Drug-drug interactions between pemafibrate and statins on pharmacokinetics in healthy male volunteers: Open-label, randomized, 6-sequence, 3-period crossover studies.

Elevated triglyceride levels are associated with an increased risk of cardiovascular events despite guideline-based statin treatment of low-density lipoprotein cholesterol. Peroxisome proliferator-activated receptor α (PPARα) agonists exert a significant triglyceride-lowering effect. However, combination therapy of PPARα agonists with statins poses an increased risk of rhabdomyolysis, which is rare but a major concern of the combination therapy. Pharmacokinetic interaction is suspected to be a contributing factor to the risk. To examine the potential for combination therapy with the selective PPARα modulator (SPPARMα) pemafibrate and statins, drug-drug interaction studies were conducted with open-label, randomized, 6-sequence, 3-period crossover designs for the combination of pemafibrate 0.2 mg twice daily and each of 6 statins once daily: pitavastatin 4 mg/day (n = 18), atorvastatin 20 mg/day (n = 18), rosuvastatin 20 mg/day (n = 29), pravastatin 20 mg/day (n = 18), simvastatin 20 mg/day (n = 20), and fluvastatin 60 mg/day (n = 19), involving healthy male volunteers. The pharmacokinetic parameters of pemafibrate and each of the statins were similar regardless of coadministration. There was neither an effect on the systemic exposure of pemafibrate nor a clinically important increase in the systemic exposure of any of the statins on the coadministration although the systemic exposure of simvastatin was reduced by about 15% and its open acid form by about 60%. The HMG-CoA reductase inhibitory activity in plasma samples from the simvastatin and pemafibrate combination group was about 70% of that in the simvastatin alone group. In conclusion, pemafibrate did not increase the systemic exposure of statins, and vice versa, in healthy male volunteers.

Impact of OATP2B1 on Pharmacokinetics of Atorvastatin Investigated in rSlco2b1-Knockout and SLCO2B1-Knockin Rats.

The organic anion transporting polypeptide (OATP) 2B1 is considered an emerging drug transporter that is found expressed in pharmacokinetically relevant organs such as the liver, small intestine, and kidney. Despite its interaction with various substrate drugs, the understanding of its in vivo relevance is still limited. In this study, we first validated the interaction of atorvastatin with rat OATP2B1 using transiently transfected HeLa cells. Moreover, we characterized our rSlco2b1-knockout and SLCO2B1-knockin rats for mRNA, protein expression, and localization of OATP2B1 in the liver, small intestine, and kidney. The transporter showed the highest expression in the liver followed by the small intestine. In humanized rats, human OATP2B1 is localized on the sinusoidal membrane of hepatocytes. In enterocytes of wild-type and humanized rats, the transporter was detected in the luminal membrane with the vast majority being localized subapical. Subsequently, we assessed atorvastatin pharmacokinetics in male wild-type, rSlco2b1-knockout, and SLCO2B1-knockin rats after a single-dose administration (orally and intravenously). Investigating the contribution of rat OATP2B1 or human OATP2B1 to oral atorvastatin pharmacokinetics revealed no differences in concentration-time profiles or pharmacokinetic parameters. However, when comparing the pharmacokinetics of atorvastatin after intravenous administration in SLCO2B1-humanized rats and knockout animals, notable differences were observed. In particular, the systemic exposure (area under the curve) decreased by approximately 40% in humanized animals, whereas the clearance was 57% higher in animals expressing human OATP2B1. These findings indicate that human OATP2B1 influences pharmacokinetics of atorvastatin after intravenous administration, most likely by contributing to the hepatic uptake. SIGNIFICANCE STATEMENT: Wild-type, rSlco2b1-knockout, and SLCO2B1-humanized Wistar rats were characterized for the expression of rat and human SLCO2B1/OATP2B1. Pharmacokinetic studies of atorvastatin over 24 hours were conducted in male wild-type, rSlco2b1-knockout, and SLCO2B1-humanized rats. After a single-dose intravenous administration, a lower systemic exposure and an increase in clearance were observed in SLCO2B1-humanized rats compared with knockout animals indicating a contribution of OATP2B1 to the hepatic clearance.

Understanding the impact of ABCG2 polymorphisms on drug pharmacokinetics: focus on rosuvastatin and allopurinol.

INTRODUCTION: In addition to the well-established understanding of the pharmacogenetics of drug-metabolizing enzymes, there is growing data on the effects of genetic variation in drug transporters, particularly ATP-binding cassette (ABC) transporters. However, the evidence that these genetic variants can be used to predict drug effects and to adjust individual dosing to avoid adverse events is still limited. AREAS COVERED: This review presents a summary of the current literature from the PubMed database as of February 2024 regarding the impact of genetic variants on ABCG2 function and their relevance to the clinical use of the HMG-CoA reductase inhibitor rosuvastatin and the xanthine oxidase inhibitor allopurinol. EXPERT OPINION: Although there are pharmacogenetic guidelines for the ABCG2 missense variant Q141K, there is still some conflicting data regarding the clinical benefits of these recommendations. Some caution appears to be warranted in homozygous ABCG2 Q141K carriers when rosuvastatin is administered at higher doses and such information is already included in the drug label. The benefit of dose adaption to lower possible side effects needs to be evaluated in prospective clinical studies.

Physiologically based pharmacokinetics modeling and transporter proteomics to predict systemic and local liver and muscle disposition of statins.

Statins are used to reduce liver cholesterol levels but also carry a dose-related risk of skeletal muscle toxicity. Concentrations of statins in plasma are often used to assess efficacy and safety, but because statins are substrates of membrane transporters that are present in diverse tissues, local differences in intracellular tissue concentrations cannot be ruled out. Thus, plasma concentration may not be an adequate indicator of efficacy and toxicity. To bridge this gap, we used physiologically based pharmacokinetic (PBPK) modeling to predict intracellular concentrations of statins. Quantitative data on transporter clearance were scaled from in vitro to in vivo conditions by integrating targeted proteomics and transporter kinetics data. The developed PBPK models, informed by proteomics, suggested that organic anion-transporting polypeptide 2B1 (OATP2B1) and multidrug resistance-associated protein 1 (MRP1) play a pivotal role in the distribution of statins in muscle. Using these PBPK models, we were able to predict the impact of alterations in transporter function due to genotype or drug-drug interactions on statin systemic concentrations and exposure in liver and muscle. These results underscore the potential of proteomics-guided PBPK modeling to scale transporter clearance from in vitro data to real-world implications. It is important to evaluate the role of drug transporters when predicting tissue exposure associated with on- and off-target effects.

The pharmacokinetics of single-dose oral atorvastatin and its metabolites support therapeutic use in cockatiels (Nymphicus hollandicus).

OBJECTIVE: To evaluate the plasma concentrations and determine the pharmacokinetic parameters of atorvastatin and its primary active metabolites (para- and orthohydroxyatorvastatin) after administration of a single oral dose in cockatiels (Nymphicus hollandicus). ANIMALS: 14 adult cockatiels (7 male, 7 female) around 2 years of age. METHODS: A compounded oral suspension of atorvastatin 10 mg/mL made with an oral suspending agent and an oral sweetener was administered via oral gavage at 20 mg/kg to each bird. Blood samples were collected at 7 different time points from 0.5 to 24 hours postadministration in a balanced incomplete block design with 3 blood samples per bird and 6 replicates per time point. Plasma concentrations of atorvastatin, parahydroxyatorvastatin, and orthohydroxyatorvastatin were determined by liquid chromatography-tandem mass spectrometry. Pharmacokinetic analysis was performed using noncompartmental analysis. RESULTS: The estimated time to maximum concentration (tmax) for atorvastatin, parahydroxyatorvastatin, and orthohydroxyatorvastatin was 3 hours for each. The estimated maximum plasma concentration (Cmax) for atorvastatin, parahydroxyatorvastatin, and orthohydroxyatorvastatin was 152.6, 172.4, and 68.8 ng/mL, respectively. The terminal half-lives were 4, 6.8, and 4.6 hours, respectively. CLINICAL RELEVANCE: These results support the therapeutic use of atorvastatin at the dose evaluated in this species based on human pharmacokinetic data. A starting dose of 20 mg/kg PO every 12 to 24 hours could be used to treat lipid disorders in cockatiels pending more data on multidose use and hypolipidemic efficacy.

Pharmacokinetic and Safety Comparison of Fixed-Dose Combination of Cilostazol/Rosuvastatin (200 + 20 mg) Versus Concurrent Administration of the Separate Components in Healthy Adults.

The combined cilostazol and rosuvastatin therapy is frequently used for coronary artery disease treatment. This open-label, 3 × 3 crossover clinical trial evaluated the pharmacokinetics and safety of a fixed-dose combination (FDC) of cilostazol/rosuvastatin (200 + 20 mg) versus a concurrent administration of the separate components (SCs) under both fasted and fed conditions. Among 48 enrolled healthy adults, 38 completed the study. Participants were administered a single oral dose of cilostazol/rosuvastatin (200 + 20 mg), either as an FDC or SCs in a fasted state, or FDC in a fed state, in each period of the trial. Blood samples were taken up to 48 hours after dosing, and plasma concentrations were analyzed using validated liquid chromatography-tandem mass spectrometry. The geometric mean ratios of FDC to SCs for area under the plasma concentration-time curve from time zero to the last quantifiable concentration (AUClast) and maximum plasma concentration (Cmax) were 0.94/1.05 and 1.06/1.15 for cilostazol and rosuvastatin, respectively (AUClast/Cmax). Compared with that during fasting, fed-state administration increased the AUClast and Cmax for cilostazol by approximately 72% and 160% and decreased these parameters for rosuvastatin by approximately 39% and 43%, respectively. To conclude, the FDC is bioequivalent to the SCs, with notable differences in pharmacokinetics when administered in a fed state. No significant safety differences were observed between the treatments.

Genome-Wide Association Study of Atorvastatin Pharmacokinetics: Associations With SLCO1B1, UGT1A3, and LPP.

In a genome-wide association study of atorvastatin pharmacokinetics in 158 healthy volunteers, the SLCO1B1 c.521T>C (rs4149056) variant associated with increased area under the plasma concentration-time curve from time zero to infinity (AUC0-∞) of atorvastatin (P = 1.2 × 10-10), 2-hydroxy atorvastatin (P = 4.0 × 10-8), and 4-hydroxy atorvastatin (P = 2.9 × 10-8). An intronic LPP variant, rs1975991, associated with reduced atorvastatin lactone AUC0-∞ (P = 3.8 × 10-8). Three UGT1A variants linked with UGT1A3*2 associated with increased 2-hydroxy atorvastatin lactone AUC0-∞ (P = 3.9 × 10-8). Furthermore, a candidate gene analysis including 243 participants suggested that increased function SLCO1B1 variants and decreased activity CYP3A4 variants affect atorvastatin pharmacokinetics. Compared with individuals with normal function SLCO1B1 genotype, atorvastatin AUC0-∞ was 145% (90% confidence interval: 98-203%; P = 5.6 × 10-11) larger in individuals with poor function, 24% (9-41%; P = 0.0053) larger in those with decreased function, and 41% (16-59%; P = 0.016) smaller in those with highly increased function SLCO1B1 genotype. Individuals with intermediate metabolizer CYP3A4 genotype (CYP3A4*2 or CYP3A4*22 heterozygotes) had 33% (14-55%; P = 0.022) larger atorvastatin AUC0-∞ than those with normal metabolizer genotype. UGT1A3*2 heterozygotes had 16% (5-25%; P = 0.017) smaller and LPP rs1975991 homozygotes had 34% (22-44%; P = 4.8 × 10-5) smaller atorvastatin AUC0-∞ than noncarriers. These data demonstrate that genetic variation in SLCO1B1, UGT1A3, LPP, and CYP3A4 affects atorvastatin pharmacokinetics. This is the first study to suggest that LPP rs1975991 may reduce atorvastatin exposure. [Correction added on 6 April, after first online publication: An incomplete sentence ("= 0.017) smaller in heterozygotes for UGT1A3*2 and 34% (22%, 44%; P × 10-5) smaller in homozygotes for LPP noncarriers.") has been corrected in this version.].

Clinical Evaluation of the Effect of Encorafenib on Bupropion, Rosuvastatin, and Coproporphyrin I and Considerations for Statin Coadministration.

BACKGROUND AND OBJECTIVES: Encorafenib is a kinase inhibitor indicated for the treatment of patients with unresectable or metastatic melanoma or metastatic colorectal cancer, respectively, with selected BRAF V600 mutations. A clinical drug-drug interaction (DDI) study was designed to evaluate the effect of encorafenib on rosuvastatin, a sensitive substrate of OATP1B1/3 and breast cancer resistance protein (BCRP), and bupropion, a sensitive CYP2B6 substrate. Coproporphyrin I (CP-I), an endogenous substrate for OATP1B1, was measured in a separate study to deconvolute the mechanism of transporter DDI. METHODS: DDI study participants received a single oral dose of rosuvastatin (10 mg) and bupropion (75 mg) on days - 7, 1, and 14 and continuous doses of encorafenib (450 mg QD) and binimetinib (45 mg BID) starting on day 1. The CP-I data were collected from participants in a phase 3 study who received encorafenib (300 mg QD) and cetuximab (400 mg/m2 initial dose, then 250 mg/m2 QW). Pharmacokinetic and pharmacodynamic analysis was performed using noncompartmental and compartmental methods. RESULTS: Bupropion exposure was not increased, whereas rosuvastatin Cmax and area under the receiver operating characteristic curve (AUC) increased approximately 2.7 and 1.6-fold, respectively, following repeated doses of encorafenib and binimetinib. Increase in CP-I was minimal, suggesting that the primary effect of encorafenib on rosuvastatin is through BCRP. Categorization of statins on the basis of their metabolic and transporter profile suggests pravastatin would have the least potential for interaction when coadministered with encorafenib. CONCLUSION: The results from these clinical studies suggest that encorafenib does not cause clinically relevant CYP2B6 induction or inhibition but is an inhibitor of BCRP and may also inhibit OATP1B1/3 to a lesser extent. Based on these results, it may be necessary to consider switching statins or reducing statin dosage accordingly for coadministration with encorafenib. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov NCT03864042, registered 6 March 2019.

Statin Drug-Drug Interactions: Pharmacokinetic Basis of FDA Labeling Recommendations and Comparison Across Common Tertiary Clinical Resources.

Statins are widely prescribed and highly susceptible to pharmacokinetic (PK)-based drug-drug interactions (DDIs). To date, there has not been a comprehensive analysis of the basis upon which statin DDI recommendations in US Food and Drug Administration (FDA) prescribing information (PI) are derived. We have conducted such an analysis. We also assessed the degree of concordance of statin DDI recommendations in FDA PI and those provided in common tertiary clinical resources. We catalogued statin DDI information, including PK data and management recommendations, for statin precipitant drugs approved from 2010 to 2021, available from FDA PI and tertiary clinical resource databases. Recommendations were categorized and mapped with associated PK data to assess consistency in the PK basis for labeling recommendations. From the 80 precipitant drugs evaluated, 180 statin DDIs were identified in FDA PI. Dedicated clinical DDI studies were conducted for 54% (n = 97) of these DDIs and 34% (n = 61) of DDI recommendations were extrapolated from clinical data with other statins. Overall, we found that PK-based statin recommendations were consistent across PI. These findings highlight regulatory precedence for translating information across statins without conducting dedicated clinical DDI studies, which may support future efforts toward streamlining the approach to investigation and labeling of statin DDIs. In addition, with the exception of some notable discrepancies, general concordance was observed between FDA and tertiary resources regarding "Dose Adjustment" and "Avoid Coadministration" recommendations. However, further analyses are warranted across other DDI pairs to determine whether discordance can routinely lead to different clinical recommendations depending on the drug information resource.

On sample size calculation in drug interaction trials.

Drug-drug interaction (DDI) trials are an important part of drug development as they provide evidence on the benefits and risks when two or more drugs are taken concomitantly. Sample size calculation is typically recommended to be based on the existence of clinically justified no-effect boundaries but these are challenging to define in practice, while the default no-effect boundaries of 0.8-1.25 are known to be overly conservative requiring a large sample size. In addition, no-effect boundaries are of little use when there is prior pharmacological evidence that a mild or moderate interaction between two drugs may be present, in which case effect boundaries would be more useful. We introduce precision-based sample size calculation that accounts for both the stochastic nature of the pharmacokinetic parameters and the anticipated width of (no-)effect boundaries, should these exist. The methodology is straightforward, requires considerably less sample size and has favorable operating characteristics. A case study on statins is presented to illustrate the ideas.

Validation of a novel direct method to determine reduced adherence to atorvastatin therapy.

AIMS: Objective methods to determine statin adherence are requested to improve lipid management. We have recently established a method to detect reduced adherence to atorvastatin therapy with cut-off values based on the sum of atorvastatin and its major metabolites in the blood. We aimed to validate this method in patients with and without cardiovascular disease, and optimize previous cut-off values. METHODS AND RESULTS: The pharmacokinetic study included 60 participants treated with atorvastatin 20 mg (N = 20), 40 mg (N = 20), and 80 mg (N = 20). Atorvastatin was then stopped and blood samples collected from day zero to day four. Quantification of the parent drug and its metabolites in blood plasma was performed with a liquid chromatography-tandem mass spectrometry assay. The cut-off values for reduced adherence were validated and optimized by calculating diagnostic sensitivity and specificity. Our candidate cut-off value of dose-normalized six-component sum of atorvastatin plus metabolites <0.10 nM/mg provided a sensitivity of 97% and a specificity of 93% for detecting ≥2 omitted doses. An optimized cut-off <0.062 nM/mg provided a sensitivity of 90% and a specificity of 100%. An alternative simplified two-component metabolite sum with a cut-off value <0.05 nM/mg provided a sensitivity of 98% and a specificity of 76%. An optimized cut-off <0.02 nM/mg provided a sensitivity of 97% and a specificity of 98%. CONCLUSION: This validation study confirms that our direct method discriminates reduced adherence from adherence to atorvastatin therapy with high diagnostic accuracy. The method may improve lipid management in clinical practice and serve as a useful tool in future studies.

Associations between SLCO1B1, APOE and CYP2C9 and lipid-lowering efficacy and pharmacokinetics of fluvastatin: a meta-analysis.

Objective: This meta-analysis was designed to investigate the associations between SLCO1B1, APOE and CYP2C9 and the lipid-lowering effects and pharmacokinetics of fluvastatin. Methods: Studies were searched from inception to March 2023, including three SNPs related to fluvastatin, SLCO1B1, CYP2C9 and APOE. Weighted mean differences and corresponding 95% CIs were analyzed to evaluate the associations between SNPs and outcomes. Results: SLCO1B1 521T>C was associated with lower total cholesterol and low-density lipoprotein reduction. Patients carrying 521CC or total cholesterol had a significantly higher area under the curve than those carrying 521TT, but no significant difference existed. Conclusion: CYP2C9 and SLCO1B1 may be associated with the efficacy and pharmacokinetics of fluvastatin.

The frequency of rs2231142 in ABCG2 among Native Hawaiian and Pacific Islander subgroups: implications for personalized rosuvastatin dosing.

Statins are among the most commonly prescribed medications worldwide. Rosuvastatin is a moderate- to high-intensity statin depending on the prescribed dose. Statin-associated muscle symptoms are the main side effects, contributing to low adherence to statins. The missense variant rs2231142 in ABCG2 affects the functionality of the ABCG2 transporter, altering the pharmacokinetics and pharmacodynamics of rosuvastatin. This special report aims to accentuate the importance of considering the ABCG2 genotype upon prescribing rosuvastatin in high cardiovascular disease risk subgroups, specifically Native Hawaiian and Pacific Islander populations. Based on the reported frequencies of rs2231142 in ABCG2, it may be justifiable to initiate low-dose rosuvastatin in Samoans relative to Marshallese or Native Hawaiians. Interpopulation differences in pharmacogenetic allele frequencies underscore the need to disaggregate broad population categories to achieve health equity in treatment outcomes.

Rosuvastatin is a medication that is used to decrease levels of bad cholesterol in the blood. One of the side effects of rosuvastatin is muscle aches, which can cause patients to stop taking their medication. ABCG2 is a gene responsible for encoding ABCG2, an important transporter that plays a role in how the body interacts with many medications, including rosuvastatin. Genetic variations in ABCG2 result in a functional or nonfunctional transporter. This special report aims to focus on the importance of considering genetic variations in ABCG2 among different population subgroups, in particular Native Hawaiians, Samoans and Marshallese. The ABCG2 genotype could inform clinicians about the most effective rosuvastatin dose to prescribe. This approach highlights the importance of individualized patient characteristics above and beyond race and ethnicity.

Atorvastatin Metabolite Pattern in Skeletal Muscle and Blood from Patients with Coronary Heart Disease and Statin-Associated Muscle Symptoms.

Self-perceived statin-associated muscle symptoms (SAMS) are prevalent, but only a minority is drug-dependent. Diagnostic biomarkers are not yet identified. The local statin exposure in skeletal muscle tissue may correlate to the adverse effects. We aimed to determine whether atorvastatin metabolites in blood reflect the corresponding metabolite levels in skeletal muscle, and whether genetic variants of statin transporters modulate this relationship. We also addressed atorvastatin metabolites as potential objective biomarkers of SAMS. Muscle symptoms were examined in patients with coronary disease and self-perceived SAMS during 7 weeks of double-blinded treatment with atorvastatin 40 mg/day and placebo in randomized order. A subset of 12 patients individually identified with more muscle symptoms on atorvastatin than placebo (confirmed SAMS) and 15 patients with no difference in muscle symptom intensity (non-SAMS) attended the present follow-up study. All received 7 weeks of treatment with atorvastatin 40 mg/day followed by 8 weeks without statins. Biopsies from the quadriceps muscle and blood plasma were collected after each treatment period. Strong correlations (rho > 0.7) between muscle and blood plasma concentrations were found for most atorvastatin metabolites. The impact of the SLCO1B1 c.521T>C (rs4149056) gene variant on atorvastatin's systemic pharmacokinetics was translated into muscle tissue. The SLCO2B1 c.395G>A (rs12422149) variant did not modulate the accumulation of atorvastatin metabolites in muscle tissue. Atorvastatin pharmacokinetics in patients with confirmed SAMS were not different from patients with non-SAMS. In conclusion, atorvastatin metabolite levels in skeletal muscle and plasma are strongly correlated, implying that plasma measurements are suitable proxies of atorvastatin exposure in muscle tissue. The relationship between atorvastatin metabolites in plasma and SAMS deserves further investigation.

Clinical Drug-Drug Interaction Between Vatiquinone, a 15-Lipoxygenase Inhibitor, and Rosuvastatin, a Breast Cancer Resistance Protein Substrate.

Vatiquinone is a small-molecule inhibitor of 15-lipoxygenase in phase 3 development for patients with mitochondrial disease and Friedreich ataxia. The objective of this analysis was to determine the effect of vatiquinone on the pharmacokinetic profile of rosuvastatin, a breast cancer resistance protein substrate. In vitro investigations demonstrated potential inhibition of BCRP by vatiquinone (half maximal inhibitory concentration, 3.8 µM). An open-label, fixed-sequence drug-drug interaction study in healthy volunteers was conducted to determine the clinical relevance of this finding. Subjects received a single dose of 20-mg rosuvastatin followed by a 7-day washout. On days 8 through 14, subjects received 400 mg of vatiquinone 3 times daily. On day 12, subjects concomitantly received a single dose of 20-mg rosuvastatin. The geometric mean ratio for maximum plasma concentration was 77.8%; however, the rosuvastatin disposition phase appeared unaffected. The geometric mean ratios for the area under the plasma concentration-time curve from time 0 to time t and from time 0 to infinity were 103.2% and 99.9%, respectively. Mean rosuvastatin apparent elimination half-life was similar between treatment groups. These results demonstrate that vatiquinone has no clinically relevant effect on the pharmacokinetics of rosuvastatin.

Statins Increase the Bioavailability of Fixed-Dose Combination of Sofosbuvir/Ledipasvir by Inhibition of P-glycoprotein.

BACKGROUND: Coadministration of statins and direct acting antiviral agents is frequently used. This study explored the effects of both atorvastatin and lovastatin on pharmacokinetics of a fixed-dose combination of sofosbuvir/ledipasvir "FDCSL". METHODS: 12 healthy volunteers participated in a randomized, three-phase crossover trial and were administered a single atorvastatin dose 80 mg plus tablet containing 400/90 mg FDCSL, a single lovastatin dose 40 mg plus tablet containing 400/90 mg FDCSL, or tablets containing 400/90 mg FDCSL alone. Liquid chromatography-tandem mass spectrometry was used to analyze plasma samples of sofosbuvir, ledipasvir and sofosbuvir metabolite "GS-331007" and their pharmacokinetic parameters were determined. RESULTS: Atorvastatin caused a significant rise in sofosbuvir bioavailability as explained by increasing in AUC0-∞ and Cmax by 34.36% and 11.97%, respectively. In addition, AUC0-∞ and Cmax of GS-331007 were increased by 73.73% and 67.86%, respectively after atorvastatin intake. Similarly, co-administration of lovastatin with FDCSL increased the bioavailability of sofosbuvir, its metabolite (AUC0-∞ increase by 17.2%, 17.38%, respectively, and Cmax increase by 12.03%, 22.24%, respectively). However, neither atorvastatin nor lovastatin showed a change in ledipasvir bioavailability. Hepatic elimination was not affected after statin intake with FDCSL. Compared to lovastatin, atorvastatin showed significant increase in AUC0-∞ and Cmax of both sofosbuvir and its metabolite. CONCLUSIONS: Both atorvastatin and lovastatin increased AUC of sofosbuvir and its metabolite after concurrent administration with FDCSL. Statins' P-glycoprotein inhibition is the attributed mechanism of interaction. The increase in sofosbuvir bioavailability was more pronounced after atorvastatin intake. Close monitoring is needed after co-administration of atorvastatin and FDCSL.

Evodiamine decreased the systemic exposure of pravastatin in non-alcoholic steatohepatitis rats due to the up-regulation of hepatic OATPs.

CONTEXT: Patients with non-alcoholic steatohepatitis (NASH) may have a simultaneous intake of pravastatin and evodiamine-containing herbs. OBJECTIVE: The effect of evodiamine on the pharmacokinetics of pravastatin and its potential mechanisms were investigated in NASH rats. MATERIALS AND METHODS: The NASH model was conducted with feeding a methionine choline-deficient (MCD) diet for 8 weeks. Sprague-Dawley rats were randomised equally (n = 6) into NASH group, evodiamine group (10 mg/kg), pravastatin group (10 mg/kg), and evodiamine (10 mg/kg) + pravastatin (10 mg/kg) group. Normal control rats were fed a standard diet. Effects of evodiamine on the pharmacokinetics, distribution, and uptake of pravastatin were investigated. RESULTS: Evodiamine decreased Cmax (159.43 ± 26.63 vs. 125.61 ± 22.17 µg/L), AUC0-t (18.17 ± 2.52 vs. 14.91 ± 2.03 mg/min/L) and AUC0-∞ (22.99 ± 2.62 vs. 19.50 ± 2.31 mg/min/L) of orally administered pravastatin in NASH rats, but had no significant effect in normal rats. Evodiamine enhanced the uptake (from 154.85 ± 23.17 to 198.48 ± 26.31 pmol/mg protein) and distribution (from 736.61 ± 108.07 to 911.89 ± 124.64 ng/g tissue) of pravastatin in NASH rat liver. The expression of Oatp1a1, Oatp1a4, and Oatp1b2 was up-regulated 1.48-, 1.38-, and 1.51-fold by evodiamine. Evodiamine decreased the levels of IL-1ß, IL-6, and TNF-α by 27.82%, 24.76%, and 29.72% in NASH rats, respectively. DISCUSSION AND CONCLUSIONS: Evodiamine decreased the systemic exposure of pravastatin by up-regulating the expression of OATPs. These results provide a reference for further validation of this interaction in humans.

QiShenYiQi pills, a Chinese patent medicine, increase bioavailability of atorvastatin by inhibiting Mrp2 expression in rats.

CONTEXT: Atorvastatin (ATV) and QiShenYiQi pills (QSYQ), a Chinese patent medicine, are often co-prescribed to Chinese cardiovascular patients. The effects of QSYQ on the pharmacokinetics of ATV have not been studied. OBJECTIVE: We investigated the influence of QSYQ on the pharmacokinetics of ATV and its metabolites upon oral or intravenous administration of ATV to rats. MATERIALS AND METHODS: Sprague-Dawley rats (n = 5/group) were pre-treated with oral QSYQ (675 mg/kg) or vehicle control for 7 days and then orally administrated ATV (10 mg/kg) or intravenously administrated ATV (2 mg/kg). Serum concentrations of ATV and metabolites were determined by ultra-high performance liquid chromatography tandem mass spectrometry. Expression of metabolic enzymes and transporters in jejunum and ileum were measured by quantitative real-time PCR and Western blot. RESULTS: QSYQ resulted in an increase of AUC0-12 h of ATV from 226.67 ± 42.11 to 408.70 ± 161.75 ng/mL/h and of Cmax of ATV from 101.46 ± 26.18 to 198.00 ± 51.69 ng/mL and in an increased of para-hydroxy atorvastatin from 9.07 ± 6.20 to 23.10 ± 8.70 ng/mL in rats administered ATV orally. No change was observed in rats treated intravenously. The expression of multidrug resistance-associated protein 2 mRNA and protein decreased in ileum, and the mRNA of P-glycoprotein decreased in jejunum, though no change in protein expression was found. DISCUSSION AND CONCLUSIONS: QSYQ increased bioavailability of ATV administered orally through inhibiting the expression of Mrp2 in ileum. Clinicians should pay close attention to potential drug-drug interactions between ATV and QSYQ.

Influence of Gegenqinlian Decoction on Pharmacokinetics and Pharmacodynamics of Atorvastatin Calcium in Hyperlipidemic Rats.

BACKGROUND AND OBJECTIVES: Gegenqinlian decoction (GQD), a classic traditional Chinese medicine (TCM), was described in Shanghan Lun. GQD is often combined with antihyperlipidemic drugs (mainly atrovastatin calcium) in TCM clinics. However, the herb-drug interaction between GQD and atrovastatin calcium (AC) is still unknown. To determine whether the combination is safe, we evaluated the effects of GQD on the activities of cytochrome P450 (CYP) 3A2 enzyme and investigated the impact of GQD on the pharmacokinetics and pharmacodynamics of AC in rats. METHODS: The pharmacokinetics of AC (10 mg/kg) with or without pretreatment with GQD (freeze-dried powder, 1.35 g/kg) were investigated using HPLC. The influence of GQD on pharmacodynamics of AC were determined by detecting the levels of serum total cholesterol (TC), triglycerides (TG), low density lipoprotein cholesterol (LDL-C), high density lipoprotein cholesterol (HDL-C), aspartate aminotransferase (AST) and alanine aminotransferase (ALT). Moreover, the probe drug method was used to explore the effect of GQD on CYP3A2 activity. RESULTS: The pharmacokinetic parameters of AC combined with GQD were significantly affected (P < 0.05) in hyperlipidemic rats. The serum TC, TG and LDL-C levels of the combination were significantly reduced (P < 0.05), and the serum HDL-C level was significantly increased (P < 0.05) compared with AC/GQD alone. AST and ALT activities treated with both GQD and AC+GQD group were significantly reduced (P < 0.05) compared with AC group. There was a significant difference in the pharmacokinetic parameters of midazolam between control and GQD groups (P < 0.05). Maximum concentration (Cmax), area under the concentration-time curve (AUC) from time 0 to the last quantifiable concentration (AUC0-t) and AUC from time 0 to infinity (AUC0-∞) increased significantly in GQD group. CONCLUSIONS: The result suggested that GQD combined with AC can improve the lipid-lowering effect of AC and reduce the damage of AC to the liver simultaneously. However, GQD can inhibit the activity of CYP3A2 in hyperlipidemic rats and increase the blood concentration of AC. Therefore, the clinical dose of AC should be adjusted when they are combined. Since the study was conducted in rats,  further research should be carried out to assess the uniformity of the pharmacokinetics and pharmacodynamics between rats and humans.

LEGACY: Phase 2a Trial to Evaluate the Safety, Pharmacokinetics, and Pharmacodynamic Effects of the Anti-EL (Endothelial Lipase) Antibody MEDI5884 in Patients With Stable Coronary Artery Disease.

OBJECTIVE: Functional HDL (high-density lipoprotein) particles that facilitate cholesterol efflux may be cardioprotective. EL (endothelial lipase) hydrolyzes phospholipids promoting catabolism of HDL and subsequent renal excretion. MEDI5884 is a selective, humanized, monoclonal, EL-neutralizing antibody. We sought to determine the safety, pharmacokinetics, and pharmacodynamic effects of multiple doses of MEDI5884 in patients with stable coronary artery disease. Approach and Results: LEGACY was a phase 2a, double-blind, placebo-controlled, parallel-design trial that randomized 132 patients with stable coronary artery disease receiving high-intensity statin therapy to 3 monthly doses of 1 of 5 dose levels of MEDI5884 (50, 100, 200, 350, or 500 mg SC) or matching placebo. The primary end point was the safety and tolerability of MEDI5884 through the end of the study (day 151). Additional end points included change in HDL cholesterol and cholesterol efflux from baseline to day 91, hepatic uptake of cholesterol at day 91, changes in various other lipid parameters. The incidence of adverse events was similar between the placebo and MEDI5884 groups. In a dose-dependent manner, MEDI5884 increased HDL cholesterol up to 51.4% (P<0.0001) and global cholesterol efflux up to 26.2% ([95% CI, 14.3-38.0] P<0.0001). MEDI5884 increased HDL particle number up to 14.4%. At the highest dose tested, an increase in LDL (low-density lipoprotein) cholesterol up to 28.7% (P<0.0001) and apoB (apolipoprotein B) up to 13.1% (P=0.04) was observed with MEDI5884. However, at the potential target doses for future studies, there was no meaningful increase in LDL cholesterol or apoB. CONCLUSIONS: Inhibition of EL by MEDI5884 increases the quantity and quality of functional HDL in patients with stable coronary artery disease on high-intensity statin therapy without an adverse safety signal at the likely dose to be used. These data support further clinical investigation. Registration: URL: https://www.clinicaltrials.gov; Unique identifier: NCT03351738.