Modelling the influence of MDR1 polymorphism on digoxin pharmacokinetic parameters

Pharmacogenomics Informs Cardiovascular Pharmacotherapy

Precision medicine exemplifies the emergence of personalized treatment options which may benefit specific patient populations based upon their genetic makeup. Application of pharmacogenomics requires an understanding of how genetic variations impact pharmacokinetic and pharmacodynamic properties. This particular approach in pharmacotherapy is helpful because it can assist in and improve clinical decisions. Application of pharmacogenomics to cardiovascular pharmacotherapy provides for the ability of the medical provider to gain critical knowledge on a patient's response to various treatment options and risk of side effects.

Pharmacogenomics of heart failure: a systematic review

BACKGROUND

Heart failure (HF) and multiple HF-related phenotypes are heritable. Genes implicated in the HF pathophysiology would be expected to influence the response to treatment.

METHODS

We conducted a series of systematic literature searches on the pharmacogenetics of HF therapy to assess the current knowledge on this field.

RESULTS

Existing data related to HF pharmacogenomics are still limited. The ADRB1 gene is a likely candidate to predict response to β-blockers. Moreover, the cytochrome P450 2D6 coding gene (CYP2D6) clearly affects the pharmacokinetics of metoprolol, although the clinical impact of this association remains to be established.

CONCLUSION

Given the rising prevalence of HF and related costs, a more personalized use of HF drugs could have a remarkable benefit for patients, caregivers and healthcare systems.

Use of a simplified nomogram to individualize digoxin dosing versus standard dosing practices in patients with heart failure

STUDY OBJECTIVES

To compare the frequency of achieving a therapeutic serum digoxin concentration (SDC), defined as 0.5-0.9 ng/ml, by using a simplified nomogram to individualize digoxin dosing with standard dosing practices in patients with heart failure, and to characterize the relationship between genetic polymorphisms of the ABCB1 gene and SDC.

DESIGN

Prospective study with a historical control group.

SETTING

Outpatient care center of an urban academic medical center.

PATIENTS

A total of 131 adults with heart failure due to left ventricular dysfunction who were treated with digoxin.

INTERVENTION

Digoxin doses were determined either by the dosing nomogram (65 patients) or standard care (SC; 66 patients) by using historical controls who were randomly selected from a list of SDCs obtained from laboratory records and who had their digoxin doses determined by standard dosing practices.

MEASUREMENTS AND MAIN RESULTS

The primary end point was the proportion of patients achieving a steady-state SDC of 0.5-0.9 ng/ml; secondary end points were mean SDC and proportion of patients achieving a steady-state SDC lower than 1.0 ng/ml. Postdistributive steady-state SDCs were measured 2-4 weeks after digoxin dosage adjustment or initiation. Therapeutic SDCs were achieved with similar frequency in both groups (38.7% in the nomogram group vs 34.5% in the SC group, p=0.65); however, more patients in the nomogram group had SDCs lower than 1.0 ng/ml than in the SC group (85.0% vs 44.9%, p<0.001). Mean daily digoxin doses were lower in the nomogram group (149 ± 67 μg vs 177 ± 74 μg, p=0.02), resulting in lower mean SDCs compared with those in the SC group (0.52 ± 0.30 ng/ml vs 1.12 ± 0.58 ng/ml, p<0.001). Patients in the pharmacogenetic substudy provided blood samples for genotyping of three common ABCB1 single nucleotide polymorphisms: C1236T (rs1128503), G2677T/A (rs2032582), and C3435T (rs1045642). SDCs were not significantly associated with ABCB1 genotypes.

CONCLUSION

Our simplified digoxin dosing nomogram resulted in lower SDCs compared with standard dosing practices but achieved therapeutic SDCs with similar frequency. A greater proportion of patients dosed according to our nomogram had SDCs lower than 1.0 ng/ml, consistent with consensus guidelines. Genetic polymorphisms of the ABCB1 gene were not associated with SDC.

Pharmacogenetics in chronic heart failure: new developments and current challenges

The individual patient responses to chronic heart failure (HF) pharmacotherapies are highly variable. This variability cannot be entirely explained by clinical characteristics, and genetic variation may play a role. Therefore, this review will summarize the background pharmacogenetic literature for major HF pharmacotherapy classes (ie, β-blockers, angiotensin-converting enzyme inhibitors, digoxin, and loop diuretics), evaluate recent advances in the HF pharmacogenetic literature in the context of previous findings, and discuss the challenges and conclusions for HF pharmacogenetic data and its clinical application.

Cardiovascular pharmacogenetics

Human genetic variation in the form of single nucleotide polymorphisms as well as more complex structural variations such as insertions, deletions and copy number variants, is partially responsible for the clinical variation seen in response to pharmacotherapeutic drugs. This affects the likelihood of experiencing adverse drug reactions and also of achieving therapeutic success. In this paper, we review key studies in cardiovascular pharmacogenetics that reveal genetic variations underlying the outcomes of drug treatment in cardiovascular disease. Examples of genetic associations with drug efficacy and toxicity are described, including the roles of genetic variability in pharmacokinetics (e.g. drug metabolizing enzymes) and pharmacodynamics (e.g. drug targets). These findings have functional implications that could lead to the development of genetic tests aimed at minimizing drug toxicity and optimizing drug efficacy in cardiovascular medicine.

In vivo probes of drug transport: commonly used probe drugs to assess function of intestinal P-glycoprotein (ABCB1) in humans

Intestinal P-glycoprotein (P-gp, ABCB1) may significantly influence drug absorption and elimination. Its expression and function is highly variable, regio-selective and influenced by genetic polymorphisms, drug interactions and intestinal diseases. An in vivo probe drug for intestinal P-gp should a registered, safe and well tolerated nonmetabolized selective substrate with low protein binding for which P-gp is rate-limiting during absorption. Other P-gp dependent processes should be of minor influence. The mechanism(s) and kinetics of intestinal uptake must be identified and quantified. Moreover, the release properties of the dosage form should be known. So far, the cardiac glycoside digoxin and the ß₁-selective blocker talinolol have been used in mechanistic clinical studies, because they meet most of these criteria. Digoxin and talinolol are suitable in vivo probe drugs for intestinal P-gp under the precondition, that they are used as tools in carefully designed pharmacokinetic studies with adequate biometrically planning of the sample size and that several limitations are considered in interpreting and discussion of the study results.

Bioequivalence tests based on individual estimates using non-compartmental or model-based analyses: evaluation of estimates of sample means and type I error for different designs

PURPOSE

The main objective of this work is to compare the standard bioequivalence tests based on individual estimates of the area under the curve and the maximal concentration obtained by non-compartmental analysis (NCA) to those based on individual empirical Bayes estimates (EBE) obtained by nonlinear mixed effects models.

METHODS

We evaluate by simulation the precision of sample means estimates and the type I error of bioequivalence tests for both approaches. Crossover trials are simulated under H ( 0 ) using different numbers of subjects (N) and of samples per subject (n). We simulate concentration-time profiles with different variability settings for the between-subject and within-subject variabilities and for the variance of the residual error.

RESULTS

Bioequivalence tests based on NCA show satisfactory properties with low and high variabilities, except when the residual error is high, which leads to a very poor type I error, or when n is small, which leads to biased estimates. Tests based on EBE lead to an increase of the type I error, when the shrinkage is above 20%, which occurs notably when NCA fails.

CONCLUSIONS

For small n or data with high residual error, tests based on a global data analysis should be considered instead of those based on individual estimates.

Population pharmacokinetics of romidepsin in patients with cutaneous T-cell lymphoma and relapsed peripheral T-cell lymphoma

PURPOSE

Romidepsin is a potent histone deacetylase inhibitor under clinical development. The objective of this study was to evaluate the effect of demographic, clinical, and pharmacogenetic covariates on the pharmacokinetics of romidepsin in patients with T-cell lymphoma.

EXPERIMENTAL DESIGN

Pharmacokinetic assessment was done in 98 patients enrolled in a phase II study who received 14 or 18 mg/m2 of romidepsin as a 4-hour infusion on day 1 during their first treatment cycle. Population modeling was done using a nonlinear mixed effects modeling approach to explore the effects of polymorphic variations in CYP3A4, CYP3A5, SLCO1B3, and ABCB1, all of which encode genes thought to be involved in romidepsin disposition.

RESULTS

A two-compartment model with linear kinetics adequately described the romidepsin disposition. Population clearance was 15.9 L/h with between-patient variability of 37%. ABCB1 2677G>T/A variant alleles tended toward a reduced clearance and lower volume of tissue distribution, but this was not supported by a statistical significance. Genetic variations in CYP3A4/5 and SCLO1B3 had no effect on the systemic exposure.

CONCLUSION

The population pharmacokinetic analysis indicates moderate interindividual variability in romidepsin pharmacokinetics and no clinically relevant covariates associated with the unexplained pharmacokinetic variability of romidepsin in this population.

Comparison of model-based tests and selection strategies to detect genetic polymorphisms influencing pharmacokinetic parameters

We evaluate by simulation three model-based methods to test the influence of a single nucleotide polymorphism on a pharmacokinetic parameter of a drug: analysis of variance (ANOVA) on the empirical Bayes estimates of the individual parameters, likelihood ratio test between models with and without genetic covariate, and Wald tests on the parameters of the model with covariate. Analyses are performed using the FO and FOCE method implemented in the NONMEM software. We compare several approaches for model selection based on tests and global criteria. We illustrate the results with pharmacokinetic data on indinavir from HIV-positive patients included in COPHAR 2-ANRS 111 to study the gene effect prospectively. Only the tests based on the EBE obtain an empirical type I error close to the expected 5%. The approximation made with the FO algorithm results in a significant inflation of the type I error of the LRT and Wald tests.

Drug-drug interaction predictions with PBPK models and optimal multiresponse sampling time designs: application to midazolam and a phase I compound. Part 2: clinical trial results

PURPOSE

To compare results of population PK analyses obtained with a full empirical design (FD) and an optimal sparse design (MD) in a Drug-Drug Interaction (DDI) study aiming to evaluate the potential CYP3A4 inhibitory effect of a drug in development, SX, on a reference substrate, midazolam (MDZ). Secondary aim was to evaluate the interaction of SX on MDZ in the in vivo study. Methods To compare designs, real data were analysed by population PK modelling technique using either FD or MD with NONMEM FOCEI for SX and with NONMEM FOCEI and MONOLIX SAEM for MDZ. When applicable a Wald test was performed to compare model parameter estimates, such as apparent clearance (CL/F), across designs. To conclude on the potential interaction of SX on MDZ PK, a Student paired test was applied to compare the individual PK parameters (i.e. log(AUC) and log(C(max))) obtained either by a non-compartmental approach (NCA) using FD or from empirical Bayes estimates (EBE) obtained after fitting the model separately on each treatment group using either FD or MD.

RESULTS

For SX, whatever the design, CL/F was well estimated and no statistical differences were found between CL/F estimated values obtained with FD (CL/F = 8.2 l/h) and MD (CL/F = 8.2 l/h). For MDZ, only MONOLIX was able to estimate CL/F and to provide its standard error of estimation with MD. With MONOLIX, whatever the design and the administration setting, MDZ CL/F was well estimated and there were no statistical differences between CL/F estimated values obtained with FD (72 l/h and 40 l/h for MDZ alone and for MDZ with SX, respectively) and MD (77 l/h and 45 l/h for MDZ alone and for MDZ with SX, respectively). Whatever the approach, NCA or population PK modelling, and for the latter approach, whatever the design, MD or FD, comparison tests showed that there was a statistical difference (P < 0.0001) between individual MDZ log(AUC) obtained after MDZ administration alone and co-administered with SX. Regarding C(max), there was a statistical difference (P < 0.05) between individual MDZ log(C(max)) obtained under the 2 administration settings in all cases, except with the sparse design with MONOLIX. However, the effect on C(max) was small. Finally, SX was shown to be a moderate CYP3A4 inhibitor, which at therapeutic doses increased MDZ exposure by a factor of 2 in average and almost did not affect the C(max).

CONCLUSION

The optimal sparse design enabled the estimation of CL/F of a CYP3A4 substrate and inhibitor when co-administered together and to show the interaction leading to the same conclusion as the full empirical design.

Pharmacogenetics in critical care: atrial fibrillation as an exemplar

Pharmacogenetic testing is currently not routine in critical care settings but recent changes in the warfarin label are likely to lead to critical care nurses encountering physician or nurse practitioner orders for such testing. Although the science for pharmacogenetics is complex, the components of patient teaching are not beyond that which nurses already provide about other laboratory, disease, and treatment-based information. It is reasonable to expect that as the science of pharmacogenetics and pharmacogenomics expands and discoveries are translated in clinical settings, the additional information from pharmacogenetic test results will help prescribers select or adjust medication doses to reduce the risk for adverse drug reactions and improve the chances of achieving therapeutic targets in a timely fashion.

Common ATP-binding cassette B1 variants are associated with increased digoxin serum concentration

BACKGROUND AND OBJECTIVE

Digoxin is a known substrate of ATP-binding cassette B1 (ABCB1/MDR1). The results of studies on the association between ABCB1 polymorphisms and digoxin kinetics, however, remain contradictory. Almost all studies were small and involved only single dose kinetics. The goal of this study was to establish ABCB1 genotype effect on digoxin blood concentrations in a large cohort of chronic digoxin users in a general Dutch European population.

METHODS

Digoxin users were identified in the Rotterdam Study, a prospective population-based cohort study of individuals aged 55 years and above. Digoxin blood levels were gathered from regional hospitals and laboratories. ABCB1 single nucleotide polymorphisms (SNPs) 1236C-->T, 2677G-->T/A, and 3435C-->T were assessed on peripheral blood DNA using Taqman assays. We studied the association between the ABCB1 genotypes and haplotypes, and digoxin blood levels using linear regression models adjusting for potential confounders.

RESULTS

Digoxin serum levels and DNA were available for 195 participants (56.4% women, mean age 79.4 years). All three ABCB1 variants were significantly associated with serum digoxin concentration (0.18-0.21 microg/l per additional T allele). The association was even stronger for the 1236-2677-3435 TTT haplotype allele [0.26 mug/l (95% CI 0.14-0.38)], but absent for other haplotypes (CGC allele considered referent), suggesting an interaction of SNPs in a causal haplotype instead of individual SNP effects.

CONCLUSION

We found that the common ABCB1 1236C-->T, 2677G-->T, and 3435C-->T variants and the associated TTT haplotype were associated with higher digoxin serum concentrations in a cohort of elderly European digoxin users in the general population.

New bearings in pharmacotherapeutic strategies: Pharmacogenetics and gene therapy

<zakljucak> Slicno drugim, novim terapijskim konceptima i genska terapija je puno obecavala, ali za sada je jos u razvoju. Glavni izazov ostaje unosenje pravog gena na pravo mesto, u pravu celiju i obezbedjenje adekvatne ekspresije, uz minimalna nezeljena dejstva. Iako se najvise radi na virusnim vektorima, smatra se da buducnost genske terapije cine znatno bezbedniji nevirusni sistemi. Bilo je izvesnih promasaja u genskoj terapiji, sto je dovelo do sumnje i zabrinutosti u siroj populaciji. Medjutim, razvoj genske terapije je realnost, kao i cinjenica da ona ima svoje mesto u medicini. Vazno je istaci da genskoj terapiji treba pristupati sa izuzetno visokim stepenom naucne, strucne i eticke odgovornosti, jer se ne moze iskljuciti mogucnost genetskih manipulacija opasnih za ljudsko zdravlje.