Population-based investigation of relative clearance of digoxin in Japanese patients by multiple trough screen analysis: an update

Influence of Weight and Body Size on the Pharmacokinetics of Heart Failure Pharmacotherapy: A Systematic Review

OBJECTIVE

To conduct a review of studies evaluating the influence of body size and weight (WT) on the pharmacokinetics (PK) of drugs recommended for heart failure (HF) treatment.

DATA SOURCES

A systematic search of the MEDLINE (1946 to April 2023) and EMBASE (1974 to April 2023) databases was conducted for articles that focused on the impact of WT or body size on the PK of drugs of interest used in HF patients.

STUDY SELECTION AND DATA EXTRACTION

Articles written in English or French related to the aim of our study were retained for analysis.

DATA SYNTHESIS

Of 6493 articles, 20 were retained for analysis. Weight was associated with the clearance of digoxin, carvedilol, enalapril, and candesartan as well as the volume of distribution of eplerenone and bisoprolol. There was no documented direct impact of WT on the PK of furosemide, valsartan, and metoprolol, although these studies were limited or confounded by the small sample size, adjustment of PK factors by WT, or the use of the Cockroff-Gault equation for the evaluation of creatinine clearance, which includes WT.

RELEVANCE TO PATIENT CARE AND CLINICAL PRACTICE

This review highlights and summarizes the available data on the importance of WT on the PK of HF treatment.

CONCLUSION

Considering the significant impact of WT on most HF drugs in this review, it may be important to further investigate it in the context of personalized therapy, particularly in patients presenting extreme WTs.

Population Pharmacokinetics of Digoxin in Nonagenarian Patients: Optimization of the Dosing Regimen

OBJECTIVE

The aim of this study was to develop a population pharmacokinetic model of digoxin in patients over 90 years old and to propose an equation for adjusting digoxin dose in this population.

METHODS

We included 326 nonagenarian patients admitted to Severo Ochoa University Hospital (Spain) who received digoxin and were under therapeutic drug monitoring. All data were retrospectively collected, and population modeling was performed with non-linear mixed-effect modeling software (NONMEM®). One- and two-compartment models were tested to calculate digoxin clearance (Cl), volume of distribution (Vd), absorption rate constant (Ka), and bioavailability (bioavailable fraction, F). The covariates were evaluated by stepwise covariate model building, and the final model was internally validated by bootstrap analysis with 1000 resamples. External validation was performed with another population of 95 patients with the same characteristics as the modeling group.

RESULTS

The population was 26% males, with a mean age of 93.2 years (90-103 years), mean creatinine 1.11 mg/dL (0.42-3.81 mg/dL), and mean total body weight 61.2 kg (40-100 kg). The pharmacokinetics of digoxin were best described by a one-compartment model (ADVAN2 TRANS2), with first-order conditional estimation with interaction. The covariates with influence on our model were creatinine clearance based on the Cockcroft-Gault equation (CG), serum potassium (K), co-administration of loop diuretics, and sex: Cl/F = 4.55 · (CG/36.4)0.468 · 0.83LD · 1.21SEX; Vd/F = 355 · (K/4.3)-0.849; Ka = 1.22 h-1 [where LD indicates loop diuretics (1 for administered, 0 for otherwise) and SEX indicates patient sex (1 for male, 0 for female)]. Based on our results, we proposed an equation to adjust the digoxin dosing regimen in nonagenarian patients: dose (mg) = 0.144 · (CG/36.4)0.468 · 0.83LD · 1.21SEX.

CONCLUSIONS

The greatest influence on digoxin clearance came from renal function calculated by the Cockcroft-Gault equation. Vd was decreased by K. The model developed showed a precise predictive performance to be applied for therapeutic drug monitoring.

Pharmacokinetics Parameters of Diagoxin among Saudi Patients in Qassim Region, Saudi Arabia

BACKGROUND

The pharmacodynamic effects of digoxin are susceptible to multiple factors, most notably, heart uptake of the digoxin dose and its concentration in the serum. Another important factor to mention is the renal function state of an individual.

OBJECTIVE

In this study, we aimed to develop a simple algorithm based on subsets of clinically relevant information, which will help to personalize digoxin based on pharmacokinetic (PK) approach, which can help on marketing the appropriate utilization of this medication.

METHOD

This was a retrospective chart review and analysis of 48 patients who were admitted to the Drug and Poison Information Center in Buraidah, Saudi Arabia, between January 2016 and April 2019. All pharmacokinetic parameters were added according to the C-peaks and C-troughs. MONOLiX® was used for pharmacokinetic data analysis.

RESULTS

Twenty-seven (56%) were males, and twenty-one (44%) were females with an average age of 63.6 years across both genders. The mean volume of distribution was 496.6 litres with an average clearance of 6.6 L/h. For females, their average volume of distribution was slightly higher than that for males (526 litres compared to 473 liters). In addition, the clearance rate between both genders showed a 2.1 litre/hour discrepancy (7.8 L/h for females compared to 5.7 L/h for males).

CONCLUSION

In order to individualize the digoxin dosage regimens, this model can be used to predict digoxin serum concentration. Further studies are needed to clarify the effects of nutritional status and co-administration of medications on digoxin pharmacokinetics.

Reduced theophylline clearance due to hepatic congestion secondary to right heart failure - A population pharmacokinetic study

Theophylline, a beneficial drug with bronchodilatory and anti-inflammatory effects, is used for the treatment of respiratory diseases. Pulmonary (PC) and hepatic congestion (HC) are secondary to the development of left- and right-sided heart failure (HF), respectively. This study aimed to evaluate the effects of PC and HC on theophylline clearance (CL) by population pharmacokinetic (PPK) analysis with consideration of the severity of HF assessed by the New York Heart Association (NYHA) functional classification. We obtained 710 minimum steady-state concentrations from 201 Japanese bronchial asthma patients with and without HF. PPK analysis was performed by NONMEM. In the analysis, the left ventricular ejection fraction, smoking (SMK), clarithromycin (CAM), sex, and age were also considered as covariates. The final model of apparent theophylline clearance (CL/F) was as follows: CL/F (L/hr/kg) = 0.0465 × 1.40^SMK × 0.870^CAM × 0.863^{HC(+)NYHA II} × 0.634^{HC(+)NYHA III} × 0.586^{HC(-)NYHA IV} × 0.467^{HC(+)NYHA IV}. SMK is a well-known factor that markedly enhances theophylline clearance through the induction of CYP1A enzymes, while CAM has been reported to inhibit CYP3A4. The final model indicates that HF patients with HC show reduced clearance of theophylline depending on the severity of HF. In this study, no effects of PC were observed.

Sex- and Gender-Based Pharmacological Response to Drugs

In humans, the combination of all sex-specific genetic, epigenetic, and hormonal influences of biologic sex produces different in vivo environments for male and female cells. We dissect how these influences of sex modify the pharmacokinetics and pharmacodynamics of multiple drugs and provide examples for common drugs acting on specific organ systems. We also discuss how gender of physicians and patients may influence the therapeutic response to drugs. We aim to highlight sex as a genetic modifier of the pharmacological response to drugs, which should be considered as a necessary step toward precision medicine that will benefit men and women. SIGNIFICANCE STATEMENT: This study discusses the influences of biologic sex on the pharmacokinetics and pharmacodynamics of drugs and provides examples for common drugs acting on specific organ systems. This study also discusses how gender of physicians and patients influence the therapeutic response to drugs.

Population Pharmacokinetic Studies of Digoxin in Adult Patients: A Systematic Review

BACKGROUND

Digoxin is a cardiac glycoside that was introduced to cardiovascular medicine more than 200 years ago. Its use is associated with large variability, which complicates achieving the desired therapeutic outcomes.

OBJECTIVES

To present a synthesis of the available literature on the population pharmacokinetics of digoxin in adults and to identify the sources of variability in its pharmacokinetics.

METHODS

This is a PROSPERO registered systematic review (CRD42018105300). A literature search was conducted using the ISI Web of Science, Science Direct, PubMed, and SCOPUS databases to identify digoxin population pharmacokinetic studies of adults that utilized the nonlinear mixed-effect modeling approach.

RESULTS

Sixteen articles were included in the present analysis. Only two studies were conducted in elderly subjects as a separate population. Both the pharmacokinetics and pharmacodynamics of digoxin were investigated in one study. Furthermore, the reviewed studies were mostly conducted in East Asian populations (68.8%). Digoxin's pharmacokinetics were usually described by a one-compartment model because of the nature of the collected data. Weight, age, kidney function, presence of heart failure, and co-administered medications such as calcium channel blockers were the most commonly identified predictors of digoxin clearance. The value of apparent clearance in a typical study individual ranged from 0.005 to 0.2 l/h/kg, while the value of the apparent volume of distribution ranged from 3.14 to 15.2 l/kg. The quality of model evaluation was deemed excellent only in 31.3% of the studies.

CONCLUSION

This review provides information about variables that need to be considered when prescribing digoxin. The results highlight the need for prospective studies that allow two-compartment pharmacokinetic/pharmacodynamic models to be established, with a special focus on the elderly subpopulation.

A systematic review of population pharmacokinetic analyses of digoxin in the paediatric population

This is a PROSPERO registered systematic review (CRD42018105207), conducted to summarize the available knowledge regarding the population pharmacokinetics of digoxin in paediatrics and to identify the sources of variability in its disposition. PubMed, ISI Web of Science, SCOPUS and Science Direct databases were searched from inception to January 2019. All paediatric population pharmacokinetic studies of digoxin that utilized the nonlinear mixed-effect modelling approach were incorporated in this review, and data were synthesized descriptively. After application of the inclusion-exclusion criteria 8 studies were included. Most studies described digoxin pharmacokinetics as a 1-compartment model with only 1 study describing its pharmacokinetics as 2-compartments. Age was an important predictor of clearance in studies involving neonates or infants, other predictors of clearance were weight, height, serum creatinine, coadministration of spironolactone and presence of congestive heart failure. Congestive heart failure was also associated with an increased volume of distribution in 1 study. The estimated value of apparent clearance in a typical individual standardized by mean weight ranged between 0.24 and 0.56 L/h/kg, the interindividual variability in clearance ranged between 7.0 and 35.1%. Half of the studies evaluated the performance of their developed models via external evaluation. In conclusion, substantial predictors of digoxin pharmacokinetics in the paediatric population in addition to model characteristics and evaluation techniques are presented. For clinicians, clearance could be predicted using age especially in neonates or infants, weight, height, serum creatinine, coadministration of medications and disease status. For future researchers, designing pharmacokinetic studies that allow 2-compartment modelling and linking pharmacokinetics with pharmacodynamics is recommended.

Sexual Dimorphism in Drug Metabolism and Pharmacokinetics

Background:

Sex and gender-based differences are observed well beyond the sex organs and affect several physiological and biochemical processes involved in the metabolism of drug molecules. It is essential to understand not only the sex and gender-based differences in the metabolism of the drug but also the molecular mechanisms involved in the regulation of drug metabolism for avoiding sex-related adverse effects of drugs in the human.

Method:

The articles on the sex and gender-based differences in the metabolism of drug molecules were retrieved from the Pub Med database. The articles were classified into the metabolism of the drug molecule, gene expression regulation of drug-metabolizing enzymes, the effect of sex hormones on the metabolism of drug, expression of drugmetabolizing enzymes, etc.

Result:

Several drug molecules are known, which are metabolized differently in males and females. These differences in metabolism may be due to the genomic and non-genomic action of sex hormones. Several other drug molecules still require further evaluation at the molecular level regarding the sex and gender-based differences in their metabolism. Attention is also required at the effect of signaling cascades associated with the metabolism of drug molecules.

Conclusion:

Sex and gender-based differences in the metabolism of drugs exist at various levels and it may be due to the genomic and non-genomic action of sex hormones. Detailed understanding of the effect of sex and related condition on the metabolism of drug molecules will help clinicians to determine the effective therapeutic doses of drugs dependingon the condition of patient and disease.

The influence of heart failure on the pharmacokinetics of cardiovascular and non-cardiovascular drugs: a critical appraisal of the evidence

Prescribing in heart failure (HF), a common disease state that predominantly affects the older population, is often a challenging task because of the dynamic nature of the condition, requiring frequent monitoring and medication review, the presence of various comorbidities, and the frailty phenotype of many patients. The significant alterations in various organs and tissues occurring in HF, particularly the reduced cardiac output with peripheral hypoperfusion and the structural and functional changes of the gastrointestinal tract, liver and kidney, might affect the pharmacokinetics of several drugs. This review critically appraises the results of published studies investigating the pharmacokinetics of currently marketed cardiovascular and selected non-cardiovascular drugs in HF patients and control groups, identifies gaps in the current knowledge, and suggests avenues for future research in this complex patient population.

Improvement of Adequate Digoxin Dosage: An Application of Machine Learning Approach

Digoxin is a high-alert medication because of its narrow therapeutic range and high drug-to-drug interactions (DDIs). Approximately 50% of digoxin toxicity cases are preventable, which motivated us to improve the treatment outcomes of digoxin. The objective of this study is to apply machine learning techniques to predict the appropriateness of initial digoxin dosage. A total of 307 inpatients who had their conditions treated with digoxin between 2004 and 2013 at a medical center in Taiwan were collected in the study. Ten independent variables, including demographic information, laboratory data, and whether the patients had CHF were also noted. A patient with serum digoxin concentration being controlled at 0.5-0.9 ng/mL after his/her initial digoxin dosage was defined as having an appropriate use of digoxin; otherwise, a patient was defined as having an inappropriate use of digoxin. Weka 3.7.3, an open source machine learning software, was adopted to develop prediction models. Six machine learning techniques were considered, including decision tree (C4.5), k-nearest neighbors (kNN), classification and regression tree (CART), randomForest (RF), multilayer perceptron (MLP), and logistic regression (LGR). In the non-DDI group, the area under ROC curve (AUC) of RF (0.912) was excellent, followed by that of MLP (0.813), CART (0.791), and C4.5 (0.784); the remaining classifiers performed poorly. For the DDI group, the AUC of RF (0.892) was the best, followed by CART (0.795), MLP (0.777), and C4.5 (0.774); the other classifiers' performances were less than ideal. The decision tree-based approaches and MLP exhibited markedly superior accuracy performance, regardless of DDI status. Although digoxin is a high-alert medication, its initial dose can be accurately determined by using data mining techniques such as decision tree-based and MLP approaches. Developing a dosage decision support system may serve as a supplementary tool for clinicians and also increase drug safety in clinical practice.

Gender Differences in Cardiovascular Drugs

The different responses of women and men to cardiovascular drugs reflect gender -specific variances in pharmacokinetic profiles and drug sensitivities coupled to inherent differences in the underlying physiology of each sex. Thus, many common cardiovascular drugs exhibit gender -specific therapeutic and adverse effects. For example, the QT interval of the electrocardiogram is longer in women compared to men, and accordingly, drugs that prolong the QT interval are more likely to cause lethal ventricular arrhythmias in female than male patients. As more clinical drug trials include women subjects, our improved knowledge base for assessing the risk/benefit ratio for cardiovascular drugs in women will enable us to consider gender as one factor in prescribing drugs and adjusting drug loading and maintenance dosages. This short review will present evidence for gender- related differences in the responses to common cardiovascular drugs including statins, antiplatelet and antithrombotic agents, β-blockers, digoxin, vasodilator therapies, and drugs associated with the Long QT Syndrome.

Sex and gender differences in cardiovascular drug therapy

This chapter outlines sex differences in pharmacokinetics and pharmacodynamics of the most frequently used drugs in cardiovascular diseases, e.g., coronary artery disease, hypertension, heart failure. Retrospective analysis of previously published drug trials revealed marked sex differences in efficacy and adverse effects in a number of cardiovascular drugs. This includes a higher mortality among women taking digoxin for heart failure, more torsade de pointes arrhythmia in QT prolonging drugs and more cough with ACE inhibitors. Trends towards a greater benefit for women and/or female animals have been observed in some studies for endothelin receptor antagonists, the calcium channel blocker amlodipine, the ACE-inhibitor ramipril and the aldosterone antagonist eplerenone. However, reproduction of these results in independent studies and solid statistical evidence is still lacking. Some drugs require a particularly careful dose adaptation in women: the beta-blocker metoprolol, the calcium channel blocker verapamil, loop-, and thiazide diuretics. In conclusion, sex differences in pharmacokinetics and pharmacodynamics have to be taken into account for cardiovascular drug therapy in women.

Population pharmacokinetic model of digoxin in older Chinese patients and its application in clinical practice

AIM

To establish a population pharmacokinetic (PPK) model of digoxin in older Chinese patients to provide a reference for individual medication in clinical practice.

METHODS

Serum concentrations of digoxin and clinically related data including gender, age, weight (WT), serum creatinine (Cr), alanine aminotransferase (ALT), aspartate aminotransferase (AST), blood urea nitrogen (BUN), albumin (ALB), and co-administration were retrospectively collected from 119 older patients taking digoxin orally for more than 7 d. NONMEM software was used to get PPK parameter values, to set up a final model, and to assess the models in clinical practice.

RESULTS

Spironolactone (SPI), WT, and Cr markedly affected the clearance rate of digoxin. The final model formula is Cl/F=5.9x[1-0.412 x SPI] x [1-0.0101x(WT-62.9)] x [1-0.0012x(Cr-126.8)] (L/h); Ka=1.63 (h(-1)); V(d)/F=550 (L). The population estimates for Cl/F and V(d)/F were 5.9 L/h and 550 L, respectively. The interindividual variabilities (CV) were 49.0% for Cl/F and 94.3% for V(d)/F. The residual variability (SD) between observed and predicted concentrations was 0.365 microg/L. The difference between the objective function value and the primitive function value was less than 3.84 (P>0.05) by intra-validation. Clinical applications indicated that the percent of difference between the predicted concentrations estimated by the PPK final model and the observed concentrations were -4.3%-+25%. Correlation analysis displayed that there was a linear correlation between observed and predicted values (y=1.35x+0.39, r=0.9639, P<0.0001).

CONCLUSION

The PPK final model of digoxin in older Chinese patients can be established using the NONMEM software, which can be applied in clinical practice.

Population pharmacokinetic investigation of digoxin in Japanese neonates

OBJECTIVE

To establish the role of patient characteristics in estimating doses of digoxin for neonates using routine therapeutic drug monitoring data.

METHOD

The steady-state blood level data (n = 129) after repetitive oral administration in 71 hospitalized neonates were analysed using Nonlinear Mixed Effects Modelling (nonmem), a computer program designed for analysing drug pharmacokinetics in study populations through pooling of data. Analysis of the pharmacokinetics of digoxin was accomplished using a one-compartment open pharmacokinetic model. The effect of a variety of developmental and demographic factors on digoxin disposition was investigated.

RESULTS

Estimates generated by nonmem indicated that the clearance of digoxin (CL/F; L/h) was influenced by the demographic variables: total body weight (TBW), gestational age (GA) and neonate clearance factor (trough serum concentration of digoxin; Conc). These influences could be modelled by the equation CL/F = 0.0261 x TBW (kg)0.645 x Conc (ng/mL)(-0.724) x GA (weeks)0.8. The interindividual variability in digoxin clearance was modelled with proportional errors. The estimated coefficient of variation was 7.0%, and the residual variability was 13.1%.

CONCLUSION

Clinical application of the model to patient care may permit selection of an appropriate initial maintenance dose, thus enabling the clinician to achieve the desired therapeutic effect. However, the digoxin dosage regimen for the individual patient should be based on a careful appraisal of their clinical need for the drug.

Population pharmacokinetics of digoxin in Egyptian pediatric patients: impact of one data point utilization

A population pharmacokinetic (PK) study was designed to estimate the PK parameters of digoxin among a selected group of Egyptian pediatric patients (n = 30) with mean age +/- SD and body weight +/- SD of 8.88 +/- 3.01 years and 23.9 +/- 5.8 kg, respectively. All patients had heart failure and were maintained on digoxin given orally. Nonlinear mixed effect modeling software version 5 (NONMEM Project Group, San Francisco, CA) and one-compartment modeling were used for fitting the data. A one-trough steady-state plasma concentration level of digoxin was used in the analysis. The population mean estimates for clearance (CL/f) and volume of distribution (V/f), in which f represents oral bioavailability, were 8.61 L/h and 450 L, respectively. Because of the limited number of samples per patient, regression analysis could not detect a correlation between patient covariates and estimated PK parameters. The analysis did not converge to obtain good parameter estimates. At least two samples per patient should be used to improve the PK estimation and allow better analysis of the relation between the potential covariates and estimated PK parameters.

Predictive performance of serum digoxin concentration in patients with congestive heart failure by a hyperbolic model based on creatinine clearance

OBJECTIVES

To formulate a simple equation for determining the daily dose requirements of digoxin by inclusion of creatinine clearance (Ccr) values as an explanatory variable.

METHODS

We included 235 routine monitoring and clinical laboratory test data (steady-state serum digoxin concentration and Ccr values), obtained from hospitalized patients receiving digoxin for treatment of congestive heart failure. The 107 data sets were fitted to a hyperbolic model to account for the relation between the ratio of serum digoxin level to the daily dose (L/D) and the Ccr values determined by six methods. Their correlation coefficients (r) were computed by non-linear regression analysis. To evaluate the validity of the best-fitting model, the predictive performance of the L/D ratios was compared with those given by seven reference models previously published, using another 128 data sets.

RESULTS

The hyperbolic model involving the Ccr values estimated by Cockcroft and Gault's equation showed the closest correlation (r = 0.81) between the actual and estimated Ccr values. Mean prediction error (ME), a measure of bias, of the L/D ratio (0.018 ng/mL) was almost negligible when other data were fitted to the proposed model, and this ME value proved to be much smaller than those calculated from the previously published prediction models. Mean absolute prediction error, a measure of precision, by the proposed model was also satisfactory for prediction.

CONCLUSION

The newly developed model provided good predictive performance of serum digoxin level. Taking simplicity in practical use into account, the clinical application of the proposed model will allow for accurate and rapid determination of the initial maintenance dosing regimen of digoxin based on the individual Ccr value, without actual measurement of its serum concentration.

How important are gender differences in pharmacokinetics?

Gender-related differences in pharmacokinetics have frequently been considered as potentially important determinants for the clinical effectiveness of drug therapy. The mechanistic processes underlying gender-specific pharmacokinetics can be divided into molecular and physiological factors. Major molecular factors involved in drug disposition include drug transporters and drug-metabolising enzymes. Men seem to have a higher activity relative to women for the cytochrome P450 (CYP) isoenzymes CYP1A2 and potentially CYP2E1, for the drug efflux transporter P-glycoprotein, and for some isoforms of glucuronosyltransferases and sulfotransferases. Women were suggested to have a higher CYP2D6 activity. No major gender-specific differences seem to exist for CYP2C19 and CYP3A. The often-described higher hepatic clearance in women compared with men for substrates of CYP3A and P-glycoprotein, such as erythromycin and verapamil, may be explained by increased intrahepatocellular substrate availability due to lower hepatic P-glycoprotein activity in women relative to men. Physiological factors resulting in gender-related pharmacokinetic differences include the generally lower bodyweight and organ size, higher percentage of body fat, lower glomerular filtration rate and different gastric motility in women compared with men. Although gender disparity in pharmacokinetics has been identified for numerous drugs, differences are generally only subtle. For a few drugs, e.g. verapamil, beta-blockers and selective serotonin reuptake inhibitors, gender-related differences in pharmacokinetics have been shown to result in different pharmacological responses, but their clinical relevance remains unproven. In contrast, gender differences of clinical importance have clearly been identified for pharmacodynamic processes such as QTc prolongation, and intensive future research efforts are needed to assess the full scope and impact of pharmacodynamic gender disparity on applied pharmacotherapy.

Pharmacoepidemiologic detection of calcium channel blocker-induced change on digoxin clearance using multiple trough screen analysis

Nonlinear mixed effects modeling was used to estimate the effects of digoxin-calcium channel blockers (verapamil, diltiazem, nifedipine) in 336 serum levels gathered from 172 patients (104 male and 68 female) receiving oral digoxin as hospital in-patients. The final model describing digoxin clearance (CL) was CL (l/day)=(87.9+2.71C(cr))0.872(CCB)0.880(CHF)0.937(SPI)0.854(DFAC), where C(cr) is the estimated creatinine clearance (ml/min); CCB=1 for concomitant administration of calcium channel blockers and CCB=zero otherwise; CHF=1 for the patients with congestive heart failure and CHF=zero otherwise; SPI=1 for concomitant administration of spironolactone and SPI=zero otherwise; DFAC=1 for administration of a half-tablet of digoxin and DFAC=zero otherwise. Concomitant administration of calcium channel blockers resulted in a 13% decrease in digoxin relative clearance.

Population pharmacokinetics of digoxin in Japanese patients: a 2-compartment pharmacokinetic model

OBJECTIVE

To clarify the observed variability of digoxin disposition by performing a population pharmacokinetic analysis in a Japanese population.

DESIGN

Retrospective analysis of clinical pharmacokinetic data.

PATIENTS AND PARTICIPANTS

Data were obtained from 106 patients with heart failure and atrial fibrillation (43 males and 63 females).

METHODS

Digoxin concentrations in serum were measured by fluorescence polarisation immunoassay. Population pharmacokinetic analysis was performed using a 2-compartment open pharmacokinetic model with the computer program NONMEM.

RESULTS

246 serum concentrations were obtained. Final pharmacokinetic parameters were: CL (L/h) = (0.036 x TBW + 0.112 x CL(CR)) x 0.77SPI x 0.784CCB, V1 = 1.83 L/kg, V2 = 22.6 L/kg and Q = 0.629 L/h/kg, where CL is total body clearance, V1 and V2 are the apparent volumes of distribution in the central and peripheral compartments, Q is intercompartmental clearance, TBW is total bodyweight (in kg), CL(CR) is creatinine clearance (in ml/min), SPI = 1 for concomitant administration of spironolactone (and zero otherwise) and CCB = 1 for concomitant administration of calcium antagonists (and zero otherwise). Concomitant administration of digoxin and spironolactone resulted in a 23% decrease in digoxin clearance. Concomitant administration of digoxin and calcium antagonists (diltiazem, nicardipine, nifedipine or verapamil) resulted in a 21.6% decrease in digoxin clearance.

CONCLUSIONS

The estimated population parameter values may assist clinicians in the individualisation of digoxin dosage regimens.

Therapeutic drug monitoring databases for postmarketing surveillance of drug-drug interactions

Drug-drug interactions can be associated with patient morbidity due to either increased toxicity or a potentially ineffective concentration. Because interactions cannot always be anticipated during drug development and actual patients receiving a drug for therapeutic use often differ from those included in clinical trials, postmarketing surveillance is essential. Therapeutic drug monitoring (TDM) databases offer a unique opportunity in this respect. Prerequisites for TDM databases to provide valid information in a pharmacoepidemiological perspective include the following: precise description of exposure to the potentially interacting drugs; measurement of parent compound and active metabolites through accurate and precise analytical techniques; documentation of relevant patient characteristics that may act as confounding factors (e.g. gender, age, smoking habits); repeated assessments over time if possible; and sound pharmacokinetic framework for data selection, analysis and interpretation. The contribution of TDM to the documentation of drug-drug interactions takes advantage of different possible study designs, discussed on the basis of recently published studies. The single case report plays an important role as an alert signal. It is illustrated for a patient on long-term treatment, who displayed an unexpectedly high clozapine concentration after the introduction of ciprofloxacin comedication. The prospective on and off comedication panel study shows advantages in terms of carefully selected inclusion criteria and control of treatment modalities. A study of the thioridazine-fluvoxamine interaction is presented, with patients followed on thioridazine monotherapy, after introduction of fluvoxamine and after its discontinuation. The main advantage of the retrospective large-scale TDM database screen is representativeness of patients actually treated, whereas drawbacks are related to quality of data and suitability for valid interpretation. Such an approach is illustrated by a review of data collected over 10 years of routine TDM that allowed documenting induction of nortriptyline metabolism by carbamazepine and inhibition by several phenothiazines. Finally, population pharmacokinetics is well suited to observational data collected for TDM purpose, provided quality is ascertained. Focus is placed on interindividual variability and relationship between pharmacokinetic parameters and patient characteristics, including comedication. The population approach is discussed with respect to a study that documented a 32% increase of haloperidol clearance associated with anticonvulsant comedication, in addition to effects of age and bodyweight. Among factors to consider for improved effectiveness in the use of TDM databases for postmarketing surveillance of drug-drug interactions, integration of efficacy and safety data in future studies and communication of expert recommendations to prescribing physicians are essential.

Epidemiologic investigation of the relative clearance of haloperidol by mixed-effect modeling using routine clinical pharmacokinetic data in Japanese patients

The steady-state trough concentrations of haloperidol were studied to clarify the role of the characteristics of Japanese patients in estimating haloperidol dosing regimens by using routine therapeutic drug-monitoring data. Nonlinear mixed-effects modeling (NONMEM) was used to estimate the effect of a variety of developmental and demographic factors on haloperidol clearance values using 270 serum level measurements obtained from 191 patients during their clinical course. The final model describing haloperidol's relative clearance was CL = 0.74 x TBW(0.594) x DOSE(0.326) x 1.32CO1 x 0.867AGE, where CL is clearance (measured in liters per hour), TBW is the total body weight (in kilograms), DOSE is the daily dose of haloperidol (in grams per kilogram per day), CO1 = 1 for concomitant administration of antiepileptic drugs (phenobarbital, phenytoin, or carbamazepine) and CO1 = 0 otherwise, and AGE = 1 for patients aged 55 years or older and AGE = 0 otherwise. Concomitant administration of haloperidol and antiepileptic drugs resulted in a 32% increase in haloperidol clearance. Patients aged 55 years or older showed a 13.3% reduction in clearance values compared with the younger population.

Population analysis for the optimization of digoxin treatment in Japanese paediatric patients

BACKGROUND AND OBJECTIVES

Information about the pharmacokinetics of digoxin in paediatric patients is limited. We therefore aimed to investigate the effects of physiological factors on the digoxin clearance in Japanese paediatric patients.

METHOD

We used routinely collected therapeutic drug monitoring data (n=544), derived from the steady-state serum concentrations of digoxin in 181 hospitalized paediatric patients.

RESULTS

Of those physiological factors which have been examined in this study, age and total body weight were most closely correlated with digoxin clearance. Data on neonates within the first postnatal month indicated a tendency towards lower clearance for premature neonates than full-term neonates (P<0.01). Digoxin clearance was reduced by spironolactone in patients younger than 4 months (P<0.05). Patients with congestive heart failure showed a lower digoxin clearance than the others (P<0.001). Serum creatinine and gender did not have a statistically significant effect on digoxin clearance.

CONCLUSION

Age and total body weight are important factors influencing digoxin clearance in children. Spironolactone affected digoxin clearance and needs to be considered when dosing paediatric subjects.

Population-based investigations of drug relative clearance using nonlinear mixed-effect modelling from information generated during the routine clinical care of patients

Interpatient variability in drug disposition and response is a therapeutic premise, and thus evaluation and management of such variability are the basis for individualized pharmacotherapy. If the mathematical approach to determining drug doses were accurate and practical, the use of calculated doses could reduce the potential for toxicity and decrease the need for repetitious drug assays. The major strength of the population pharmacokinetics approach is that useful information can be extracted from sparse data collected during routine clinical care. Population pharmacokinetics can be defined as the study of the variability in serum drug concentrations between individuals when standard dosage regimens are administered. An approach to population pharmacokinetic data analysis has been implemented in the Nonlinear Mixed Effects Model (NONMEM) computer program. This report shows the feasibility of using a simple pharmacokinetic screen approach to estimate the population mean relative drug clearance and detecting drug-drug interaction by use of NONMEM. In clinical application of multiple trough screen or multiple peak screen, the variability of drug relative clearance within the population is assessed and a mathematical relationship between drug relative clearance and individual patient characteristics, such as age, body weight, gender, disease state or drug interaction with concomitant drug is derived. In this report I describe this approach and its application using several examples previously reported by us and others.