luciferase assay. In Caco-2 cells, atorvastatin treatment provoked a decrease in luciferase activity and, accordingly, miR-491-3p was upregulated about 2.7 times after 48h-statin treatment. Luciferase analysis of miR-491-3p with a mimetic or inhibitor of miR-491-3p revealed that this microRNA could target ABCB1 3'UTR, as after miR-491-3p inhibition, ABCB1 levels were increased by two-fold, and miR-491-3p superexpression decreased ABCB1 3'UTR activity. Finally, functional analysis revealed that treatment with miR-491-3p inhibitor could reverses atorvastatin attenuation of ABCB1 (Pg-p) protein levels.

CONCLUSION

Our results suggest atorvastatin control ABCB1 expression via miR-491-3p in Caco-2 cells. This finding may be an important mechanism of statin drug-drug interaction, since common concomitant drugs used in the prevention of cardiovascular diseases are ABCB1 substrates.

ABCB1 polymorphism is associated with atorvastatin-induced liver injury in Japanese population

BACKGROUND

To investigate the associations between atorvastatin-induced liver injury (AILI) and polymorphisms in eight genes possibly involved in the hepatic metabolism (CYP2C9, CYP2C19, CYP3A4, CYP3A5 and UGT1A1) and membrane transport (ABCB1, ABCG2 and SLCO1B1) of atorvastatin, we genotyped 30 AILI and 414 non-AILI patients recruited at BioBank Japan for 15 single nucleotide polymorphisms (SNPs).

RESULTS

An SNP in ABCB1 (rs2032582: 2677G > T/A) was significantly associated with AILI (P = 0.00068, odds ratio (OR) = 2.59 with 95 % confidence interval (CI) of 1.49-4.50, G allele versus T and A alleles), indicating that the G allele might be a risk factor for AILI. The cytotoxicity test demonstrated that IC50 value of atorvastatin to inhibit the growth and/or viability of Flp-In-293/ABCB1 (2677G) cells was 5.44 ± 0.10 mM, which was significantly lower than those in Flp-In-293/ABCB1 (2677 T) (6.02 ± 0.07 mM) and Flp-In-293/ABCB1 (2677A) cells (5.95 ± 0.08 mM).

CONCLUSIONS

These results indicate that ABCB1 rs2032582 may predict the risk of AILI in Japanese population.

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.

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.

Modeling the effects of commonly used drugs on human metabolism

Metabolism contributes significantly to the pharmacokinetics and pharmacodynamics of a drug. In addition, diet and genetics have a profound effect on cellular metabolism with respect to both health and disease. In the present study, we assembled a comprehensive, literature-based drug metabolic reconstruction of the 18 most highly prescribed drug groups, including statins, anti-hypertensives, immunosuppressants and analgesics. This reconstruction captures in detail our current understanding of their absorption, intracellular distribution, metabolism and elimination. We combined this drug module with the most comprehensive reconstruction of human metabolism, Recon 2, yielding Recon2_DM1796, which accounts for 2803 metabolites and 8161 reactions. By defining 50 specific drug objectives that captured the overall drug metabolism of these compounds, we investigated the effects of dietary composition and inherited metabolic disorders on drug metabolism and drug-drug interactions. Our main findings include: (a) a shift in dietary patterns significantly affects statins and acetaminophen metabolism; (b) disturbed statin metabolism contributes to the clinical phenotype of mitochondrial energy disorders; and (c) the interaction between statins and cyclosporine can be explained by several common metabolic and transport pathways other than the previously established CYP3A4 connection. This work holds the potential for studying adverse drug reactions and designing patient-specific therapies.

Mechanisms and assessment of statin-related muscular adverse effects

Statin-associated muscular adverse effects cover a wide range of symptoms, including asymptomatic increase of creatine kinase serum activity and life-threatening rhabdomyolysis. Different underlying pathomechanisms have been proposed. However, a unifying concept of the pathogenesis of statin-related muscular adverse effects has not emerged so far. In this review, we attempt to categorize these mechanisms along three levels. Firstly, among pharmacokinetic factors, it has been shown for some statins that inhibition of cytochrome P450-mediated hepatic biotransformation and hepatic uptake by transporter proteins contribute to an increase of systemic statin concentrations. Secondly, at the myocyte membrane level, cell membrane uptake transporters affect intracellular statin concentrations. Thirdly, at the intracellular level, inhibition of the 3-hydroxy-3-methylglutaryl coenzyme A (HMG-CoA) reductase results in decreased intracellular concentrations of downstream metabolites (e.g. selenoproteins, ubiquinone, cholesterol) and alteration of gene expression (e.g. ryanodine receptor 3, glycine amidinotransferase). We also review current recommendations for prescribers.

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.

Evaluation of an In Silico PBPK Post-Bariatric Surgery Model through Simulating Oral Drug Bioavailability of Atorvastatin and Cyclosporine

An increasing prevalence of morbid obesity has led to dramatic increases in the number of bariatric surgeries performed. Altered gastrointestinal physiology following surgery can be associated with modified oral drug bioavailability (Foral). In the absence of clinical data, an indication of changes to Foral via systems pharmacology models would be of value in adjusting dose levels after surgery. A previously developed virtual "post-bariatric surgery" population was evaluated through mimicking clinical investigations on cyclosporine and atorvastatin after bariatric surgery. Cyclosporine simulations displayed a reduced fraction absorbed through gut wall (fa) and Foral after surgery, consistent with reported observations. Simulated atorvastatin Foral postsurgery was broadly reflective of observed data with indications of counteracting interplay between reduced fa and an increased fraction escaping gut wall metabolism (FG). Inability to fully recover observed atorvastatin exposure after biliopancreatic diversion with duodenal switch highlights the current gap regarding the knowledge of associated biological changes.CPT: Pharmacometrics & Systems Pharmacology (2013) 2, e47; doi:10.1038/psp.2013.23; advance online publication 12 June 2013.

Diabetes mellitus reduces the clearance of atorvastatin lactone: results of a population pharmacokinetic analysis in renal transplant recipients and in vitro studies using human liver microsomes

BACKGROUND AND OBJECTIVE

Patients with diabetes mellitus might be at a higher risk of HMG-CoA reductase inhibitor (statin)-induced myotoxicity, possibly because of reduced clearance of the statin lactone. The present study was designed to investigate the effect of diabetes on the biotransformation of atorvastatin acid, both in vivo in nondiabetic and diabetic renal transplant recipients, and in vitro in human liver samples from nondiabetic and diabetic donors.

SUBJECTS AND METHODS

A total of 312 plasma concentrations of atorvastatin acid and atorvastatin lactone, from 20 nondiabetic and 32 diabetic renal transplant recipients, were included in the analysis. Nonlinear mixed-effects modelling was employed to determine the population pharmacokinetic estimates for atorvastatin acid and atorvastatin lactone. In addition, the biotransformation of these compounds was studied using human liver microsomal fractions obtained from 12 nondiabetic and 12 diabetic donors.

RESULTS

In diabetic patients, the plasma concentration of atorvastatin lactone was significantly higher than that of atorvastatin acid throughout the 24-hour sampling period. The optimal population pharmacokinetic model for atorvastatin acid and atorvastatin lactone consisted of a two- and one-compartment model, respectively, with interconversion between atorvastatin acid and atorvastatin lactone. Parent drug was absorbed orally with a population estimate first-order absorption rate constant of 0.457 h(-1). The population estimates of apparent oral clearance (CL/F) of atorvastatin acid to atorvastatin lactone, intercompartmental clearance (Q/F), apparent central compartment volume of distribution after oral administration (V(1)/F) and apparent peripheral compartment volume of distribution after oral administration (V(2)/F) for atorvastatin acid were 231 L/h, 315 L/h, 325 L and 4910 L, respectively. The population estimates of apparent total clearance of atorvastatin lactone (CL(M)/F), apparent intercompartmental clearance of atorvastatin lactone (Q(M)/F) and apparent volume of distribution of atorvastatin lactone after oral administration (V(M)/F) were 85.4 L/h, 166 L/h and 249 L, respectively. The final covariate model indicated that the liver enzyme lactate dehydrogenase was related to CL/F and alanine aminotransferase (ALT) was related to Q/F. Importantly, diabetic patients have 3.56 times lower CL(M)/F than nondiabetic patients, indicating significantly lower clearance of atorvastatin lactone in these patients. Moreover, in a multivariate population pharmacokinetics model, diabetes status was the only significant covariate predicting the values of the CL(M)/F. Correspondingly, the concentration of atorvastatin acid remaining in the microsomal incubation was not significantly different between nondiabetic and diabetic liver samples, whereas the concentration of atorvastatin lactone was significantly higher in the samples from diabetic donors. In vitro studies, using recombinant enzymes, revealed that cytochrome P450 (CYP) 3A4 is the major CYP enzyme responsible for the biotransformation of atorvastatin lactone.

CONCLUSIONS

These studies provide compelling evidence that the clearance of atorvastatin lactone is significantly reduced by diabetes, which leads to an increased concentration of this metabolite. This finding can be clinically valuable for diabetic transplant recipients who have additional co-morbidities and are on multiple medications.

Understanding the critical disposition pathways of statins to assess drug-drug interaction risk during drug development: it's not just about OATP1B1

The use of statins is widespread across disease areas because many patients have comorbidities. Given that these drugs have become common as comedications, it is essential to have an understanding of the potential risks of drug-drug interactions (DDIs) between statins and candidate drugs in development. Although the hepatic uptake transporter organic anion-transporting polypeptide 1B1 (OATP1B1) is known to play a substantial role in statin-related DDI risk, other transporters and metabolizing enzymes can also be involved. Consequently, a holistic approach to risk assessment is required, tailored to each statin. Using evidence from pharmacogenetics, DDIs, and literature on absorption, distribution, metabolism, and elimination (ADME) in humans, this review identifies pathways that contribute the most to, and are therefore the most critical to, the disposition of each statin. It also provides an understanding of the expected theoretical maximum increase in systemic exposure if the disposition of a statin is inhibited. Finally, on a statin-by-statin basis, we propose in vitro inhibition studies that should be routinely conducted during drug development so as to better assess DDI risk.

Optimized assays for human UDP-glucuronosyltransferase (UGT) activities: altered alamethicin concentration and utility to screen for UGT inhibitors

The measurement of the effect of new chemical entities on human UDP-glucuronosyltransferase (UGT) marker activities using in vitro experimentation represents an important experimental approach in drug development to guide clinical drug-interaction study designs or support claims that no in vivo interaction will occur. Selective high-performance liquid chromatography-tandem mass spectrometry functional assays of authentic glucuronides for five major hepatic UGT probe substrates were developed: β-estradiol-3-glucuronide (UGT1A1), trifluoperazine-N-glucuronide (UGT1A4), 5-hydroxytryptophol-O-glucuronide (UGT1A6), propofol-O-glucuronide (UGT1A9), and zidovudine-5'-glucuronide (UGT2B7). High analytical sensitivity permitted characterization of enzyme kinetic parameters at low human liver microsomal and recombinant UGT protein concentration (0.025 mg/ml), which led to a new recommended optimal universal alamethicin activation concentration of 10 μg/ml for microsomes. Alamethicin was not required for recombinant UGT incubations. Apparent enzyme kinetic parameters, particularly for UGT1A1 and UGT1A4, were affected by nonspecific binding. Unbound intrinsic clearance for UGT1A9 and UGT2B7 increased significantly after addition of 2% bovine serum albumin, with minimal changes for UGT1A1, UGT1A4, and UGT1A6. Eleven potential UGT and cytochrome P450 inhibitors were evaluated as UGT inhibitors, resulting in observation of nonselective UGT inhibition by chrysin, mefenamic acid, silibinin, tangeretin, ketoconazole, itraconazole, ritonavir, and verapamil. The pan-cytochrome P450 inhibitor, 1-aminobenzotriazole, minimally inhibited UGT activities and may be useful in reaction phenotyping of mixed UGT and cytochrome P450 substrates. These methods should prove useful in the routine assessments of the potential for new drug candidates to elicit pharmacokinetic drug interactions via inhibition of human UGT activities and the identification of UGT enzyme-selective chemical inhibitors.

The effect of bexarotene on atorvastatin pharmacokinetics: results from a phase I trial of bexarotene plus chemotherapy in patients with advanced non-small cell lung cancer

PURPOSE

Bexarotene (Targretin(®) capsules) is a retinoid-X-receptor agonist and an inducer of CYP3A4-mediated metabolism. This phase I trial evaluated the pharmacokinetic (PK) and drug-drug interactions of bexarotene with chemotherapy and a lipid-lowering agent (atorvastatin or fenofibrate). This trial was run in parallel with phase III trials of the combinations to determine whether repeated doses of bexarotene capsules affect the pharmacokinetics (PK) of the chemotherapeutic or the lipid-lowering agents.

METHODS

Patients (n = 48) with advanced non-small cell lung cancer were treated with repetitive cycles of either paclitaxel/carboplatin or cisplatin/vinorelbine chemotherapy, bexarotene (400 mg/m(2)/day) administered continuously starting on day 4 of chemotherapy, and a lipid-lowering drug, either atorvastatin or fenofibrate, starting at least 5 days before chemotherapy due to hypertriglyceridemia induced by bexarotene. Extensive plasma sampling to characterize the PK profiles of the lipid-lowering drugs, relevant chemotherapy agents was performed on day 1 (without bexarotene) and during chemotherapy cycles 2 or 3 (with bexarotene).

RESULTS

Here, we report the drug-drug interactions between the lipid-lowering agents and bexarotene. Mean atorvastatin clearance and dose-corrected AUC values were reduced by nearly 50% with the addition of concomitant bexarotene. As fenofibrate was less effective at controlling hypertriglyceridemia, too few patients received this agent to make any meaningful conclusions about drug-drug interactions.

CONCLUSIONS

A drug-drug interaction was seen in this trial with bexarotene co-administration leading to a significant reduction in the AUC of atorvastatin. The likely mechanism for this interaction is through induction of CYP3A4 by bexarotene given the role of this enzyme in the metabolism of atorvastatin. Knowledge of this interaction is important for optimizing lipid management with atorvastatin for patients receiving bexarotene.

Paraoxonase (PON1 and PON3) Polymorphisms: Impact on Liver Expression and Atorvastatin-Lactone Hydrolysis

Atorvastatin δ-lactone, a major, pharmacologically inactive metabolite, has been associated with toxicity. In a previous study we showed that polymorphisms of UGT1A3 influence atorvastatin δ-lactone formation. Here we investigated the reverse reaction, atorvastatin δ-lactone hydrolysis, in a human liver bank. Screening of microarray data revealed paraoxonases PON1 and PON3 among 17 candidate esterases. Microsomal δ-lactone hydrolysis was significantly correlated to PON1 and PON3 protein (r(s) = 0.60; r(s) = 0.62, respectively; P < 0.0001). PON1 and PON3 were strongly correlated to each other (r(s) = 0.60) but PON1 was shown to be more extensively glycosylated than PON3. In addition a novel splice-variant of PON3 was identified. Genotyping of 40 polymorphisms within the PON-locus identified PON1 promoter polymorphisms (-108T > C, -832G > A, -1741G > A) and a tightly linked group of PON3 polymorphisms (-4984A > G, -4105G > A, -1091A > G, -746C > T, and F21F) to be associated with changes in atorvastatin δ-lactone hydrolysis and expression of PON1 but not PON3. However, carriers of the common PON1 polymorphisms L55M or Q192R showed no difference in δ-lactone hydrolysis or PON expression. Haplotype analysis revealed decreased δ-lactone hydrolysis in carriers of the most common haplotype *1 compared to carriers of haplotypes *2, *3, *4, and *7. Analysis of non-genetic factors showed association of hepatocellular and cholangiocellular carcinoma with decreased PON1 and PON3 expression, respectively. Increased C-reactive protein and γ-glutamyl transferase levels were associated with decreased protein expression of both enzymes, and increased bilirubin levels, cholestasis, and presurgical exposure to omeprazole or pantoprazole were related to decreased PON3 protein. In conclusion, PON-locus polymorphisms affect PON1 expression whereas non-genetic factors have an effect on PON1 and PON3 expression. This may influence response to therapy or adverse events in statin treatment.

A systems biology approach to dynamic modeling and inter-subject variability of statin pharmacokinetics in human hepatocytes

Background

The individual character of pharmacokinetics is of great importance in the risk assessment of new drug leads in pharmacological research. Amongst others, it is severely influenced by the properties and inter-individual variability of the enzymes and transporters of the drug detoxification system of the liver. Predicting individual drug biotransformation capacity requires quantitative and detailed models.

Results

In this contribution we present the de novo deterministic modeling of atorvastatin biotransformation based on comprehensive published knowledge on involved metabolic and transport pathways as well as physicochemical properties. The model was evaluated on primary human hepatocytes and parameter identifiability analysis was performed under multiple experimental constraints. Dynamic simulations of atorvastatin biotransformation considering the inter-individual variability of the two major involved enzymes CYP3A4 and UGT1A3 based on quantitative protein expression data in a large human liver bank (n = 150) highlighted the variability in the individual biotransformation profiles and therefore also points to the individuality of pharmacokinetics.

Conclusions

A dynamic model for the biotransformation of atorvastatin has been developed using quantitative metabolite measurements in primary human hepatocytes. The model comprises kinetics for transport processes and metabolic enzymes as well as population liver expression data allowing us to assess the impact of inter-individual variability of concentrations of key proteins. Application of computational tools for parameter sensitivity analysis enabled us to considerably improve the validity of the model and to create a consistent framework for precise computer-aided simulations in toxicology.

Statin-induced myopathy: a review and update

INTRODUCTION

Statin-induced myopathy is an important cause of statin intolerance and the most common cause of statin discontinuation. Observational studies estimate that 10 - 15% of statin users develop statin-related muscle side effects ranging from mild myalgia to more severe muscle symptoms with significant CPK elevations.

AREAS COVERED

This article reviews the epidemiology, clinical features, risk factors and mechanisms of statin-induced myopathy and provides an evidence-based algorithm for managing patients with statin myopathy.

EXPERT OPINION

There are multiple risk factors for statin-induced myopathy that are both patient-related (age, genetics, co-morbidities) and drug-related (statin metabolism via the CYP system, drug-drug interactions and statin drug transport). Management options for statin-intolerant patients include statin switching, especially to low-dose, non-daily doses of long-acting statins, such as rosuvastatin and atorvastatin, and other non-statin lipid-lowering agents, such as ezetimibe and colesevelam, and possibly red yeast rice. In conclusion, statin-induced myopathy is a significant clinical problem that contributes considerably to statin therapy discontinuation. However, there exist multiple and effective management options for statin intolerant patients.

Physiogenomic analysis of statin-treated patients: domain-specific counter effects within the ACACB gene on low-density lipoprotein cholesterol?

AIM

Administered at maximal dosages, the most common statins--atorvastatin, simvastatin and rosuvastatin--lower low-density lipoprotein cholesterol (LDLC) by an average of 37-57% in patients with primary hypercholesterolemia. We hypothesized novel genetic underpinnings for variation in LDLC levels in the context of statin therapy.

MATERIALS & METHODS

Genotyping of 384 SNPs in 202 volunteers from a lipid outpatient clinic was accomplished and LDLC levels obtained from chart records. The SNPs were distributed across 222 genes representing physiological pathways such as general metabolism, cholesterol biochemistry, cardiovascular function, inflammation, neurobiology and cell proliferation. We discovered significant associations with LDLC levels for the rs34274 SNP (p < 0.0002) and for rs2241220 (p < 0.008) in the acetyl-coenzyme A carboxylase beta (ACACB) gene. When corrected for multiple testing, the false-discovery rate associated with rs34274 was 0.076 (significance threshold: 0.10) and for rs2241220 the false-discovery rate was 0.93 (not significant). The acetyl coenzyme A carboxylase beta enzyme synthesizes malonyl coenzyme A, an essential substrate for hepatic fatty acid synthesis and an inhibitor of fatty acid oxidation.

RESULTS

The SNPs were in weak linkage disequilibrium (D = 0.302). Minor alleles at these sites demonstrate opposing influences on LDLC; the C>T substitution at rs34724 is a risk marker and the C>T substitution at rs2241220 a protective marker for LDLC levels. These SNPs hypothetically influence enzymatic activity through different mechanisms, rs34274 through the PII promoter and rs2241220 via alteration of the protein's responsiveness to allosteric influence.

CONCLUSION

Physiogenomic evidence suggests a novel link between LDLC levels and the regulation of fatty acid metabolism. The findings complement previously discovered novel SNP relationships to myalgia (pain) and myositis (serum creatine kinase activity). By genotyping for myositis, myalgia and LDLC levels, a physiogenomic model may be developed to help clinicians maximize effectiveness and minimize side effects in prescribing statins.

Aleglitazar, a balanced PPARα/γ agonist, has no clinically relevant pharmacokinetic interaction with high-dose atorvastatin or rosuvastatin

BACKGROUND

Aleglitazar, a dual PPAR-α/γ agonist, combines the lipid benefits of fibrates and the insulin-sensitizing benefits of thiazolidinediones.

OBJECTIVE

To investigate the pharmacokinetic effects of co-administration of atorvastatin or rosuvastatin with aleglitazar.

RESEARCH DESIGN AND METHODS

In a two-cohort, open-label, randomised, three-period crossover study, 44 healthy subjects received once-daily oral doses of aleglitazar 300 μg, statin (atorvastatin 80 mg or rosuvastatin 40 mg) and aleglitazar co-administered with each statin for 7 days. Plasma concentrations of each drug were measured and pharmacokinetic parameters determined on day 7 in each period.

MAIN OUTCOME MEASURES

Peak observed plasma concentration (C(max)) and total exposures (AUC(0 - 24)) of aleglitazar, atorvastatin and rosuvastatin.

RESULTS

C(max) and AUC(0 - 24) to aleglitazar were similar, whether administered alone or in combination with a statin. Total exposure to either statin was unaffected by co-administration with aleglitazar. C(max) treatment ratios for both statins exceeded the conventional no-effect boundary (1.25) when administered with aleglitazar.

CONCLUSIONS

Co-administration of aleglitazar with a statin does not alter the pharmacokinetic profile of either drug.

Management of dyslipidemias with fibrates, alone and in combination with statins: role of delayed-release fenofibric acid

Cardiovascular disease (CVD) represents the leading cause of mortality worldwide. Lifestyle modifications, along with low-density lipoprotein cholesterol (LDL-C) reduction, remain the highest priorities in CVD risk management. Among lipid-lowering agents, statins are most effective in LDL-C reduction and have demonstrated incremental benefits in CVD risk reduction. However, in light of the residual CVD risk, even after LDL-C targets are achieved, there is an unmet clinical need for additional measures. Fibrates are well known for their beneficial effects in triglycerides, high-density lipoprotein cholesterol (HDL-C), and LDL-C subspecies modulation. Fenofibrate is the most commonly used fibric acid derivative, exerts beneficial effects in several lipid and nonlipid parameters, and is considered the most suitable fibrate to combine with a statin. However, in clinical practice this combination raises concerns about safety. ABT-335 (fenofibric acid, Trilipix^®) is the newest formulation designed to overcome the drawbacks of older fibrates, particularly in terms of pharmacokinetic properties. It has been extensively evaluated both as monotherapy and in combination with atorvastatin, rosuvastatin, and simvastatin in a large number of patients with mixed dyslipidemia for up to 2 years and appears to be a safe and effective option in the management of dyslipidemia.

Nutritional status affects fluvastatin-induced hepatotoxicity and myopathy in rats

Rats that consumed a high-fat and high-sucrose diet (HF diet) developed hepatic steatosis. Treatment of HF diet-fed rats with fluvastatin (8 mg/kg) was lethal, followed by an elevation in levels of plasma aspartate aminotransferase and creatine kinase activities and skeletal muscle toxicity. This study was conducted to determine whether nutritional status affects statin-induced adverse effects in rats. Fluvastatin treatment of rats fed the HF diet led to an increase in systemic exposure, suggesting altered metabolism and elimination. In fact, although hepatic multidrug resistance-associated protein (Mrp) 2 and multidrug resistance (Mdr) 1b protein levels were not significantly changed by fluvastatin treatment for 8 days of rats fed a HF diet, the organic anion-transporting protein (Oatp) 1, Mrp3, CYP1A, CYP2C, UDP-glucuronosyltransferase (UGT) 1A1, and UGT1A5 protein levels were moderately decreased and the Oatp2, CYP3A, and UGT2B1 protein levels were markedly suppressed. No significant difference in the baseline level of Oatp1, Oatp2, Mrp2, Mrp3, Mdr1b, CYP1A, CYP2C, CYP3A, UGT1A1, UGT1A5, or UGT2B1 protein was found between the standard diet- and HF diet-fed groups. In addition, the mRNA levels of Oatp2, CYP2C11, and CYP3A1/2 were markedly decreased in HF diet-fed and fluvastatin-treated rats. There was no significant difference in the glucuronidation activities against fluvastatin among the four groups. In liver cell nuclei, levels of constitutive androstane receptor, pregnane X receptor, and hepatocyte nuclear factor 4α proteins were decreased in fluvastatin-treated HF diet-fed rats, which correlated with the decrease in Oatp2, CYP2C, and CYP3A. Taken together, these results indicate that nutritional status may influence adverse effects of fluvastatin by increasing systemic exposure through modulation of hepatic uptake and elimination.

Myopathy with statin-fibrate combination therapy: clinical considerations

Many patients who receive statin therapy for hyperlipidemia-such as patients with diabetes mellitus and metabolic syndrome--have residual cardiovascular risk. These patients often have dyslipidemia, including low levels of HDL cholesterol and elevated levels of triglycerides and small, dense LDL. For such patients, combination treatment with statins and fibrates is a potentially useful strategy to improve lipid and lipoprotein profiles and reduce cardiovascular risk. However, statin-fibrate combination regimens have potential adverse effects on skeletal muscle, including myopathy. To date, no large-scale, prospective, randomized, controlled trial has evaluated the safety and efficacy of statin-fibrate combination therapy; one such trial is underway but will not report data until 2010. Until then, clinicians need to consider pharmacokinetic, pharmacodynamic, metabolic, pathophysiologic and other factors that can increase the systemic exposure of statins and/or fibrates and hence heighten the risk of toxic effects on muscles, as well as data from clinical trials and recommendations of consensus panels to optimize the safety of such combination regimens. On the basis of currently available data, fenofibrate or fenofibric acid is the fibrate of choice when used in combination with a statin because each is, in theory, associated with a lower risk of myopathy than gemfibrozil.

Management of complex lipid abnormalities with a fixed dose combination of simvastatin and extended release niacin

ER niacin combined with simvastatin provides an additional option for achieving LDL-C and non-HDL-C goals for cardiovascular prevention, with greater efficacy in those with triglyceride levels >200 mg/dL. ER niacin 1000 mg combined with simvastatin 20 mg reduced LDL-C by 6%, non-HDL-C by 7%, and triglycerides by 13%, and raised HDL-C by 11% compared to simvastatin 20 mg alone. The 2000 mg dose combined with simvastatin 20 to 40 mg raised reduced LDL-C by 7% to 24%, non-HDL-C by 16% to 28%, and triglycerides by 23% to 34%, and increased HDL-C by 18% to 22% compared to similar dose simvastatin therapy. While cardiovascular risk is reduced in proportion to the magnitude of LDL-C lowering, the additive benefit of raising HDL-C and lowering triglycerides remains to be determined. ER niacin-simvastatin is reasonably well tolerated, with a <7% discontinuation rate due to flushing in patients who used aspirin or non-steroidal anti-inflammatory medications as needed. However, drop-out rates were high in both the simvastatin and ER niacin–simvastatin treatment groups in both the 24- and 52-week studies. The safety profile of the combination appears to be similar to that of niacin and simvastatin used as monotherapies. Results of ongoing morbidity/mortality trials of ER niacin added to statin therapy are eagerly awaited.

Managing statin myopathy

Approximately 10% of patients treated with statins experience some form of muscle-related side effects in clinical practice. These can range from asymptomatic creatine kinase (CK) elevation, to muscle pain, weakness, and its most severe form, rhabdomyolysis. Higher risk patients for statin myopathy are those older than 80, with a small body frame, on higher statin doses, on other medications, or with other systemic diseases including hepatic or renal diseases, diabetes mellitus, or hypothyroidism. The cause of statin myopathy is presumed to be the same for its variable presentation but has not been defined. In patients with myopathic symptoms, their symptoms and CK levels determine whether statin therapy can be continued or must be stopped.

Simvastatin: present and future perspectives

Simvastatin is lipophilic statin with a short half-life that is primarily metabolized by CYP450 3A4. At doses of 5 - 80 mg, simvastatin lowers LDL cholesterol by 25 - 50%. Simvastatin has been shown to reduce the risk of cardiovascular disease by 35% and overall mortality by up to 30% over 5 years. The recommended starting dose of simvastatin 40 mg is approved as a lipid-lowering agent and for all high-risk patients, including those with cardiovascular disease and diabetes, regardless of the baseline LDL level. Simvastatin dose should be adjusted in those receiving CYP3A4 inhibitors, gemfibrozil, or ciclosporin, amiodarone, or in those with severe renal insufficiency. Coformulation of simvastatin with ezetimibe is now available, and coformulation with extended release niacin is under development.

The UDP-Glucuronosyltransferase 2B7 Isozyme Is Responsible for Gemfibrozil Glucuronidation in the Human Liver

Gemfibrozil, a fibrate hypolipidemic agent, is eliminated in humans by glucuronidation. A gemfibrozil glucuronide has been reported to show time-dependent inhibition of cytochrome P450 2C8. Comprehensive assessment of the drug interaction between gemfibrozil and cytochrome P450 2C8 substrates requires a clear understanding of gemfibrozil glucuronidation. However, the primary UDP-glucuronosyltransferase (UGT) isozymes responsible for gemfibrozil glucuronidation remain to be determined. Here, we identified the main UGT isozymes involved in gemfibrozil glucuronidation. Evaluation of 12 recombinant human UGT isozymes shows gemfibrozil glucuronidation activity in UGT1A1, UGT1A3, UGT1A9, UGT2B4, UGT2B7, and UGT2B17, with UGT2B7 showing the highest activity. The kinetics of gemfibrozil glucuronidation in pooled human liver microsomes (HLMs) follows Michaelis-Menten kinetics with high and low affinity components. The high affinity K(m) value was 2.5 microM, which is similar to the K(m) value of gemfibrozil glucuronidation in recombinant UGT2B7 (2.2 microM). In 16 HLMs, a significant correlation was observed between gemfibrozil glucuronidation and both morphine 3-OH glucuronidation (r = 0.966, p < 0.0001) and flurbiprofen glucuronidation (r = 0.937, p < 0.0001), two reactions mainly catalyzed by UGT2B7, whereas no significant correlation was observed between gemfibrozil glucuronidation and either estradiol 3beta-glucuronidation and propofol glucuronidation, two reactions catalyzed by UGT1A1 and UGT1A9, respectively. Flurbiprofen and mefenamic acid inhibited gemfibrozil glucuronidation in HLMs with similar IC(50) values to those reported in recombinant UGT2B7. These results suggest that UGT2B7 is the main isozyme responsible for gemfibrozil glucuronidation in humans.