Assessment of Aging-Related Function Variations of P-gp Transporter in Old-Elderly Chinese CHF Patients Based on Modeling and Simulation.

BACKGROUND AND OBJECTIVES: P-glycoprotein (P-gp) is one of the most intensely studied transporters owing to its broad tissue distribution and substrate specificity. Existing research suggests that the risk of systemic exposure to dabigatran etexilate (DABE) and digoxin, two P-gp probe substrates in vivo, has significantly increased in elderly patients. We applied a model-based quantitative pharmacological approach to assess aging-related P-gp changes in the Chinese old-elderly population. METHODS: Population pharmacokinetic (PopPK) modeling was first performed using clinical pharmacokinetic data to explore the effect of age on the pharmacokinetic characteristics of dabigatran (DAB, the active principle of DABE) and digoxin in elderly Chinese patients. Corresponding physiologically based pharmacokinetic (PBPK) models were established to further explain the elevated systemic exposure to these two drugs. Eventually, standard dosing regimens of DABE and digoxin were assessed in Chinese old-elderly patients with chronic heart failure (CHF) with different stages of renal impairment. RESULTS: PopPK analysis suggested that age as a covariate had an additional effect on the apparent clearance of these two drugs after correcting for creatinine clearance. PBPK simulation results suggested that disease-specific pathophysiological changes could explain DAB exposure in the young elderly. In the elderly population, 17.1% of elevated DAB exposure remained unexplained, and 25.5% of the reduced P-gp function associated with aging was ultimately obtained using sensitivity analysis. This value was further validated using digoxin data obtained by PBPK modeling. The simulation results suggest that CHF patients with advanced age and moderate-to-severe renal impairment require heightened vigilance for elevated exposure risk during the use of DABE and digoxin. CONCLUSIONS: Aging might be a significant risk factor for elevated systemic exposure to DAB and digoxin by reducing P-gp-mediated efflux in the Chinese old elderly population.

Assessment of Drug-Drug Interactions between Taspoglutide, a Glucagon-Like Peptide-1 Agonist, and Drugs Commonly Used in Type 2 Diabetes Mellitus: Results of Five Phase I Trials.

BACKGROUND AND OBJECTIVE: Taspoglutide, a glucagon-like peptide-1 agonist, like native glucagon-like peptide-1, delays gastric emptying time and prolongs intestinal transit time, which may alter the pharmacokinetics of concomitantly administered oral drugs. The effect of taspoglutide on the pharmacokinetics of five oral drugs commonly used in patients with type 2 diabetes mellitus was assessed in healthy subjects. METHODS: Five clinical pharmacology studies evaluated the potential drug-drug interaction between multiple subcutaneous taspoglutide doses and a single dose of lisinopril, warfarin, and simvastatin and multiple doses of digoxin and an oral contraceptive containing ethinylestradiol and levonorgestrel. The extent of interaction was quantified using geometric mean ratios and 90% confidence intervals for the maximum plasma concentration and area under the plasma concentration-time curve. In addition to pharmacokinetics, pharmacodynamic effects were assessed for warfarin and the oral contraceptive. RESULTS: Among the tested drugs, the effect of taspoglutide on the pharmacokinetics of simvastatin was most pronounced, on the day of taspoglutide administration, the average exposure to simvastatin was decreased by - 26% and - 58% for the area under the plasma concentration-time curve and maximum plasma concentration, respectively, accompanied by an increase in average exposure to its active metabolite, simvastatin ß-hydroxy acid (+ 74% and + 23% for area under the plasma concentration-time curve and maximum plasma concentration, respectively). Although statistically significant changes in exposure were observed for other test drugs, the 90% confidence intervals for the geometric mean ratio for maximum plasma concentration and area under the plasma concentration-time curve were within the 0.7-1.3 interval. No clinically relevant changes on coagulation (for warfarin) and ovulation-suppressing activity (for the oral contraceptive) were apparent. CONCLUSION: Overall, multiple doses of taspoglutide did not result in changes in the pharmacokinetics of digoxin, an oral contraceptive containing ethinylestradiol and levonorgestrel, lisinopril, warfarin, and simvastatin that would be considered of clinical relevance. Therefore, no dose adjustments are warranted upon co-administration.

An ECV304 monoculture model for permeability assessment of blood-brain barrier.

OBJECTIVE: ECV304/C6 co-culture model is a widely used tool for BBB studies. However, cell source may influence the establishment of co-culture model and some C6 cells could damage the barrier integrity. Here, we established an ECV304 monoculture model and evaluated it in the respect of tightness, tight junction proteins and discriminative brain penetration. METHODS: The tightness of ECV304 cell layers was evaluated by the measurement of permeability to hydrophilic marker Lucifer yellow. Immunofluorescence method was explored to detect the expression of tight junction proteins occludin, claudin-5 and ZO-1 in ECV304 cells. The discriminative brain penetration of the model was assessed by a permeability testing of compounds with different penetration rates, including digoxin, quinidine, and propranolol. RESULTS: The ECV304 monolayers developed low permeability to Lucifer yellow (permeability coefficient: 0.31 ± 0.02 × 10-3 cm/min) and exhibited positive immunostaining of occludin, claudin-5 and ZO-1. The permeability coefficients of high permeable quinidine and propranolol across ECV304 cell layers were higher than that of low permeable digoxin by 3.6 and 2.8-fold, respectively. CONCLUSIONS: The ECV304 monoculture model developed tight paracellular barrier and discriminated between compounds with different permeability, indicating it as a potential in vitro model for BBB permeability assessment.

Assessment of Pharmacokinetic Interactions Between Obeticholic Acid and Caffeine, Midazolam, Warfarin, Dextromethorphan, Omeprazole, Rosuvastatin, and Digoxin in Phase 1 Studies in Healthy Subjects.

INTRODUCTION: Obeticholic acid (OCA), a potent and selective farnesoid X receptor agonist, is indicated for the treatment of primary biliary cholangitis (PBC). We investigated the potential drug-drug interaction effect of OCA on metabolic CYP450 enzymes and drug transporters. METHODS: Five phase 1 single-center, open-label, fixed-sequence, inpatient studies were conducted in healthy adult subjects to evaluate the effect of oral daily doses of 10 or 25 mg OCA on single-dose plasma pharmacokinetics of specific probe substrates for enzymes CYP1A2 (caffeine, R-warfarin), CYP3A (midazolam, R-warfarin), CYP2C9 (S-warfarin), CYP2D6 (dextromethorphan), CYP2C19 (omeprazole), and drug transporters, BCRP/OATP1B1/OATP1B3 (rosuvastatin), and P-gp (digoxin). RESULTS: OCA showed no substantial suppression/inhibition of S-warfarin, digoxin, and dextromethorphan and weak interactions with caffeine, omeprazole, rosuvastatin, and midazolam. The maximal pharmacodynamic responses (E max) to warfarin-based INR, PT, and aPTT were reduced by 11%, 11%, and 1%, respectively, for the 10-mg dose group and by 7%, 7% and 0%, respectively, for the 25-mg dose group. Overall, drugs dosed in combination with OCA were well tolerated, and most adverse events were mild in severity. No clinically important trends were noted in laboratory evaluations, vital signs, or 12-lead ECGs. CONCLUSION: In these studies, OCA showed weak to no suppression/inhibition of metabolic enzymes and drug transporters at the highest recommended therapeutic dose in patients with PBC. On the basis on these analyses, monitoring and maintenance of target INR range are required during coadministration of OCA with drugs that are metabolized by CYP1A2 (R-warfarin). FUNDING: Intercept Pharmaceuticals, Inc.

Pharmacokinetic monitoring of chronic treatment with digoxin from Primary Health Care.

INTRODUCTION: The serum digoxin concentration (SDC) should be between 0.8 and 2 ng/ml. The objective is to assess the pharmacokinetic monitoring of SDC performed from primary healthcare (PH) in patients with chronic treatment. METHODS: Cross-sectional retrospective study of patients with chronic treatment with digoxin belonging to the department of a General University Hospital.Data were analized: age, sex, diagnosis, number of serum digoxin concentration determinations, date and origin of the request for monitoring, analytical result and pharmacokinetic assessment are collected. RESULTS: 624 patients are undergoing chronic treatment with digoxin, 68% women, mean age 78.4 (39-98) years. 308 (49.4%) patients haven't analytical determination of SDC (Group 1), 183 (29.3%) patients have a SDC occasionally performed with a request from specialist care (Group 2) and 133 (21,3%) patients have CSD performed with a request from primary healthcare doctors, with an average of 2.42 monitoring per patient and year (Group 3). These are those patients who have pharmacokinetic monitoring of chronic treatment with digoxin. Of the group 2.25 (13.6%) patientes were hospital admission from emergency department for presenting digitalis intoxication with CSD>2 ng/ml, and 39 (21.3%) patients for low dosing with CSD<0.5 ng/ml. Group 3.4 (3%) patients presented digitalis intoxication and 5 (3.8%) for insufficient dosing. CONCLUSIONS: A small proportion of patients undergoing chronic treatment with digoxin are under pharmacokinetic monitoring and a reduction in complications derived from inappropriate CSD compared to those not under pharmacokinetic follow-up is observed.

Introducción: La concentración sérica de digoxina (CSD) debe situarse entre 0,8 y 2 ng/ml. El objetivo es valuar el seguimiento farmacocinético de las CSD que se realiza desde Atención Primaria (AP) en pacientes con tratamiento crónico.Métodos: Estudio trasversal observacional retrospectivo de pacientes en tratamiento crónico con digoxina que pertenecen al departamento de un Hospital General Universitario. Se recogen datos de edad, sexo, diagnóstico, número de determinaciones séricas de digoxina realizadas, fecha y origen de la solicitud de monitorización, resultado analítico y valoración farmacocinética. (Infradosificación, normodosificación o supradosificación).Resultados: 624 pacientes están en tratamiento crónico con digoxina: 68% mujeres, edad media 78,4 (39-98) años. 308 (49,4%) pacientes no tienen realizada ninguna determinación analítica de CSD (Grupo 1), 183 (29,3%) pacientes tienen CSD realizadas de manera esporádica con solicitud tramitada desde Atención Especializada (Grupo 2) y 133 (21,3%) pacientes tienen CSD realizadas de manera periódica con solicitud cursada por médicos de AP, con un promedio de 2,42 monitorizaciones por paciente y año (Grupo 3). Estos son los que tienen un seguimiento farmacocinético del tratamiento crónico con digoxina.Del Grupo 2,2(13,6%) entran por el Servicio de Urgencias por presentar intoxicación digitálica con CSD>2 ng/ml, y 39 (21,3%) pacientes por baja dosificación con CSD<0,5ng/ml. Del Grupo 3,4 (3%) presentan intoxicación digitálica y 5 (3,8%) infradosificación.Conclusiones: Una pequeña parte de los pacientes que se encuentran en tratamiento crónico con digoxina están en seguimiento farmacocinético. Se observa una reducción de las complicaciones derivadas de CSD inapropiadas con respecto a los que no están en seguimiento farmacocinético.

Clinical drug-drug interaction assessment of ivacaftor as a potential inhibitor of cytochrome P450 and P-glycoprotein.

Ivacaftor is approved in the USA for the treatment of cystic fibrosis (CF) in patients with a G551D-CFTR mutation or one of eight other CFTR mutations. A series of in vitro experiments conducted early in the development of ivacaftor indicated ivacaftor and metabolites may have the potential to inhibit cytochrome P450 (CYP) 2C8, CYP2C9, CYP3A, and CYP2D6, as well as P-glycoprotein (P-gp). Based on these results, a series of clinical drug-drug interaction (DDI) studies were conducted to evaluate the effect of ivacaftor on sensitive substrates of CYP2C8 (rosiglitazone), CYP3A (midazolam), CYP2D6 (desipramine), and P-gp (digoxin). In addition, a DDI study was conducted to evaluate the effect of ivacaftor on a combined oral contraceptive, as this is considered an important comedication in CF patients. The results indicate ivacaftor is a weak inhibitor of CYP3A and P-gp, but has no effect on CYP2C8 or CYP2D6. Ivacaftor caused non-clinically significant increases in ethinyl estradiol and norethisterone exposure. Based on these results, caution and appropriate monitoring are recommended when concomitant substrates of CYP2C9, CYP3A and/or P-gp are used during treatment with ivacaftor, particularly drugs with a narrow therapeutic index, such as warfarin.

Pharmacokinetic and pharmacodynamic drug-drug interaction assessment between pradigastat and digoxin or warfarin.

Pradigastat, a novel diacylglycerol acyltransferase-1 inhibitor, was evaluated for both pharmacokinetic (PK) and pharmacodynamic (PD) drug-drug interactions when co-administered with digoxin or warfarin in healthy subjects. This open-label study included two parallel subject cohorts each with three sequential treatment periods. Forty subjects were enrolled in the study with 20 subjects allocated to each cohort. PK and PD (PT/INR for warfarin only) samples were collected in each period. The statistical analysis results showed that the 90% CIs of the geometric mean ratios of digoxin, R-warfarin, and S-warfarin PK parameters (AUC and Cmax) were all within 0.80-1.25 interval. The 90% CIs of the geometric mean ratios of pradigastat PK parameters (AUC and Cmax) were within 0.80-1.25 interval when co-administered with warfarin; while co-administration with digoxin slightly reduced pradigastat exposure (∼15%). The results also showed that 90% CIs of the geometric mean ratios of warfarin PD parameters (AUC(PT), PTmax, AUC(INR), and INRmax) were within 0.80-1.25 interval. Pradigastat and digoxin or warfarin had no relevant clinical PK or PD drug-drug interactions. Administration of pradigastat and warfarin or pradigastat and digoxin as a mono or combined treatment appears to be safe and tolerated.

Variability in P-glycoprotein inhibitory potency (IC50) using various in vitro experimental systems: implications for universal digoxin drug-drug interaction risk assessment decision criteria.

A P-glycoprotein (P-gp) IC50 working group was established with 23 participating pharmaceutical and contract research laboratories and one academic institution to assess interlaboratory variability in P-gp IC50 determinations. Each laboratory followed its in-house protocol to determine in vitro IC50 values for 16 inhibitors using four different test systems: human colon adenocarcinoma cells (Caco-2; eleven laboratories), Madin-Darby canine kidney cells transfected with MDR1 cDNA (MDCKII-MDR1; six laboratories), and Lilly Laboratories Cells--Porcine Kidney Nr. 1 cells transfected with MDR1 cDNA (LLC-PK1-MDR1; four laboratories), and membrane vesicles containing human P-glycoprotein (P-gp; five laboratories). For cell models, various equations to calculate remaining transport activity (e.g., efflux ratio, unidirectional flux, net-secretory-flux) were also evaluated. The difference in IC50 values for each of the inhibitors across all test systems and equations ranged from a minimum of 20- and 24-fold between lowest and highest IC50 values for sertraline and isradipine, to a maximum of 407- and 796-fold for telmisartan and verapamil, respectively. For telmisartan and verapamil, variability was greatly influenced by data from one laboratory in each case. Excluding these two data sets brings the range in IC50 values for telmisartan and verapamil down to 69- and 159-fold. The efflux ratio-based equation generally resulted in severalfold lower IC50 values compared with unidirectional or net-secretory-flux equations. Statistical analysis indicated that variability in IC50 values was mainly due to interlaboratory variability, rather than an implicit systematic difference between test systems. Potential reasons for variability are discussed and the simplest, most robust experimental design for P-gp IC50 determination proposed. The impact of these findings on drug-drug interaction risk assessment is discussed in the companion article (Ellens et al., 2013) and recommendations are provided.

A simplified protocol employing elacridar in rodents: a screening model in drug discovery to assess P-gp mediated efflux at the blood brain barrier.

In the present study we have developed a simple, time, and cost effective in vivo rodent protocol to screen the susceptibility of a test compound for P-glycoprotein (P-gp) mediated efflux at the blood brain barrier (BBB) during early drug discovery. We used known P-gp substrates as test compounds (quinidine, digoxin, and talinolol) and elacridar (GF120918) as a chemical inhibitor to establish the model. The studies were carried out in both mice and rats. Elacridar was dosed intravenously at 5 mg/kg, 0.5 h prior to probe substrate administration. Plasma and brain samples were collected and analyzed using UPLC-MS/MS. In the presence of elacridar, the ratio of brain to plasma area under the curve (B/P) in mouse increased 2, 4, and 38-fold, respectively, for talinolol, digoxin, and quinidine; whereas in rat, a 70-fold increase was observed for quinidine. Atenolol, a non P-gp substrate, exhibited poor brain penetration in the presence or absence of elacridar in both species (B/P ratio ~ 0.1). Elacridar had no significant effect on the systemic clearance of digoxin or quinidine; however, a trend towards increasing volume of distribution and half life was observed. Our results support the utility of elacridar in evaluation of the influence of P-gp mediated efflux on drug distribution to the brain. Our protocol employing a single intravenous dose of elacridar and test compound provides a cost effective alternative to expensive P-gp knockout mice models during early drug discovery.

Non-linear mixed effects modeling - from methodology and software development to driving implementation in drug development science.

Few scientific contributions have made significant impact unless there was a champion who had the vision to see the potential for its use in seemingly disparate areas-and who then drove active implementation. In this paper, we present a historical summary of the development of non-linear mixed effects (NLME) modeling up to the more recent extensions of this statistical methodology. The paper places strong emphasis on the pivotal role played by Lewis B. Sheiner (1940-2004), who used this statistical methodology to elucidate solutions to real problems identified in clinical practice and in medical research and on how he drove implementation of the proposed solutions. A succinct overview of the evolution of the NLME modeling methodology is presented as well as ideas on how its expansion helped to provide guidance for a more scientific view of (model-based) drug development that reduces empiricism in favor of critical quantitative thinking and decision making.

Concurrent administration of donepezil HCl and digoxin: assessment of pharmacokinetic changes.

AIM: The aim of this study was to examine the pharmacokinetics of donepezil HCl and digoxin separately, and in combination, following administration of single oral doses. Changes in cardiac conduction parameters following drug administration were also assessed. METHODS: This was an open-label, randomized, three-period crossover study in healthy male volunteers (n=12). During each treatment period, subjects received a single dose of either donepezil HCl (5 mg), digoxin (0.25 mg), or a combination of both drugs. Each treatment period was followed by a 2-week, drug-free washout period. RESULTS: All 12 volunteers completed the study without incident. No statistically significant differences in donepezil pharmacokinetics (Cmax, tmax, AUC(0-120), AUC(0-infinity) or t1/2) were observed when donepezil administered alone was compared with donepezil administered in combination with digoxin. Similarly, no statistically significant differences in digoxin pharmacokinetics were observed when digoxin was administered alone or in combination with donepezil. No clinically relevant changes in cardiac conduction (lead II ECG) were observed in any subject during any treatment period. CONCLUSIONS: Co-administration of single doses of donepezil HCl (5 mg) and digoxin (0.25 mg) produced no changes in the pharmacokinetic profile of either drug. In addition, co-administration produced no changes in cardiac conduction parameters during the 24 h of telemetry monitoring following drug administration.

Assessment of pharmacokinetic and pharmacodynamic drug interactions between nefazodone and digoxin in healthy male volunteers.

The effect of nefazodone on pharmacokinetic and pharmacodynamic parameters of digoxin were evaluated in an open, randomized, multiple-dose, three-way crossover study of 18 healthy male volunteers. The volunteers received nefazodone alone (200 mg twice daily), digoxin alone (0.2 mg daily), or nefazodone combined with digoxin during three 8-day treatment periods, with a single dose on the ninth day. There was a 10-day washout period between treatment periods. Coadministration of nefazodone with digoxin had no effect on the frequency and severity of adverse events compared with those observed with either drug alone. Steady-state area under the concentration-time curve (AUC) and peak (Cmax) and trough (Cmin) concentrations of digoxin were significantly higher (15%, 29%, and 27%, respectively) after coadministration of nefazodone/digoxin than after administration of digoxin. Despite these increases, no clinically significant changes in vital signs, heart rate, or PR, QRS, and QT intervals on the electrocardiogram occurred after coadministration from those measured after digoxin monotherapy. Coadministration did not affect the pharmacokinetics of nefazodone or its metabolites (hydroxynefazodone, m-chlorophenylpiperazine, triazole dione). Because digoxin has a narrow therapeutic index, monitoring of plasma digoxin levels and appropriate adjustment of dosage are recommended when nefazodone and digoxin are administered concurrently.

Inhibition of Na(+)-K(+)-ATPase by digoxin and its relation with energy expenditure and nutrient oxidation rate.

This study investigates the effects of digoxin, an inhibitor of the Na+ pump (Na(+)-K(+)-ATPase), on resting metabolic rate (RMR), respiratory quotient (RQ), and nutrient oxidation rate. Twelve healthy male subjects followed a double-blind protocol design and received either 1 mg/day digoxin or a placebo 2 days before indirect calorimetry measurements. Digoxin induced a 0.22 +/- 0.07 kJ/min or 3.8 +/- 1.5% (mean +/- SE, P = 0.01) decrease in RMR and a 0.40 +/- 0.13 kJ/min (P = 0.01) decrease in fat oxidation rate, whereas carbohydrate and protein oxidation rates did not change significantly. A dose-response relationship between serum digoxin and RQ was observed. These results suggest that digoxin reduces not only RMR but also fat oxidation rate by mechanisms that remain to be elucidated. Because a linkage and an association between genes coding the Na(+)-K(+)-ATPase and the RQ have been previously observed, the present demonstration of an effect of Na(+)-K(+)-ATPase inhibition on fat oxidation rate strengthens the concept that the activity of this enzyme may play a role in body weight regulation.

Assessment of the pharmacokinetic interaction between zileuton and digoxin in humans.

The effects of coadministration of zileuton on the pharmacokinetic profile of digoxin were investigated in a double-blind placebo-controlled crossover study in 12 healthy male volunteers. During each study phase, the subjects received zileuton 600mg every 6 hours (regimen A) or placebo (regimen B) for 13 days. In addition, all subjects received concomitant digoxin 0.25 mg/day on study days 1 to 11 during both study phases. The study results provide no evidence of any significant overall effect of zileuton on digoxin plasma concentration-time profiles. Although the mean time to reach the maximum plasma concentration for digoxin was significantly shorter after concomitant administration of digoxin and zileuton than after concomitant administration of digoxin and placebo (0.95 vs 1.43 hours), there were no significant differences between the 2 regimens in the values for maximum plasma concentration, area under the plasma concentration-time curve from 0 to 24 hours, elimination half-life, oral clearance, and apparent volume of distribution associated with the terminal phase. Therefore, it is concluded that digoxin and zileuton may be coadministered without risk of clinically relevant effects on the pharmacokinetic profile of digoxin.

A clinical assessment of the potential for pharmacological interaction between nimesulide and digoxin in patients with heart failure.

The potential interaction between nimesulide, a nonsteroidal anti-inflammatory drug, and digoxin was studied in 9 patients [6 males, 3 females; mean age 67 (range 57 to 70) years] with mild heart failure. All patients were receiving maintenance therapy with digoxin (0.25 mg/day, orally) and were treated with oral nimesulide 100mg twice daily for 7 days. Blood samples were collected at 8am and 6pm for 4 days before and throughout the nimesulide treatment period for determination of serum digoxin concentrations. Physical health, electrocardiographic recordings and blood and urine samples were also monitored. Mean serum digoxin concentrations remained within the normal therapeutic range throughout the study despite large interindividual variation. Furthermore, there were no significant differences between the morning and afternoon serum digoxin concentrations and there was no major change in the clinical condition of any patient. These results indicate that short term administration (7 days) of conventional therapeutic doses of nimesulide (100mg twice daily) does not modify the serum digoxin profile in patients with low class heart failure treated with a maintenance dose (0.25 mg/day) of this cardiac glycoside.

An assessment of population-based and Bayesian methods to individualize digoxin doses shortly after the start of therapy for atrial fibrillation.

The accuracy of population-based methods and of Bayesian analysis to predict individual digoxin pharmacokinetic variables have been evaluated by their ability to predict a measured peak and trough serum digoxin concentration. We studied 13 digitalized patients (three women) whose mean (range) age and weight was 65.8 (60-78) years and 76.6 (68-101.6) kg and who had stable renal function. The population-based methods (using a clearance of 48.87 + 0.87 x creatinine clearance in ml/h/kg and volume of distribution, in litres, of either 7.3 x weight (kg) or 269 + 3.12 x creatinine clearance) were more than adequate for clinical purposes. The mean prediction errors of a measured steady-state peak concentration from these two population methods were -0.074 and 0.013 microgram/l respectively, whilst those of a measured trough concentration were -0.058 and 0.005 microgram/l. Bayesian analysis, using a sample drawn 11 h after the dose on day five of therapy, gave overall the least biased and most precise of the revised estimates. The mean prediction errors of peak and trough values using this sample were 0.069 and -0.005 microgram/l respectively. As expected, the closer the sample was drawn to the time of the trough concentration the more precise were the Bayesian-derived predictions. The value of the Bayesian technique to individualize digoxin doses could not be validated because it was not possible to distinguish between this and the population methods.(ABSTRACT TRUNCATED AT 250 WORDS)

Making digoxin therapeutic drug monitoring more effective.

Digoxin is an important drug in the treatment of patients with either congestive heart failure or atrial arrhythmia. Because of its narrow therapeutic range, digoxin serum concentrations are commonly monitored in both inpatients and outpatients. However, with the costs of health care skyrocketing, there is debate whether such therapeutic drug monitoring (TDM) is cost-effective. To reduce the number of samples drawn too soon after a previous dose and in an effort to improve digoxin TDM at this teaching hospital, a new dosing and monitoring policy was initiated. This policy involved uniform digoxin dosing at 5 p.m. (1700 h) for all inpatients and serum drug measurements at 7 a.m. (0700 h) the next day. By coordinating the time of dosing to be greater than 12 h prior to serum digoxin analysis, the number of inappropriate digoxin serum determinations have been reduced. This new protocol has increased the effectiveness of the toxicology laboratory and enhanced the efficiency of the house staff. Other issues concerning digoxin TDM are also addressed. These findings can be generalized to all drugs that are monitored at any hospital and can result in a significant cost savings and decrease the time spent analyzing inappropriate data.