Clinical usefulness of limited sampling strategies for estimating AUC of proton pump inhibitors

Evaluation of Omeprazole Limited Sampling Strategies to Estimate Constitutive Cytochrome P450 2C19 Activity in Healthy Adults

BACKGROUND

Limited sampling strategy (LSS) is a validated method to estimate pharmacokinetic (PK) parameters from a reduced number of samples. Omeprazole is used to phenotype in vivo cytochrome P450 (CYP) 2C19 activity. This study examined an LSS using 2 estimation methods to determine apparent oral clearance (CL/F) and thus CYP2C19 activity.

METHODS

Data from 7 previously published studies included healthy subjects receiving a single, oral dose of omeprazole with intensive PK sampling. CL/F was estimated using noncompartmental analysis (NCA) and population PK modeling. LSS was simulated by selecting the 1, 2, 4, and/or 6-hour postdose time points. Linear regression was performed to assess whether CL/F estimated from limited sampling could accurately predict CL/F from the full PK profile.

RESULTS

Median CL/F was 23.7 L/h by NCA and 19.3 L/h by population PK modeling. In comparing the LSS NCA estimated versus observed CL/F, all evaluated linear regression models had unacceptable coefficients of determination (r, range: 0.14-0.81). With the population PK approach, 737 plasma concentrations (n = 71) and CYP2C19 genotype data were described with a 1-compartment structural model with mixed zero and first-order absorption and lag time. In comparing the population PK LSS estimated versus observed CL/F, all evaluated linear regression models had unacceptable r (range: 0.02-0.74). Post hoc comparison of CYP2C19 poor metabolizers versus CYP2C19 extensive metabolizers resulted in significantly lower CL/F in poor metabolizers versus extensive metabolizers.

CONCLUSIONS

Omeprazole LSS performed poorly in estimating CL/F using 2 separate estimation approaches and does not seem to be a suitable method for determining CYP2C19 activity.

Multiplex Phenotyping for Systems Medicine: A One-Point Optimized Practical Sampling Strategy for Simultaneous Estimation of CYP1A2, CYP2C9, CYP2C19, and CYP2D6 Activities Using a Cocktail Approach

Phenotyping of the CYP450 enzyme activities contributes to personalized medicine, but the past phenotyping approaches have followed a piecemeal strategy measuring single enzyme activities in vivo. A barrier to phenotyping of populations in rural and remote areas is the limited time and resources for sample collection. The CEIBA cocktail approach allows metabolic capacity estimation of multiple CYP450 enzymes in a single sample analysis, but the attendant sample collection schemes for applications in diverse global settings are yet to be optimized. The present study aimed to select an optimal matrix to simultaneously analyze CYP450 enzyme activities so as to simplify the sampling schemes in the phenotyping protocol to enhance its throughput and feasibility in native populations or in remote and underserviced geographies and social contexts. We evaluated 13 Ecuadorian healthy volunteers for CYP1A2, CYP2C9, CYP2C19, and CYP2D6 genotypes and their metabolic phenotypes, including CYP3A4, in plasma and urine after administering one reduced dose of caffeine, losartan, omeprazole, and dextromethorphan. Pharmacokinetic analyses were performed, and the correlation between AUC parent/AUC metabolite and the ratio between concentrations of probe drugs and their corresponding metabolites at timepoints ranging from 0 to 12 hours post-dose were analyzed. A single sampling timepoint, 4 hours post-dose in plasma, was identified as optimal to reflect the metabolic activity of the attendant CYP450 enzymes. This study optimizes the CEIBA multiplexed phenotyping approach and offers new ways forward for integrated drug metabolism analyses, in the pursuit of global personalized medicine applications in resource-limited regions, be they in developed or developing countries.

Limited sampling strategies to predict the area under the concentration-time curve for rifampicin

BACKGROUND

Rifampicin (RMP) is the most effective first-line antituberculosis drug. One of the most critical aspects of using it in fixed-drug combination formulations is to ensure it reaches therapeutic levels in blood. The determination of the area under the concentration-time curve (AUC) and appropriate dose adjustment of this drug may contribute to optimization of therapy. Even when the maximal concentration (Cmax) of RMP also predicts its sterilizing effect, the time to reach it (Tmax) takes 40 minutes to 6 hours. The aim of this study was to develop a limited sampling strategy (LSS) for therapeutic drug monitoring assistance for RMP.

METHODS

Full concentration-time curves were obtained from 58 patients with tuberculosis (TB) after the oral administration of RMP in fixed-drug combination formulation. A validated high-performance liquid chromatographic method was used. Pharmacokinetic parameters were estimated with a noncompartmental model. Generalized linear models were obtained by forward steps, and bootstrapping was performed to develop LSS to predict AUC curve from time 0 to the last measured at 24 hours postdose (AUC0-24). The predictive performance of the proposed models was assessed using RMP profiles from 25 other TB patients by comparing predicted and observed AUC0-24.

RESULTS

The mean AUC0-24 in the current study was 91.46 ± 36.7 mg·h·L, and the most convenient sampling time points to predict it were 2, 4 and 12 hours postdose (slope [m] = 0.955 ± 0.06; r = 0.92). The mean prediction error was -0.355%, and the root mean square error was 5.6% in the validation group. Alternate LSSs are proposed with 2 of these sampling time points, which also provide good predictions when the 3 most convenient are not feasible.

CONCLUSIONS

The AUC0-24 for RMP in TB patients can be predicted with acceptable precision through a 2- or 3-point sampling strategy, despite wide interindividual variability. These LSSs could be applied in clinical practice to optimize anti-TB therapy based on therapeutic drug monitoring.

Omeprazole limited sampling strategies to predict area under the concentration-time curve ratios: implications for cytochrome P450 2C19 and 3A phenotyping

PURPOSE

To develop a limited sampling strategy (LSS) to predict area under the concentration-time curve (AUC) ratios of omeprazole (AUC(OPZ)) to its metabolites 5-hydroxyomeprazole (AUC(5OH)) and omeprazole sulfone (AUC(SUL)) as phenotyping parameters for cytochrome P450 (CYP) 2C19 and 3A.

METHODS

Data were obtained from 37 (4 women) Caucasian, Chinese, and Korean healthy adults from three published studies. The AUC(OPZ), AUC(5OH), and AUC(SUL) were calculated via noncompartmental analysis. Observed AUC(OPZ, OBS)/AUC(5OH, OBS) and AUC(OPZ, OBS)/AUC(SUL, OBS) were determined. Plasma concentrations of omeprazole, 5-hydroxyomeprazole, and omeprazole sulfone at 1, 1.5, 2, 3, 4, 6, and 8 h post-dose were used to generate limited sampling strategy (LSS) models to predict AUC(OPZ,PRE)/AUC(5OH,PRE) and AUC(OPZ,PRE/)AUC(SUL,PRE). Bias and precision were assessed via percentage mean prediction error (%MPE) and percentage mean absolute error (%MAE), with acceptable limits being <15%.

RESULTS

For CYP2C19, the AUC(OPZ,OBS)/AUC(5OH,OBS) was [mean ± standard deviation (SD)] 2.10 ± 1.63. Five LSS models of AUC(OPZ,PRE)/AUC(5OH,PRE) were generated, but none met the bias or precision criteria. Upon stratification by CYP2C19 genotype and ethnicity, a three-timepoint (at 1, 2, and 4 h) LSS model accurately predicted AUC(OPZ)/AUC(5OH) in Caucasian CYP2C19*1/*1 subjects. For CYP3A, AUC(OPZ,OBS)/AUC(SUL,OBS) (mean ± SD) was 1.79 ± 0.67. All LSS models had unacceptable %MAE, even when stratified by CYP2C19 genotype and ethnicity.

CONCLUSIONS

A LSS model to predict AUC(OPZ)/AUC(5OH), and thus CYP2C19 activity, was generated for Caucasian CYP2C19*1/*1 subjects. However, additional model validation is needed prior to general use. LSS models to predict AUC(OPZ)/AUC(SUL), and thus CYP3A activity, were not possible, even upon stratification by CYP2C19 genotype and ethnicity.