Pharmacokinetics Of Digoxin Research Articles

Effects of Fostamatinib on the Pharmacokinetics of Digoxin (a P-Glycoprotein Substrate): Results From in Vitro and Phase I Clinical Studies

PurposeFostamatinib, a spleen tyrosine kinase inhibitor and prodrug of the active metabolite R406, is being developed as an anti-inflammatory drug for several indications for which polypharmacy is likely. Digoxin, indicated for congestive cardiac failure, may be used for certain supraventricular dysrhythmias. The studies reported herein examined whether fostamatinib and R406 are inhibitors of P-glycoprotein (P-gp) in vitro and evaluated the effect of fostamatinib on the pharmacokinetic parameters of digoxin to understand drug–drug interaction (DDI) potential in the clinic. MethodsInhibition of P-gp–mediated digoxin transport by fostamatinib and R406 was determined across Caco-2 cell monolayers. Apparent permeability of digoxin was determined and used to calculate efflux ratios and percentage inhibition. Half maximal inhibitory concentrations (IC50) and theoretical gastrointestinal concentration [I2] (dose in moles per 250 mL) were calculated to gauge clinical DDI potential. In a subsequent Phase I study, the plasma concentration–time profiles and resulting pharmacokinetic parameters were examined across 2 treatment periods: (1) oral digoxin loading dose of 0.25 mg BID on day 1 and 0.25 mg once daily on days 2 to 8, and (2) oral digoxin 0.25 mg once daily and oral fostamatinib 100 mg BID on days 9 to 15. FindingsFostamatinib (but not R406) was determined to be a P-gp inhibitor in vitro (IC50 = 3.2 μM). On the basis of a theoretical gastrointestinal concentration (I2)/IC50 ratio of 216 ([I2] = 691 μM), predictions indicated the potential for absorption-based DDI in vivo through inhibition of intestinal P-gp. In the clinical study, when digoxin was co-administered with fostamatinib, digoxin levels were higher before dosing and throughout the dosing interval, and an increase in exposure to digoxin was observed. Co-administration led to a 1.70-fold increase in digoxin maximum plasma concentration at steady state (Cmax,ss) versus digoxin administration alone (2.18 vs 1.32 ng/mL). Median digoxin time of Cmax was earlier when digoxin was co-administered with fostamatinib (1.00 vs 1.48 hours). The digoxin AUC during the dosing interval at steady state was increased 1.37-fold with co-administration. No severe or serious adverse events or deaths were reported. ImplicationsFostamatinib was confirmed to be a P-gp inhibitor in vitro and in vivo, and a DDI with digoxin was apparent. Co-administration of digoxin and fostamatinib was generally well tolerated. However, continued review of digoxin response and dose is advisable should these agents be prescribed concomitantly. ClinicalTrials.gov identifier: NCT01355354.

Population pharmacokinetics and optimization of the dosing regimen of digoxin in adult patients.

BackgroundThis study aimed to evaluate the population pharmacokinetics of digoxin in Japanese patients and establish a dosage regimen based on the pharmacokinetic data.MethodsWe analyzed 287 serum digoxin samples from 192 individuals by using the nonlinear mixed effects model. We used simulations to optimize the dosage regimen of digoxin to achieve a high likelihood of the target concentration (0.5–0.8 ng/mL).ResultsThe total body clearance (CL/F ([L/h]) was calculated using the following formula: CL/F = (1.21 + 0.0532 × CLcr [(mL/min]) × (1 + 0.787 × AMD), where CLcr is the creatinine clearance and AMD is 0 in the case of concomitant administration of amiodarone and 1 otherwise. To achieve the target concentration (0.5–0.8 ng/mL), the dosage of digoxin was 0.0625 mg/day (CLcr < 35 mL/min and AMD = 0); 0.125 mg/day (CLcr, 35–65 mL/min and AMD = 0); 0.1875 mg/day (CLcr, 65–100 mL/min and AMD = 0); 0.0625 mg/every other day (CLcr < 30 mL/min and AMD = 1); and 0.0625 mg/day (CLcr, 30–85 mL/min and AMD = 1).ConclusionsOur findings suggest that population parameters are useful for evaluating digoxin pharmacokinetics.

Proximal Roux-en-Y gastric bypass alters drug absorption pattern but not systemic exposure of CYP3A4 and P-glycoprotein substrates.

To evaluate the effect of Roux-en-Y gastric bypass surgery (RYGB) on the pharmacokinetics of midazolam (a CYP3A4 substrate) and digoxin (a P-glycoprotein substrate). Prospective, nonblinded, longitudinal, single-dose pharmacokinetic study in three phases: presurgery baseline and postoperative assessments at 3 and 12months. Twelve obese patients meeting current standards for bariatric surgery. At each study visit, patients received a single dose of oral digoxin and midazolam at 8a.m. Blood samples were collected at regular intervals for 24hours after dosing. Continuous 12-lead electrocardiogram (EKG), heart rate, blood pressure, and respiratory rate were monitored, and pharmacokinetic parameters from the three visits were compared. The peak plasma concentration (Cmax ) of midazolam increased by 66% and 71% at 3- and 12-month post-RYGB (p=0.017 and p=0.001, respectively), whereas the median time to peak concentration (Tmax ) was reduced by 50%. The mean Cmax for 1'-hydroxymidazolam increased by 87% and 80% at 3 and 12 months (p=0.001 and p<0.001, respectively). However, neither the area under the concentration-time curve (AUC) for midazolam nor the metabolite-to-parent AUC ratio changed significantly over time. For digoxin, the median Tmax decreased from 40minutes at baseline to 30 and 20minutes at 3 and 12 months, respectively. The mean AUC for digoxin, heart rate, and EKG patterns were similar across the three study phases. Contemporary proximal RYGB increases the rate of drug absorption without significantly changing the overall exposure to midazolam and digoxin. The Cmax of a CYP3A4 substrate with a high extraction ratio was substantially increased after RYGB.

Population Pharmacokinetics and Optimization of the Dosing Regimen of Digoxin in Adult Patients

Background: This study aimed to evaluate the population pharmacokinetics of digoxin in Japanese patients and establish a dosage regimen based on the pharmacokinetic data. Methods: We analyzed 287 serum digoxin samples from 192 individuals by using the nonlinear mixed effects model. We used simulations to optimize the dosage regimen of digoxin to achieve a high likelihood of the target concentration (0.5-0.8 ng/mL). Results: The total body clearance (CL/F ([L/h]) was calculated using the following formula: CL/F=(1.21i¼‹0.0532 × CLcr [(mL/min]) × (1+0.787 × AMD), where CLcr is the creatinine clearance and AMD is 0 in the case of concomitant administration of amiodarone and 1 otherwise. To achieve the target concentration (0.5–0.8 ng/mL), the dosage of digoxin was 0.0625 mg/day (CLcr <35 mL/min and AMD=0); 0.125 mg/day (CLcr, 35–65 mL/min and AMD=0); 0.1875 mg/day (CLcr, 65–100 mL/min and AMD=0); 0.0625 mg/every other day (CLcr <30 mL/min and AMD=1); and 0.0625 mg/day (CLcr, 30–85 mL/min and AMD=1). Conclusion: Our findings suggest that population parameters are useful for evaluating digoxin pharmacokinetics.

Lack of effect of ezogabine/retigabine on the pharmacokinetics of digoxin in healthy individuals: results from a drug-drug interaction study.

IntroductionThe potential for ezogabine/retigabine (EZG/RTG) and its N-acetyl metabolite (NAMR) to inhibit the transporter protein P-glycoprotein-(P-gp)-mediated digoxin transport was tested in vitro. EZG/RTG did not inhibit P-gp. However, NAMR inhibited P-gp in a concentration-dependent manner. Based on these in vitro results, NAMR had the potential to inhibit P-gp at therapeutic doses of EZG/RTG (600–1,200 mg/day). As digoxin has a narrow therapeutic index, inhibition of digoxin clearance may have an impact on its safety.MethodsAn open-label, single-center, two session, fixed-sequence study was conducted to assess the effect of co-administration of therapeutic doses of EZG/RTG on digoxin pharmacokinetics in healthy adults. In session 1, subjects received a single dose of digoxin 0.25 mg. In session 2, EZG/RTG was up-titrated over 6 weeks. Digoxin 0.25 mg was co-administered at EZG/RTG steady-state doses of 600, 900, and, based on tolerability, 1,050/1,200 mg/day. Blood samples were collected over 144 hours for determination of digoxin, EZG/RTG, and NAMR concentrations. Urine samples were collected over 48 hours for determination of digoxin concentrations.ResultsOf 30 subjects enrolled, 29 were included in the pharmacokinetic analysis. Compared with digoxin alone, co-administration with EZG/RTG led to small increases in the digoxin plasma area under the concentration–time curve (AUC)0–120 at doses of 600, 900, and 1,050/1,200 mg (geometric mean ratio 1.08, 90% confidence interval [CI] 1.01–1.15; 1.18, 90% CI 1.10–1.27; 1.13, 90% CI 1.05–1.21, respectively). Safety was consistent with previous repeat-dose studies of EZG/RTG in healthy subjects.ConclusionCo-administration of EZG/RTG across the therapeutic range resulted in small, non-dose-dependent and non-clinically relevant increases in digoxin systemic exposure, suggesting that digoxin dose adjustment is not necessary.

Lurasidone drug-drug interaction studies: a comprehensive review.

To evaluate potential drug-drug interactions with the atypical antipsychotic lurasidone. Seven phase I studies were conducted to investigate the effects of repeated dosing of ketoconazole, diltiazem, rifampin, or lithium on the pharmacokinetics (PK) of single oral doses of lurasidone, or the effects of repeated dosing of lurasidone on the PK of digoxin, midazolam, or the oral contraceptive norgestimate/ethinyl estradiol. Two 6-week, phase III studies included evaluation of the potential for interaction between lurasidone and lithium or valproate. Maximum serum or plasma concentration (Cmax) and area under the concentration-time curve (AUC) were calculated. Concomitant ketoconazole administration resulted in a 6.8-fold increase in lurasidone Cmax and a 9.3-fold increase in lurasidone AUC; concomitant diltiazem administration resulted in 2.1- and 2.2-fold increases, respectively. Rifampin decreased lurasidone Cmax and AUC (one-seventh and one-fifth of lurasidone alone, respectively). Steady-state dosing with lurasidone increased Cmax and AUC0-24 (AUC from time 0 to 24 h postdose) of digoxin by 9% and 13%, respectively, and of midazolam by 21% and 44%, respectively. There were no significant interactions between lurasidone and lithium, valproate, ethinyl estradiol, or norelgestromin (the major active metabolite of norgestimate). Lurasidone PK is altered by strong cytochrome P450 (CYP) 3A4 inhibitors or inducers, and coadministration is contraindicated; whereas moderate CYP3A4 inhibitors have less effect, and lurasidone dosage restrictions are recommended. No dose adjustment for lurasidone is needed when administered with lithium or valproate. Dose adjustment is not required for lithium, valproate, digoxin (a P-glycoprotein substrate), or midazolam or oral contraceptives (CYP3A4 substrates) when coadministered with lurasidone.

No clinically significant drug interactions between lenalidomide and P-glycoprotein substrates and inhibitors: results from controlled phase I studies in healthy volunteers

PurposeLenalidomide, a weak substrate of P-glycoprotein (P-gp) in vitro, is an oral anticancer drug eliminated predominantly via renal excretion as unchanged compound. The role of P-gp in lenalidomide disposition and the associated clinical relevance were evaluated.MethodsTwo phase I, crossover studies were conducted in healthy volunteers. In Study 1, subjects received lenalidomide (10 mg × 7 days) alone or with the P-gp substrate digoxin (0.5 mg on Day 5). In Study 2, subjects received lenalidomide (a single 25 mg dose) alone, the P-gp inhibitor quinidine (300–600 mg twice-daily × 5 days) plus lenalidomide (on Day 4), the P-gp inhibitor/substrate temsirolimus (a single 25 mg dose) alone, or lenalidomide plus temsirolimus. Pharmacokinetic and safety data were collected for lenalidomide and the co-administrated drugs.ResultsThere were no significant changes in the maximum concentration (C max) and area under the plasma concentration–time curve (AUC) of lenalidomide when co-administered with quinidine, digoxin, or temsirolimus. Neither the rate nor the capacity of lenalidomide renal excretion was affected by quinidine or temsirolimus, in addition lenalidomide absorption rate and bioavailability remained unchanged. Furthermore, lenalidomide had no significant effect on blood C max and AUC of temsirolimus and its active metabolite sirolimus (also a P-gp inhibitor/substrate). The C max of digoxin was slightly higher (+14 %) when administered with lenalidomide versus placebo. There were no other changes in digoxin pharmacokinetics upon co-administration with lenalidomide. No remarkable safety findings were observed.ConclusionsThere are no clinically significant pharmacokinetic interactions between lenalidomide and substrates or inhibitors of P-gp.

A Population Pharmacokinetic Analysis of the Influence of Nutritional Status of Digoxin in Hospitalized Korean Patients

BackgroundSafe and effective use of digoxin in hospitalized populations requires information about the drug’s pharmacokinetics and the influence of various factors on drug disposition. However, no attempts have been made to link an individual’s digoxin requirements with nutritional status. ObjectivesThe main goal of this study was to estimate the population pharmacokinetics of digoxin and to identify the nutritional status that explains pharmacokinetic variability in hospitalized Korean patients. MethodsRoutine therapeutic drug-monitoring data from 106 patients who received oral digoxin at Seoul National University Bundang Hospital were retrospectively collected. The pharmacokinetics of digoxin were analyzed with a 1-compartment, open-label pharmacokinetic model by using a nonlinear mixed-effects modeling tool (NONMEM) and a multiple trough screening approach. ResultsThe effect of demographic characteristics and biochemical and nutritional indices were explored. Estimates generated by using NONMEM indicated that the CL/F of digoxin was influenced by renal function, serum potassium, age, and percentage of ideal body weight (PIBW). These influences could be modeled by following the equation CL/F (L/h) = 1.36 × (creatinine clearance/50)1.580 × K0.835 × 0.055 × (age/65) × (PIBW/100)0.403. The interindividual %CV for CL/F was 34.3%, and the residual variability (SD) between observed and predicted concentrations was 0.225 μg/L. The median estimates from a bootstrap procedure were comparable and within 5% of the estimates from NONMEM. Correlation analysis with the validation group showed a linear correlation between observed and predicted values. ConclusionsThe use of this model in routine therapeutic drug monitoring requires that certain conditions be met which are consistent with the conditions of the subpopulations in the present study. Therefore, further studies are needed to clarify the effects of nutritional status on digoxin pharmacokinetics. The present study established important sources of variability in digoxin pharmacokinetics and highlighted the relationship between pharmacokinetic parameters and nutritional status in hospitalized Korean patients.

The effect of maraviroc on the pharmacokinetics of digoxin in healthy volunteers.

Clinical Pharmacology in Drug DevelopmentVolume 3, Issue 3 p. 202-206 Brief Report The effect of maraviroc on the pharmacokinetics of digoxin in healthy volunteers Manoli Vourvahis, Corresponding Author Manoli Vourvahis Pfizer Global Research and Development, New York, NY, USA Corresponding Author: Manoli Vourvahis, Pfizer Global Research and Development, 219 East 42nd Street, New York, NY 10017 (e-mail: [email protected])Search for more papers by this authorJuanzhi Fang, Juanzhi Fang Pfizer Global Research and Development, Groton, CT, USACurrent address: Shire HGT, Lexington, MA, USA.Search for more papers by this authorHeng Wee Choo, Heng Wee Choo Pfizer Clinical Research Unit, Singapore, SingaporeSearch for more papers by this authorJayvant Heera, Jayvant Heera Pfizer Global Research and Development, Groton, CT, USASearch for more papers by this author Manoli Vourvahis, Corresponding Author Manoli Vourvahis Pfizer Global Research and Development, New York, NY, USA Corresponding Author: Manoli Vourvahis, Pfizer Global Research and Development, 219 East 42nd Street, New York, NY 10017 (e-mail: [email protected])Search for more papers by this authorJuanzhi Fang, Juanzhi Fang Pfizer Global Research and Development, Groton, CT, USACurrent address: Shire HGT, Lexington, MA, USA.Search for more papers by this authorHeng Wee Choo, Heng Wee Choo Pfizer Clinical Research Unit, Singapore, SingaporeSearch for more papers by this authorJayvant Heera, Jayvant Heera Pfizer Global Research and Development, Groton, CT, USASearch for more papers by this author First published: 11 November 2013 https://doi.org/10.1002/cpdd.91Citations: 2 Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Citing Literature Volume3, Issue3May/June 2014Pages 202-206 RelatedInformation

Physiologically based pharmacokinetic modelling and in vivo [I]/Ki accurately predict P‐glycoprotein‐mediated drug‐drug interactions with dabigatran etexilate

In vitro inhibitory potency (Ki )-based predictions of P-glycoprotein (P-gp)-mediated drug-drug interactions (DDIs) are hampered by the substantial variability in inhibitory potency. In this study, in vivo-based [I]/Ki values were used to predict the DDI risks of a P-gp substrate dabigatran etexilate (DABE) using physiologically based pharmacokinetic (PBPK) modelling. A baseline PBPK model was established with digoxin, a known P-gp substrate. The Km (P-gp transport) of digoxin in the baseline PBPK model was adjusted to Km (i) to fit the change of digoxin pharmacokinetics in the presence of a P-gp inhibitor. Then 'in vivo' [I]/Ki of this P-gp inhibitor was calculated using Km (i) /Km . Baseline PBPK model was developed for DABE, and the 'in vivo' [I]/Ki was incorporated into this model to simulate the static effect of P-gp inhibitor on DABE pharmacokinetics. This approach was verified by comparing the observed and the simulated DABE pharmacokinetics in the presence of five different P-gp inhibitors. This approach accurately predicted the effects of five P-gp inhibitors on DABE pharmacokinetics (98-133% and 89-104% for the ratios of AUC and Cmax respectively). The effects of 16 other P-gp inhibitors on the pharmacokinetics of DABE were also confidently simulated. 'In vivo' [I]/Ki and PBPK modelling, used in combination, can accurately predict P-gp-mediated DDIs. The described framework provides a mechanistic basis for the proper design of clinical DDI studies, as well as avoiding unnecessary clinical DDI studies.

Application of permeability-limited physiologically-based pharmacokinetic models: Part I–digoxin pharmacokinetics incorporating P-glycoprotein-mediated efflux

A prerequisite for the prediction of the magnitude of P-glycoprotein (P-gp)-mediated drug–drug interactions between digoxin and P-gp inhibitors (e.g. verapamil and its metabolite norverapamil) or P-gp inducers (e.g. rifampicin) is a predictive pharmacokinetic model for digoxin itself. Thus, relevant in vitro metabolic, transporter and inhibitory data incorporated into permeability-limited models, such as the “advanced dissolution, absorption and metabolism” (ADAM) module and the permeability-limited liver (PerL) module, integrated with a mechanistic physiologically-based pharmacokinetic (PBPK) model such as that of the Simcyp Simulator (version 12.2) are necessary. Simulated concentration–time profiles of digoxin generated using the developed model were consistent with observed data across 31 independent studies [13 intravenous single dose (SD), 12 per oral SD and six multiple dose studies]. The fact that predicted tmax (time of maximum plasma concentration observed) and Cmax (maximum plasma concentration observed) of oral digoxin were similar to observed values indicated that the relative contributions of permeation and P-gp-mediated efflux in the model were appropriate. There was no indication of departure from dose proportionality over the dose range studied (0.25–1.5 mg). All dose normalised area under the plasma concentration-time curve profiles (AUCs) for the 0.25, 0.5, 0.75 and 1 mg doses resembled each other. Thus, PBPK modelling in conjunction with mechanistic absorption and distribution models and reliable in vitro transporter data can be used to assess the impact of dose on P-gp-mediated efflux (or otherwise).

Absence of clinically relevant drug-drug interaction between odanacatib and digoxin after concomitant administration

This study was conducted in order to assess the effect of multiple doses of odanacatib, a cathepsin (Cat)-K inhibitor, on the pharmacokinetics of digoxin. Twelve healthy male and female subjects received 0.5 mg digoxin and 50 mg odanacatib. This open label study was conducted to determine the effect of odanacatib on the plasma pharmacokinetics of immunoreactive digoxin. Subjects received a single oral dose of 0.5 mg digoxin followed by a 10-day washout, followed by 3 once-weekly oral doses of 50 mg odanacatib and co-administration with 0.5 mg digoxin with the last odanacatib dose. A linear mixed-effect model was used to analyze AUC0-120h. Safety and tolerability were assessed. The estimated geometric-mean-ratio (90% confidence interval) for AUC0-120h was 0.95 (0.89, 1.01), which was within (0.80, 1.25) determined to demonstrate a lack of interaction. There were no serious AEs, discontinuations due to AEs, or clinically significant abnormalities in ECG or vital sign measurements. This study demonstrated that 50 mg odanacatib did not lead to clinically important effects on the pharmacokinetics of 0.5 mg digoxin.

Darexaban (YM150), an oral direct factor Xa inhibitor, has no effect on the pharmacokinetics of digoxin

To investigate the impact of the direct Factor Xa inhibitor darexaban administered in a modified-release formulation (darexaban-MR) on the pharmacokinetic (PK) profile of digoxin. In this Phase I, randomized, double-blind, two-period crossover study (8 days for each treatment, 10 days washout), 24 healthy subjects received darexaban-MR 120 mg once/day (qd) + digoxin 0.25 mg qd in one treatment period, and placebo + digoxin 0.25 mg qd in the other treatment period. Blood for PK assessment of digoxin and darexaban was obtained in serial profile on day 8, as well as pre-dose on day 6-7; urinary PK samples were obtained up to 24 h after the last dose on day 8. A lack of interaction was determined if 90 % confidence intervals (CIs) for the geometric mean ratios (GMR) of digoxin C max,ss and AUC0-24h,ss with and without darexaban-MR co-administration were within 0.80-1.25 limits. Pharmacodynamic activity was assessed by international normalized ratio and activated partial thromboplastin time. Twenty-three subjects completed the study. The GMR (90 % CI) for C max,ss and AUC0-24h,ss of digoxin plus darexaban versus digoxin plus placebo was 1.03 (90 % CI: 0.94-1.12) and 1.11 (90 % CI: 1.05-1.17), respectively. The 90 % CI for the GMRs fell within the limits of 0.80-1.25, indicating a lack of drug-drug interaction. Co-administration of digoxin with darexaban-MR was well tolerated, with no unexpected treatment-emergent adverse events or safety concerns. Co-administration of darexaban-MR did not impact the steady-state PK profile of digoxin.

Therapeutic Drug Monitoring and Population Pharmacokinetics of Digoxin in Jordanian Patients

Therapeutic monitoring of digoxin and the population pharmacokinetic parameters in Jordanian patients were done. Fifty three patients visited cardiac department of Jordan University hospital participated in this study, thirty two patients had congestive heart failure (CHF), while twenty one patients had atrial fibrillation (AF). Ninety three blood samples were collected from those patients for the measurement of digoxin level using AxSYM digoxin II assay method. Serum creatinine and potassium levels were also measured, in addition to blood pressure and heart rate. Microsoft Excel and Statistica programs were used for kinetic and statistical analysis. NONMEM computer program ADVAN 4 and 2 compartment model was used for population analysis of digoxin parameters. The serum digoxin level ranged from 0.11-4 ng/ml. The percentage of all patients enrolled in this study that were out of therapeutic range was 49.05%. Serum digoxin levels were out of therapeutic range in 53.12% of patients with CHF and 42.85% in those with AF. The pharmacokinetic parameters for digoxin obtained in this study using traditional methods were: creatinine clearance CLcr (89.78 ± 45.61 ml/min), digoxin actual clearance CL (200.57 ± 154.52 L/day), volume of distribution V (541.57 ± 149.87L), t1/2(2.98 ± 2.05 day), elimination rate constant (0.41± 0.396 day-1). A strong correlation was also found between actual digoxin clearance with log dose normalized (R2=0.999), and t1/2 (R2= 0.875). No correlations were found between the log of the normalized dose and other pharmacokinetic parameters or potassium levels. The population pharmacokinetic parameter for digoxin obtained in this study were: CL (3.34L/h), Vc (3.27L), Vt (123L), inter-compartment clearance Q (72L/h), absorption rate constant KA (1.25h-1). In Jordanian patients with either AF or CHF digoxin dose adjustment based on therapeutic drug monitoring principles is recommended. Digoxin pharmacokinetics were similar to those reported in non-Jordanian patients; estimated population pharmacokinetic parameters were in agreement with literature values.

Influence of Long-term Enteral Nutrition on Pharmacokinetics of Digoxin in Rats

This study was designed to clarify the influence of long-term enteral nutrition (EN) on the pharmacokinetics of digoxin. Rats were fed EN diets (semi-digested, digested, and elemental) for 4 weeks, then digoxin (0.05 mg/kg) was administered orally. The AUC(0-∞) and k(a) of digoxin were significantly reduced in the semi-digested diet group versus the control, while the AUC(0-∞) was significantly increased in the digested and elemental diet groups. The mRNA level of Slco1a4 was significantly reduced at the upper small intestine in all EN groups. Further, the expression levels of P-glycoprotein (P-gp) protein and Abcb1a mRNA were increased at the same site in all EN groups, and the increases were significant in the elemental diet group. Cyp3a2 protein and mRNA expressions were significantly reduced in the liver in the digested and elemental diet groups. Abcb1a mRNA was also significantly reduced in the kidney in these groups. These results indicate that the absorption kinetics at the small intestine is influenced by semi-digested diet, and the elimination kinetics in the liver and kidney are influenced by digested and elemental diet. Semi-digested diet also altered digoxin pharmacokinetics in humans. Thus, the effect of long-term EN on digoxin pharmacokinetics depended on the dietary components.

The Influence of Multiple-Dose Vorapaxar, an Oral PAR-1 Receptor Antagonist, on the Single-Dose Pharmacokinetics and Pharmacodynamics of Digoxin.

Vorapaxar is a novel orally active thrombin receptor antagonist selective for the PAR-1 receptor. This open-label, single-center, fixed-sequence, 2-period, 2-treatment study assessed the pharmacokinetics and pharmacodynamics of single-dose digoxin in the presence/absence of multiple-dose vorapaxar. Eighteen healthy adult subjects received two treatments in a fixed sequence separated by ≥8-day washout: (A) digoxin 0.5 mg (Day 1); (B) vorapaxar 2.5 mg/day Days 1-6 and single-dose vorapaxar 40 mg administered with single-dose digoxin 0.5 mg Day 7. The geometric mean ratio (%; GMR) for the two treatments (digoxin alone and digoxin plus vorapaxar) and 90% confidence intervals (CIs) for and AUCtf and Cmax of digoxin were calculated. Pharmacodynamics of digoxin was assessed by measuring changes in electrocardiogram (ECG) parameters. The GMR (90% CIs) estimates for digoxin AUCtf and Cmax were 105% (91, 121) and 154% (130, 181), respectively. Except for differences in peak plasma concentrations, the pharmacokinetics of digoxin were similar between the two treatments. Coadministration of vorapaxar plus digoxin had no effect on digoxin Tmax or ECG parameters. The results of this study suggest that the coadministration of vorapaxar and digoxin is unlikely to cause a clinically significant drug-drug interaction.

Absence of a pharmacokinetic interaction of rilpivirine with the P‐glycoprotein substrate digoxin in healthy volunteers

Rilpivirine (RPV, TMC278, Edurant®) is a next‐generation non‐nucleoside reverse transcriptase inhibitor (NNRTI), which demonstrated high virologic response rates and non‐inferiority versus efavirenz in two Phase III trials in HIV‐infected patients through 96 weeks [1,2]. RPV has been shown to inhibit P‐glycoprotein (P‐gp) in vitro with an apparent IC50 of 9.2 µM (3.4 µg/mL). This study evaluated the in‐vivo effect of steady‐state RPV 25 mg once daily (qd) on the single‐dose pharmacokinetics of the probe P‐gp substrate digoxin. This was a Phase I, open‐label, randomised, crossover trial in 22 HIV‐negative volunteers. Participants received in one session a single 0.5 mg dose of digoxin, and in another session RPV 25 mg qd for 16 days with a single 0.5 mg dose of digoxin in the morning of Day 11. All study drugs were taken with a breakfast. Pharmacokinetic profiles of digoxin in plasma and urine were determined over 144 hours after dosing in each session. Steady‐state RPV 24‐hour pharmacokinetic profiles in plasma were determined on Day 11. Plasma and urine samples were analysed using validated LC‐MS/MS methods. Pharmacokinetic parameters were calculated with non‐compartmental methods. The least square (LS) means and associated 90% confidence intervals (CI) of treatment ratios were calculated based on log‐transformed pharmacokinetic parameters. Safety and tolerability were assessed throughout the trial. Digoxin pharmacokinetic parameters and statistical results are summarised in Table 1. Single dose pharmacokinetic parameters of digoxin in the absense and presence of steady‐state RPV Parameter digoxin 0.5 mg alone (reference) digoxin 0.5 mg + RPV 25 mg qd (test) N 21 22 AUC4h ng.h/mL 4.44±1.21 4.46±1.31 AUClast ng.h/mL 26.6±7.38 26.0±7.86 Cmax, ng/mL 1.93±0.637 2.05±0.678 tmax, h 1.50 (0.68–3.00) 1.74 (0.65–3.02) t½, h 38.8±6.30 38.3±8.17 Durine total, % 47.7±9.51 55.7±12.2 CLR, L/h 9.46±2.54 11.2±2.66 LS means (90% CI) of digoxin pharmacokinetic parameter ratios* AUClast 0.98 (0.93–1.04)a Cmax 1.06 (0.97–1.17)a CLR 1.16 (1.07–1.25)b Ratios presented as test/reference, calculated based on log‐transformed pharmacokinetic parameters. N=21 for test and N=22 for reference. N=18 for test and N=22 for reference. The plasma and urine digoxin pharmacokinetics were unaffected by co‐administration of steady‐state RPV. The 90% CIs of the LS means ratios of the main pharmacokinetic parameters were contained within the 0.80‐1.25 boundaries of no effect. The terminal elimination half‐life of digoxin was similar in the absence or the presence of steady‐state RPV. RPV pharmacokinetic parameters were comparable to those in previous clinical trials in healthy volunteers. Administration of digoxin and RPV was generally safe and well tolerated. There were no discontinuations due to adverse events. In conclusion, RPV does not affect the pharmacokinetics of the probe P‐gp substrate digoxin. In vivo, at the recommended RPV dose of 25mg qd, the observed in‐vitro inhibition of P‐gp by RPV is not clinically relevant.

Population pharmacokinetics of digoxin in elderly patients

This study was aimed at determining the population pharmacokinetics of digoxin and identifying factors that explain pharmacokinetic variability in elderly patients. The data of 142 elderly patients and 448 samples were collected after repetitive oral digoxin. Blood samples were drawn at various times after administration. Population pharmacokinetic analysis was performed using nonlinear mixed effects modelling program (NONMEM). A one-compartment model with first-order absorption and elimination was selected as the base model. The influence of demographic characteristics, biochemical and haematological indices as well as other commonly used co-medications were explored. The typical values with interindividual variability for apparent clearance (CL/F) and apparent volume of distribution (V/F) were 8.9Lh(-1) (43.2%) and 420L (65.8%), respectively. The residual variability was 31.6%. CL/F decreased significantly with renal function, total body weight, calcium channel blockers or spironolactone co-therapy and symptom with congestive heart failure. The median parameter estimates from a nonparametric bootstrap procedure were comparable and within 5% of the estimates from NONMEM. These results provide important information for clinicians to optimize digoxin regimens in elderly patients.

Effect of Telaprevir on the Pharmacokinetics of Midazolam and Digoxin

In this open-label study, 24 healthy volunteers received a single intravenous (IV) dose of 0.5 mg of midazolam on day 1 and a single oral dose each of 2 mg of midazolam and 0.5 mg of digoxin on day 3. Telaprevir 750 mg every 8 hours was administered from day 8 through day 23, along with a single IV dose of 0.5 mg of midazolam on day 17 and single oral doses of 2 mg of midazolam and 0.5 mg of digoxin on day 19. Midazolam, 1'-hydroxymidazolam, digoxin, and telaprevir concentrations in plasma and digoxin concentrations in urine were measured and pharmacokinetic parameters calculated. On comparing administration with versus without telaprevir, the geometric least squares mean ratios (with 90% confidence limits) for IV midazolam were 1.02 (0.80, 1.31) for maximum observed concentrations (C(max)) and 3.40 (3.04, 3.79) for area under the curve from 0 to 24 hours (AUC(0-24h)); for oral midazolam 2.86 (2.52, 3.25) for C(max) and 8.96 (7.75, 10.35) for AUC(0-24h); and for oral digoxin 1.50 (1.36, 1.65) for C(max) and 1.85 (1.70, 2.00) for area under the curve from 0 to infinity (AUC(0-∞)). Coadministration of telaprevir with oral midazolam resulted in approximately 3-fold decrease in the mean AUC(0-∞) of 1'-hydroxymidazolam. The renal clearance of digoxin was similar with or without telaprevir. Results show that telaprevir is an inhibitor of CYP3A and P-glycoprotein.

Pharmacokinetics of the Direct Factor Xa Inhibitor Edoxaban and Digoxin Administered Alone and in Combination

The oral anticoagulant edoxaban, a factor Xa inhibitor, will likely be coadministered with digoxin in some patients with atrial fibrillation. Both drugs are substrates for P-glycoprotein. The objective of this phase 1, parallel study was to assess the effects of coadministration of both drugs on their respective pharmacokinetics (PK) and pharmacodynamics (PD). Forty-eight subjects, aged 18 to 45 years, received either edoxaban 60 mg once daily × 7 days (n = 24) or digoxin 0.25 mg twice daily × 2 days and once daily × 5 days (n = 24) and then concomitantly for 7 days. Serial blood and urine samples were collected for digoxin and edoxaban concentrations on days 7 and 14. Serial coagulation assays were measured for edoxaban on days 7 and 14. Edoxaban PK parameters demonstrated mild increases in area under the curve and peak concentrations of 9.5% and 15.6%, respectively, when coadministered with digoxin. Although digoxin PK parameters demonstrated increased area under the curve and peak concentrations of 8.3% and 28%, respectively, plasma concentrations were within the established therapeutic range. Edoxaban PD were consistent with PK. Both drugs were well tolerated alone or in combination. No clinically significant changes in PK, PD, or renal elimination were observed with concomitant administration of edoxaban and digoxin.