Center specificity in the limited sampling model (LSM): can the LSM developed from healthy subjects be extended to disease states?

Fexofenadine Plasma Concentrations to Estimate Systemic Exposure in Healthy Adults Using a Limited Sampling Strategy with a Population Pharmacokinetic Approach

BACKGROUND

Fexofenadine is a recommended in vivo probe drug for phenotyping P-glycoprotein (P-gp) and organic anion transporting polypeptide (OATP) 1B1/3 transporter activities. This study evaluated a limited sampling strategy using a population pharmacokinetic approach to estimate plasma fexofenadine exposure as an index of P-gp and OATP activities.

METHODS

In a previous study, a single oral dose of fexofenadine (120 mg) was administered alone or in combination with grapefruit juice, Panax ginseng , or Echinacea purpurea to healthy adult participants. Serial plasma samples were collected up to 72 hours after administration and fexofenadine concentrations were measured. A population pharmacokinetic model was developed using nonlinear mixed-effects modeling. Limited sampling models (LSMs) using single and 2-timepoint fexofenadine concentrations were compared with full profiles from intense sampling using empirical Bayesian post hoc estimations of systemic exposure derived from the population pharmacokinetic model. Predefined criteria for LSM selection and validation included a coefficient of determination (R 2 ) ≥ 0.90, relative percent mean prediction error ≥ -5 to ≤5%, relative percent mean absolute error ≤ 10%, and relative percent root mean square error ≤ 15%.

RESULTS

Fexofenadine concentrations (n = 1520) were well described using a 2-compartment model. Grapefruit juice decreased the relative oral bioavailability of fexofenadine by 25%, whereas P. ginseng and E. purpurea had no effect. All the evaluated single timepoint fexofenadine LSMs showed unacceptable percent mean prediction error, percent mean absolute error, and/or percent root mean square error. Although adding a second time point improved precision, the predefined criteria were not met.

CONCLUSIONS

Identifying novel fexofenadine LSMs to estimate P-gp and OATP1B1/3 activities in healthy adults for future transporter-mediated drug-drug interaction studies remains elusive.

S-warfarin limited sampling strategy with a population pharmacokinetic approach to estimate exposure and cytochrome P450 (CYP) 2C9 activity in healthy adults

PURPOSE

S-warfarin is used to phenotype cytochrome P450 (CYP) 2C9 activity. This study evaluated S-warfarin limited sampling strategy with a population pharmacokinetic (PK) approach to estimate CYP2C9 activity in healthy adults.

METHODS

In 6 previously published studies, a single oral dose of warfarin 10 mg was administered alone or with a CYP2C9 inducer to 100 healthy adults. S-warfarin concentrations were obtained from adults during conditions when subjects were not on any prescribed medications. A population PK model was developed using non-linear mixed effects modeling. Limited sampling models (LSMs) using single- or 2-timepoint concentrations were compared with full PK profiles from intense sampling using empiric Bayesian post hoc estimations of S-warfarin AUC derived from the population PK model. Preset criterion for LSM selection and validation were a correlation coefficient (R²) >0.9, relative percent mean prediction error (%MPE) >-5 to <5%, relative percent mean absolute error (%MAE) ≤ 10%, and relative percent root mean squared error (%RMSE) ≤ 15%.

RESULTS

S-warfarin concentrations (n=2540) were well described with a two-compartment model. Mean apparent oral clearance was 0.56 L/hr and volume of distribution was 35.5 L. Clearance decreased 33% with the CYP2C9 *3 allele and increased 42% with lopinavir/ritonavir co-administration. During CYP2C9 constitutive conditions, LSMs at 48 hr and at 72 hr as well as 2-timepoint LSMs were within acceptable limits for R², %MPE, %MAE, and %RMSE. During CYP2C9 induction, S-warfarin LSMs had unacceptable %MPE, %MAE, and %RMSE.

CONCLUSIONS

Phenotyping studies with S-warfarin in healthy subjects can utilize a single- and/or a 2-timepoint LSM with a population PK approach to estimate constitutive CYP2C9 activity.

Limited sampling strategy of partial area under the concentration-time curves to estimate midazolam systemic clearance for cytochrome P450 3A phenotyping

OBJECTIVE

Intravenous (IV) midazolam is the preferred cytochrome P450 (CYP) 3A probe for phenotyping, with systemic clearance (CL) estimating hepatic CYP3A activity. A limited sampling strategy was conducted to determine whether partial area under the concentration-time curves (AUCs) could reliably estimate midazolam systemic CL during conditions of CYP3A baseline activity, inhibition, and induction/activation.

METHODS

Midazolam plasma concentrations during CYP3A baseline (n = 93), inhibition (n = 40), and induction/activation (n = 33) were obtained from 7 studies in healthy adults. Noncompartmental analysis determined observed CL (CL(obs)) and partial AUCs. Linear regression equations were derived from partial AUCs to estimate CL (CL(pred)) during CYP3A baseline, inhibition, and induction/activation. Preestablished criterion for linear regression analysis was r(2) ≥ 0.9. CL(pred) was compared with CL(obs), and relative bias and precision were assessed using percent mean prediction error and percent mean absolute error.

RESULTS

During CYP3A baseline and inhibition, all evaluated partial AUCs failed to meet criterion of r(2) ≥ 0.9 and/or percent mean absolute error <15%. During CYP3A induction/activation, equations derived from partial AUCs from 0 to 1 hour (AUC0-1), 0 to 2 hours (AUC0-2), and 0 to 4 hours (AUC0-4) were acceptable, with good precision and minimal bias. These equations provided the same conclusions regarding equivalency testing compared with intense sampling.

CONCLUSIONS

During CYP3A induction/activation, but not baseline or inhibition, midazolam partial AUC0-1, AUC0-2, and AUC0-4 reliably estimated systemic CL and consequently hepatic CYP3A activity in healthy adults.

Evaluation of partial area under the concentration time curve to estimate midazolam apparent oral clearance for cytochrome P450 3A phenotyping

BACKGROUND

Midazolam apparent oral clearance (CLORAL) is used to estimate intestinal and hepatic cytochrome P450 (CYP) 3A activity. A limited sampling approach was performed to access a midazolam partial area under the concentration time curve (AUC) to estimate CLORAL.

METHODS

Midazolam plasma concentrations from healthy adults were obtained during CYP3A baseline (n=116), inhibition (n=75), and induction or activation (n=66) from seven published studies. Observed CLORAL and partial AUCs of AUC0-2, AUC0-4, AUC0-6, AUC1-2, AUC1-4, AUC2-4, and AUC2-6 were determined by noncompartmental analysis. Subject data were randomly divided into a training set and a validation set. Linear regression equations, derived from partial AUCs, were developed from training set data. Predicted CLORAL was determined from these equations from validation set data. Preset criterion was a coefficient of determination (r2) greater than or equal to 0.9. Bias and precision were evaluated by relative percent mean prediction error (%MPE) and relative percent mean absolute error (%MAE).

RESULTS

During CYP3A baseline conditions, all of the evaluated CLORAL equations had unacceptable r2 (range: 0.34-0.86). During CYP3A inhibition, all of the evaluated CLORAL equations had unacceptable %MAE. Acceptable r2, %MPE, and %MAE were observed during CYP3A induction/activation with AUC0-4 (r2=0.99, %MPE=3.9, %MAE=12.5) and AUC1-4 (r2=0.99, %MPE=6%, %MAE=11.1%). The same equations also predicted the extent of CYP3A induction as a lack of equivalence was observed with AUC0-4 and AUC1-4.

CONCLUSIONS

Midazolam partial AUCs were unable to estimate CYP3A activity during the evaluated baseline and inhibitory conditions. Midazolam CLORAL utilizing a partial AUC0-4 and AUC1-4 was able to estimate CYP3A induction with rifampin and Ginkgo biloba extract.

Limited Sampling Models for Oral Midazolam: Midazolam Plasma Concentrations, Not the Ratio of 1-Hydroxymidazolam to Midazolam Plasma Concentrations, Accurately Predicts AUC as a Biomarker of CYP3A Activity

Oral midazolam is used as a phenotyping probe for cytochrome P450 (CYP) 3A activity and requires multiple plasma samples to measure drug exposure. Limited sampling is a useful strategy for optimizing sampling and reducing costs and labor. We studied limited sampling models using multiple linear regressions to predict the area under the concentration versus time curve (AUC) of midazolam using either midazolam plasma concentrations or the ratio of 1-hydroxymidazolam (1-OH MDZ) to midazolam plasma concentrations. CYP3A baseline activity data for oral midazolam from previous studies were used (45 healthy adults for models using midazolam plasma concentrations and 41 healthy adults for models using the ratios of 1-OH MDZ to midazolam plasma concentrations). Limited sampling models were derived, validated, and evaluated for precision and bias. Two equations using the time points at 0.5 and 6 hours and 0.5, 2, and 6 hours were acceptable and predictive of midazolam AUC using midazolam plasma concentrations. No 1-OH MDZ to midazolam plasma concentration ratios accurately predicted midazolam AUC.

Evaluation of limited sampling models for prediction of oral midazolam AUC for CYP3A phenotyping and drug interaction studies

BACKGROUND

The area under the concentration-time curve (AUC) after oral midazolam administration is commonly used for cytochrome P450 (CYP) 3A phenotyping studies. The aim of this investigation was to evaluate a limited sampling strategy for the prediction of AUC with oral midazolam.

METHODS

A total of 288 concentration-time profiles from 123 healthy volunteers who participated in four previously performed drug interaction studies with intense sampling after a single oral dose of 7.5 mg midazolam were available for evaluation. Of these, 45 profiles served for model building, which was performed by stepwise multiple linear regression, and the remaining 243 datasets served for validation. Mean prediction error (MPE), mean absolute error (MAE) and root mean squared error (RMSE) were calculated to determine bias and precision

RESULTS

The one- to four-sampling point models with the best coefficient of correlation were the one-sampling point model (8 h; r (2) = 0.84), the two-sampling point model (0.5 and 8 h; r (2) = 0.93), the three-sampling point model (0.5, 2, and 8 h; r (2) = 0.96), and the four-sampling point model (0.5,1, 2, and 8 h; r (2) = 0.97). However, the one- and two-sampling point models were unable to predict the midazolam AUC due to unacceptable bias and precision. Only the four-sampling point model predicted the very low and very high midazolam AUC of the validation dataset with acceptable precision and bias. The four-sampling point model was also able to predict the geometric mean ratio of the treatment phase over the baseline (with 90 % confidence interval) results of three drug interaction studies in the categories of strong, moderate, and mild induction, as well as no interaction.

CONCLUSION

A four-sampling point limited sampling strategy to predict the oral midazolam AUC for CYP3A phenotyping is proposed. The one-, two- and three-sampling point models were not able to predict midazolam AUC accurately.

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.