Drug-Drug Interactions Between Glucagon-Like Peptide 1 Receptor Agonists and Oral Medications: A Systematic Review

BACKGROUND

Glucagon-like peptide 1 receptor agonists (GLP1RAs) are used in the treatment of diabetes and obesity. Their slowing effect of gastric emptying might change oral drug absorption, potentially affecting pharmacokinetics, particularly in the case of medications with a narrow therapeutic index.

PURPOSE

The purpose of this systematic review is to summarize data on drug-drug interactions between GLP1RAs and oral drugs.

DATA SOURCES

The PubMed and EMBASE databases were searched up to November, 1st 2023.

STUDY SELECTION

We selected pharmacokinetic studies of any injectable GLP1RA given with an oral medication, and product prescribing sheets reporting data without access to the original study.

DATA EXTRACTION

Two authors independently extracted the data.

DATA SYNTHESIS

Twenty-two reports and six prescribing sheets were included. Treatment with GLP1RAs resulted in unaffected or reduced Cmax and delayed tmax of drugs with high solubility and permeability (warfarin, contraceptive pills, acetaminophen), drugs with high solubility and low permeability (angiotensin converting enzyme inhibitors), drugs with low solubility and high permeability (statins) and drugs with low solubility and permeability (digoxin). However, the use of GLP1RAs did not exert clinically significant changes in the AUC or differences in clinically relevant endpoints.

LIMITATIONS

The major limitations of the studies that are included in this systematic review are the enrollment of healthy subjects and insufficient data in conditions that might affect pharmacokinetics (e.g., kidney dysfunction).

CONCLUSIONS

To conclude, reduced Cmax and delayed tmax of drugs co-administered with GLP1RAs are consistent with the known delayed gastric output by the latter. Nevertheless, the overall drug exposure was not considered clinically significant. Dose adjustments are probably not required for simultaneous use of GLP1RAs with oral medications. Still, results should be carefully generalized to cases of background kidney dysfunction or when using drugs with narrow therapeutic index. The study is registered in PROSPERO: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42022332339 .

Population Pharmacokinetics of Atorvastatin in High-Altitude and Plain Patients with Hyperlipidemic

The pharmacokinetic (PK) characteristics of drugs were altered under high-altitude hypoxia. We aim to describe the population PK of atorvastatin (ATV) to identify patient characteristics that are predictive of variability in the PK parameters of the ATV and investigate the effects of high-altitude hypoxia on the blood concentration of ATV in patients with hyperlipidemia. A total of 160 plasma concentrations were collected from 40 patients with hyperlipidemia in plateau areas and 40 in plain areas. The population pharmacokinetic model of patients with hyperlipidemia in plateau and plain areas of China was established by a nonlinear mixed-effects model. The PK of ATV were described by a 1-compartment model with first-order elimination. The main PK parameters of ATV were the first-order absorption rate (0.76 hour-1 fixed); clearance (174.22 L/h) and apparent volume of distribution (1119.62 L). The values of area and age were identified as significant covariates for the clearance, area, age, and urea for the volume of distribution. The steady-state peak concentration in the plateau area was higher than that in the plain area. This study may suggest dose reduction is necessary for patients with hyperlipidemia in high altitudes.

Population pharmacokinetic of paracetamol and atorvastatin with co-administration of semaglutide

Semaglutide is a glucagon-like-peptide-1 (GLP-1) analogue marketed for once-weekly subcutaneous administration for type 2 diabetes mellitus. Like other long-acting GLP-1 analogues, semaglutide reduces gastric emptying and, potentially, alters the rate of absorption of orally co-administered drugs. The objective of the current analysis was to evaluate the effects on the gastric emptying rate caused by semaglutide on pharmacokinetic model parameters of paracetamol and atorvastatin in healthy subjects. Non-linear mixed effect modeling was used to estimate population pharmacokinetic model parameters of paracetamol and atorvastatin after single doses with or without semaglutide. The absorption rate (ka) of paracetamol decreased by 53% when co-administered with semaglutide. For atorvastatin, ka and transit compartment rate (ktr) decreased by 72% and 91%, respectively. Thus, gastric emptying, measured as T50, i.e., drug disappearance from the absorption compartments, showed an additional 5-min delay for paracetamol and a 67-min delay for atorvastatin when co-administered with semaglutide. Semaglutide affected pharmacokinetic model parameters of paracetamol and atorvastatin, and minor quantitative differences in gastric emptying between placebo vs. semaglutide administration were observed. However, these effects of semaglutide were considered not to be of clinical relevance.

Atorvastatin population pharmacokinetics in a real-life setting: Influence of genetic polymorphisms and association with clinical response

The purpose of this study was to investigate the potential clinical relevance of estimating the apparent clearance (CL/F) of atorvastatin through population pharmacokinetic (PopPK) modeling with samples collected in a real‐life setting in a cohort of ambulatory patients at risk of cardiovascular disease by using an opportunistic sampling strategy easily accessible in clinical routine. A total of 132 pharmacokinetic (PK) samples at a maximum of three visits were collected in the 70 included patients. The effects of demographic, genetic, and clinical covariates were also considered. With the collected data, we developed a two‐compartment PopPK model that allowed estimating atorvastatin CL/F relatively precisely and considering the genotype of the patient for SLCO1B1 c.521T>C single‐nucleotide polymorphism (SNP). Our results indicate that the estimation of the CL/F of atorvastatin through our PopPK model might help in identifying patients at risk of myalgia. Indeed, we showed that a patient presenting a CL/F lower than 414.67 L h⁻¹ is at risk of suffering from muscle discomfort. We also observed that the CL/F was correlated with the efficacy outcomes, suggesting that a higher CL/F is associated with a better drug efficacy (i.e., a greater decrease in total and LDL‐cholesterol levels). In conclusion, our study demonstrates that PopPK modeling can be useful in daily clinics to estimate a patient’ atorvastatin clearance. Notifying the clinician with this information can help in identifying patients at risk of myalgia and gives indication about the potential responsiveness to atorvastatin therapy.

A pharmacokinetics-based approach to the monitoring of patient adherence to atorvastatin therapy

The inadequate adherence of patients whose hyperlipidemia is treated with atorvastatin (ATR) to medical instructions presents a serious health risk. Our aim was to develop a flexible approach based on therapeutic drug monitoring (TDM), nonparametric population pharmacokinetic modeling, and Monte Carlo simulation to differentiate adherent patients from partially and nonadherent individuals in a nonrandomized, unicentric, observational study. Sixty-five subjects were enrolled. Nonparametric, mixed-effect population pharmacokinetic models of the sums of atorvastatin and atorvastatin lactone concentrations (ATR+ATRL) and of the concentrations of the acid and lactone forms of ATR and its 2- and 4-hydroxylated pharmacologically active metabolites (ATR+MET) were elaborated by including the TDM results obtained in 128 samples collected from thirty-nine subjects. Monte Carlo simulation was performed based on the elaborated models to establish the probabilities of attaining a specific ATR+ATRL or ATR+MET concentration in the range of 0.002-10 nmol (mg dose)-1 L-1 at 1-24 h postdose by adherent, partially adherent, and nonadherent patients. The results of the simulations were processed to allow the estimation of the adherence of further 26 subjects who were phlebotomized at sampling times of 2-20 h postdose by calculating the probabilities of attaining the ATR+ATRL and ATR+MET concentrations measured in these subjects in adherent, partially adherent, and nonadherent individuals. The best predictive values of the estimates of adherence could be obtained with sampling at early sampling times. 61.54% and 38.46% of subjects in the adherence testing set were estimated to be fully and partially adherent, respectively, while in all cases the probability of nonadherence was extremely low. The evaluation of patient adherence to ATR therapy based on pharmacokinetic modeling and Monte Carlo simulation has important advantages over the collection of trough samples and the use of therapeutic ranges.

Influence of Drug-Drug Interactions on the Pharmacokinetics of Atorvastatin and Its Major Active Metabolite ortho-OH-Atorvastatin in Aging People Living with HIV

Background

People living with HIV (PLWH) are aging and experience age-related physiological changes and comorbidities. Atorvastatin is a widely prescribed lipid-lowering agent metabolized by cytochrome P450 (CYP) 3A4, whose hepatocyte uptake is facilitated by organic anion transporting polypeptide (OATP) 1B1/1B3. Inhibition or induction of this enzyme and hepatic transporter can increase or decrease atorvastatin exposure, respectively.

Objective

This study aimed to describe the pharmacokinetic profile of atorvastatin and its major metabolite, and to evaluate drug–drug interactions (DDIs) with antiretrovirals (ARVs).

Methods

The atorvastatin pharmacokinetic profile was best described by a two-compartment model with first-order absorption and elimination. Metabolite concentrations were described by considering both linear metabolism from atorvastatin and presystemic metabolism. The influence of demographic and clinical covariates on drug and metabolite pharmacokinetics was assessed using NONMEM^®. Model-based simulations were performed to evaluate the magnitude of DDIs with ARVs.

Results

Full pharmacokinetic profiles (98 atorvastatin + 62 o-OH-atorvastatin concentrations) and sparse concentrations (78 and 53 for atorvastatin and o-OH-atorvastatin, respectively) were collected in 59 PLWH. Interindividual variability was high. The coadministration of boosted ARVs decreased atorvastatin clearance by 58% and slowed down o-OH-atorvastatin formation by 88%. Atorvastatin clearance increased by 78% when coadministered with CYP3A4 inducers. Simulations revealed a 180% increase and 44% decrease in atorvastatin exposure (area under the curve) in the presence of ARVs with inhibiting and inducing properties, respectively.

Conclusion

This study showed an important interindividual variability in atorvastatin pharmacokinetics that remains largely unexplained after the inclusion of covariates. Since boosted ARVs double atorvastatin exposure, the initial dosage might be reduced by half, and titrated based on individual clinical targets.

Electronic supplementary material

The online version of this article (10.1007/s40262-020-00876-0) contains supplementary material, which is available to authorized users.

The Adherence Rate Threshold is Drug Specific

Introduction

Patient adherence to a medication regimen is usually expressed as an adherence rate, defined as the proportion of prescribed doses actually taken. An adherence rate threshold, above which the therapeutic effect is maintained, is typically assigned an arbitrary value, commonly 0.8.

Objective

Here, we determined the value of the adherence rate threshold objectively in different drugs of the same class, using statins as an example.

Methods

We used pharmacokinetic/pharmacodynamic (PK/PD) modeling to predict serum levels of low-density lipoprotein cholesterol (LDL-C) in patients taking simvastatin 20 mg or atorvastatin 5 mg once daily for 30 days. LDL-C reduction was modeled for adherence rates of 1.0, 0.8, 0.6, 0.4, and 0.2. The results were expressed as the percentage of time spent at the LDL-C goal (< 70 mg/dL). The adherence rate threshold was defined as the minimum adherence rate that resulted in the same amount of time at goal as perfect adherence (i.e., a rate of 1.0).

Results

For simvastatin, an adherence rate of 0.8 resulted in a significant decrease in time at the LDL-C goal compared to perfect adherence (54.8% versus 85.1%; P < 0.001), and rates < 0.8 resulted in progressively less time at goal. For atorvastatin, the rates of 0.8 and 0.6 resulted in essentially the same amount of time at goal as perfect adherence (87.8% and 87.7%, respectively, versus 88.1%; P > 0.05 for both), with less time at goal only occurring at rates ≤ 0.4 (P < 0.001). Thus, the adherence rate thresholds are > 0.8 for simvastatin and between 0.4 and 0.6 for atorvastatin.

Conclusion

These results indicate that a value of 0.8 cannot be applied universally.

Modelling of atorvastatin pharmacokinetics and the identification of the effect of a BCRP polymorphism in the Japanese population

AIM

Ethnicity plays a modulating role in atorvastatin pharmacokinetics (PK), with Asian patients reported to have higher exposure compared with Caucasians. Therefore, it is difficult to safely extrapolate atorvastatin PK data and models across ethnic groups. This work aims to develop a population PK model for atorvastatin and its pharmacologically active metabolites specifically for the Japanese population. Subsequently, it aimed to identify genetic polymorphisms affecting atorvastatin PK in this population.

METHODS

Atorvastatin acid (ATA) and ortho-hydroxy-atorvastatin acid (o-OH-ATA) plasma concentrations, clinical/demographic characteristics and genotypes for 18 (3, 3, 1, 1, 7, 2 and 1 in the ABCB1, ABCG2, CYP3A4, CYP3A5, SLCO1B1, SLCO2B1 and PPARA genes, respectively) genetic polymorphisms were collected from 27 Japanese individuals (taking 10 mg atorvastatin once daily) and analysed using a population PK modelling approach.

RESULTS

The population PK model developed (one-compartment for ATA linked through metabolite formation to an additional compartment describing the disposition of o-OH-ATA) accurately described the observed data and the associated population variability. Our analysis suggested that patients carrying one variant allele for the rs2622604 polymorphism (ABCG2) show a 55% (95% confidence interval: 16-131%) increase in atorvastatin oral bioavailability relative to the value in individuals without the variant allele.

CONCLUSION

The current work reports the identification in the Japanese population of a BCRP polymorphism, not previously associated with the PK of any statin, that markedly increases ATA and o-OH-ATA exposure. The model developed may be of clinical importance to guide dosing recommendations tailored specifically for the Japanese.

A framework for quantifying the influence of adherence and dose individualization

A failure to accommodate for a patient's imperfect adherence may result in therapeutic failure. Similarly, failure to accommodate a patient's individual needs via dose individualization may also result in poor patient outcomes. The property of a drug that signifies the likelihood of therapeutic success to imperfect adherence is termed "forgiveness." We introduce an extension to this concept as: (1) a priori forgiveness (forgiveness when dose individualization is not considered) and (2) a posteriori forgiveness (forgiveness when considering dose individualization). We illustrate cases when adherence is of primary importance and in which dose individualization is of primary importance. The concept of a priori forgiveness and a posteriori forgiveness provides a quantitative measure that allows the influence of adherence to be disentangled from dose individualization and could be used to provide clear guidelines about the relative importance of each in clinical practice.

Stability indicating method development and validation for simultaneous estimation of atorvastatin calcium and celecoxib in bulk and niosomal formulation by RP-HPLC

The present work describes development and validation of a specific, sensitive, precise and stability-indicating high-performance liquid chromatographic method of analysis of atorvastatin calcium and celecoxib, both as a bulk drug and in niosomal formulation. The analysis has been performed by using Cosmosil-C18 column (4.6 mm´250 mm, 5 m) at 25 °C using acetonitrile: ammonium acetate buffer pH 5.0: methanol (50:25:25 v/v/v) as mobile phase. The detection was carried out at 277nm with a flow rate of 1.0mL/min. The retention times of Atorvastatin calcium and Celecoxib were 6.195 and 3.989min, respectively. The method was validated according to ICH guidelines, for specificity, precision, linearity, accuracy and robustness. Atorvastatin calcium and Celecoxib were subjected to stress conditions of hydrolysis, oxidation, photolysis and thermal degradation. The degradation was observed in oxidation and acid hydrolysis. The linearity for atorvastatin calcium and celecoxib were in the range of 100-500 µg/mL. The recovery study of atorvastatin and celecoxib were found to be in the range of 98.96 - 99.92% and 98.90-100%, respectively. The proposed method was validated and successfully applied to the estimation of Atorvastatin calcium and Celecoxib in combined in-house niosomal formulation.

Population pharmacokinetics of sifalimumab, an investigational anti-interferon-α monoclonal antibody, in systemic lupus erythematosus

Background and Objectives

Sifalimumab is a fully human immunoglobulin G1κ monoclonal antibody that binds to and neutralizes a majority of the subtypes of human interferon-α. Sifalimumab is being evaluated as a treatment for systemic lupus erythematosus (SLE). The primary objectives of this analysis were (a) to develop a population pharmacokinetic model for sifalimumab in SLE; (b) to identify and quantitate the impact of patient/disease characteristics on pharmacokinetic variability; and (c) to evaluate fixed versus body weight (WT)-based dosing regimens.

Methods

Sifalimumab serum concentration-time data were collected from a phase Ib study (MI-CP152) designed to evaluate the safety and tolerability of sifalimumab in adult patients with SLE. Sifalimumab was administered every 14 days as a 30- to 60-minute intravenous infusion with escalating doses of 0.3, 1.0, 3.0, and 10 mg/kg and serum concentrations were collected over 350 days. A total of 120 patients provided evaluable pharmacokinetic data with a total of 2,370 serum concentrations. Sifalimumab serum concentrations were determined using a validated colorimetric enzyme-linked immunosorbent assay (ELISA) with a lower limit of quantitation of 1.25 μg/mL. Population pharmacokinetic modeling of sifalimumab was performed using a non-linear mixed effects modeling approach with NONMEM VII software. Impact of patient demographics, clinical indices, and biomarkers on pharmacokinetic parameters were explored using a stepwise forward selection and backward elimination approach. The appropriateness of the final model was tested using visual predictive check (VPC). The impact of body WT-based and fixed dosing of sifalimumab was evaluated using a simulation approach. The final population model was utilized for phase IIb dosing projections.

Results

Sifalimumab pharmacokinetics were best described using a two-compartment linear model with first order elimination. Following intravenous dosing, the typical clearance (CL) and central volume of distribution (V₁) were estimated to be 176 mL/day and 2.9 L, respectively. The estimates (coefficient of variation) of between-subject variability for CL and V₁ were 28 and 31 %, respectively. Patient baseline body WT, interferon gene signature from 21 genes, steroid use, and sifalimumab dose were identified as significant covariates for CL, whereas only baseline body WT was a significant covariate for V₁ and peripheral volume of distribution (V₂). Although the above-mentioned covariates were statistically significant, they did not explain variability in pharmacokinetic parameters to any relevant extent (<7 %). Thus, no dosing adjustments are necessary. VPC confirmed good predictability of the final population pharmacokinetic model. Simulation results demonstrate that both fixed and body WT-based dosing regimens yield similar median steady state concentrations and overall variability. Fixed sifalimumab doses of 200, 600, and 1,200 mg monthly (with a loading dose at Day 14) were selected for a phase IIb clinical trial.

Conclusion

A two-compartment population pharmacokinetic model adequately described sifalimumab pharmacokinetics. The estimated typical pharmacokinetic parameters were similar to other monoclonal antibodies without target mediated elimination. Although the population pharmacokinetic analysis identified some statistically significant covariates, they explained <7 % between-subject variability in pharmacokinetic parameters indicating that these covariates are not clinically relevant. The population pharmacokinetic analysis also demonstrated the feasibility of switching to fixed doses in phase IIb clinical trials of sifalimumab.

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.

Pharmacokinetic interaction studies of co-administration of ticagrelor and atorvastatin or simvastatin in healthy volunteers

PURPOSE

Interactions between ticagrelor and atorvastatin or simvastatin were investigated in two-way crossover studies.

METHODS

Both studies were open-label for statin; the atorvastatin study was placebo-controlled for ticagrelor. For atorvastatin, volunteers (n = 24) received ticagrelor (loading dose 270 mg; 90 mg twice daily, 7 days) or placebo, plus atorvastatin calcium (80 mg; day 5). For simvastatin, volunteers (n = 24) received simvastatin 80 mg, or ticagrelor (loading dose 270 mg; 180 mg twice daily, 7 days) plus simvastatin (80 mg; day 5). In each study, volunteers received the alternate treatment after washout (≥ 7 days).

RESULTS

Ticagrelor increased mean atorvastatin maximum plasma concentration (C(max)) and area under the plasma concentration-time curve from zero to infinity (AUC) by 23 % and 36 %, respectively. Simvastatin C(max) and AUC were increased by 81 % and 56 % with ticagrelor. Ticagrelor also increased C(max) and AUC of analysed atorvastatin metabolites by 13-55 % and 32-67 %, respectively, and simvastatin acid by 64 % and 52 %, respectively. Co-administration of ticagrelor with each statin was well tolerated.

CONCLUSIONS

Exposure to ticagrelor and its active metabolite, AR-C124910XX, was generally unchanged by a single dose of either statin, except for a minor increase in ticagrelor C(max) in the presence of simvastatin. Effects of ticagrelor on atorvastatin pharmacokinetics were modest and unlikely clinically relevant, while with simvastatin, changes were slightly larger, and simvastatin doses >40 mg with ticagrelor should be avoided.