Limited Sampling Strategy For Estimation Research Articles

The pharmacokinetics of tacrolimus in peripheral blood mononuclear cells and limited sampling strategy for estimation of exposure in renal transplant recipients.

Intracellular exposure of tacrolimus (TAC) may be a better marker of therapeutic effect than whole blood exposure. We aimed to evaluate the influence of genetic polymorphism on the pharmacokinetics of TAC in peripheral blood mononuclear cells (PBMCs) and develop limited sampling strategy (LSS) models to estimate the area under the curve (AUC0-12h) in the PBMC of Chinese renal transplant patients. Ten blood samples of each of the 23 renal transplant patients were collected 0-12h after 14 (10-18) days of TAC administration. PBMCs were separated and quantified. The TAC level in PBMCs was determined, and pharmacokinetic parameters were estimated by noncompartmental study. The AUC0-12h of TAC in whole blood was estimated by Bayesian approach based on a population pharmacokinetic model established in 65 renal transplant patients. The influence of CYP3A5 and ABCB1 genotypes on exposure was estimated. By applying multiple stepwise linear regression analysis, LSS equations for TAC AUC0-12h in the PMBC of renal transplant patients were established, and the bias and precision of various equations were identified and compared. We found a modest correlation between TAC exposure in whole blood and PBMC (r2 = 0.5260). Patients with the CYP3A5 6986GG genotype had a higher AUC0-12h in PBMCs than those with the 6986 AA or GA genotype (P = 0.026). Conversely, patients with the ABCB1 3435TT genotype had a higher AUC0-12h in PBMC than those with the 3435 CC and CT genotypes (P = 0.046). LSS models with 1-4 blood time points were established (r2 = 0.570-0.989). The best model for predicting TAC AUC0-12h was C2-C4-C6-C10 (r2 = 0.989). The model with C0.5-C6 (r2 = 0.849) can be used for outpatients who need monitoring to be performed in a short period. The CYP3A5 and ABCB1 genotypes impact TAC exposure in PBMCs, which may further alter the effects of TAC. The LSS model consisting of 2-4 time points is an effective approach for estimating full TAC AUC0-12h in Chinese renal transplant patients. This approach may provide convenience and the possibility for clinical monitoring of TAC intracellular exposure.

Limited sampling strategies for estimation of tacrolimus exposure in kidney transplant recipients receiving extended-release tacrolimus preparation.

Tacrolimus is the key component of most contemporary immunosuppressive drug regimens for the prevention of transplant rejection. Area under the concentration time curve over 24 h (AUC0–24) predicts efficacy, but predose (trough) tacrolimus blood concentration (C0) is currently used to guide dosing. In clinical or research situations where an estimate of AUC is required, collection of a full 24 h pharmacokinetic (PK) profile is cumbersome. Limited sampling strategies (LSSs) have been developed for some tacrolimus preparations but not for the new, extended‐release, once‐daily formulation of tacrolimus, ENVARSUS XR. Twenty‐four kidney transplant recipients were enrolled in this study. Twenty‐four tacrolimus PK profiles were obtained over 24 h. Multiple linear regression was used to generate LSSs with the best subset selection for accurate estimation of tacrolimus AUC0–24. The predictive performance of each model was assessed in the evaluation group. The correlation between actual and predicted AUC0–24 was evaluated and mean percentage prediction error (MPE%), mean absolute percentage prediction error (MAE%), and root mean squared error (RMSE) were calculated for each prediction model to assess bias and precision. The selected LSSs were highly correlated to AUC0–24 compared with the correlation between C0 and AUC0‐24. Two and three sampling points limited sampling strategies: C0, C2, and C10 provide the most reliable and effective LSS for estimation of tacrolimus AUC0–24 in routine clinic use. These limited sampling models can be applied in therapeutic drug monitoring schemes to personalize tacrolimus dosing for kidney transplant recipients on treatment with extended‐release tacrolimus.

A Limited Sampling Strategy to Estimate Whole Blood and Intra-lymphocyte Exposure of Everolimus in Renal Transplant Recipients using Population Pharmacokinetic Modeling and Bayesian Estimators

Introduction Intra-lymphocyte exposure of everolimus may be a better marker of therapeutic effect compared to trough whole blood concentrations. We aimed to develop pharmacokinetic population models and Bayesian estimators based on a limited sampling strategy for estimation of whole blood and intra-lymphocyte dose interval exposures of everolimus in renal transplants. Methods Full whole-blood and intra-lymphocyte concentration-time profiles of everolimus were obtained from 12 stable renal transplants on two different occasions, 4 weeks apart. The dataset was treated as 24 individual profiles and split into a development dataset (n=20) and a validation dataset (n=4). The pharmacokinetic model was developed using non-parametric modeling (Pmetrics) and its performances and those of the derived Bayesian estimator were evaluated in the validation set. Results A structural two compartment model with first-order elimination and two absorption phases described by a sum of two gamma distributions were developed. None of the tested covariates (age, gender, CYP3A5-genotype, hematocrit, fat-free mass) were retained in the final model. A limited sampling schedule of two whole blood samples at 0 and 1.5 hours and one intra-lymphocyte sample at 1.5 hours post dose provided accurate estimates of the area under the curve (AUC) in comparison with the trapezoidal reference AUC (relative bias ± SD = -3.9 ±10.6% and 4.1 ±12.3% for whole blood and intra-lymphocyte concentrations, respectively). Conclusion The developed model allows a simultaneous and accurate prediction of whole blood and intra-lymphocyte everolimus exposure based on two sample times and one intracellular concentrations determination. The model supplies a base for a feasible exploration of the relationships between intra-lymphocyte exposure and therapeutic effects in prospective trials.

A Limited Sampling Strategy to Estimate Exposure of Everolimus in Whole Blood and Peripheral Blood Mononuclear Cells in Renal Transplant Recipients Using Population Pharmacokinetic Modeling and Bayesian Estimators.

Intracellular exposure of everolimus may be a better marker of therapeutic effect than trough whole blood concentrations. We aimed to develop pharmacokinetic population models and Bayesian estimators based on a limited sampling strategy for estimation of dose interval exposures of everolimus in whole blood and peripheral blood mononuclear cells (PBMCs) in renal transplant recipients. Full whole blood and PBMC concentration-time profiles of everolimus were obtained from 12 stable renal transplant recipients on two different occasions, 4weeks apart. The dataset was treated as 24 individual profiles and split into a development dataset (n = 20) and a validation dataset (n = 4). The pharmacokinetic model was developed using non-parametric modeling and its performances and those of the derived Bayesian estimator were evaluated in the validation set. A structural two-compartment model with first-order elimination and two absorption phases described by a sum of two gamma distributions were developed. None of the tested covariates (age, sex, albumin, hematocrit, fat-free mass and genetic variants such as CYP3A5*1, ABCB1 haplotype, PPARA*42, PPARA*48, and POR*28) were retained in the final model. A limited sampling schedule of two whole blood samples at 0 and 1.5h and one PBMC sample at 1.5h post dose provided accurate estimates of the area under the plasma concentration-time curve (AUC) in comparison with the trapezoidal reference AUC (relative bias ± standard deviation = - 3.9 ± 10.6 and 4.1 ± 12.3% for whole blood and PBMC concentrations, respectively). The developed model allows simultaneous and accurate prediction of everolimus exposure in whole blood and PBMCs, and supplies a base for a feasible exploration of the relationships between intracellular exposure and therapeutic effects in prospective trials.

Limited Sampling Strategy for the Estimation of Mycophenolic Acid Area under the Concentration–Time Curve Treated in Japanese Living-Related Renal Transplant Recipients with Concomitant Extended-Release Tacrolimus

Mycophenolate mofetil (MMF) is used for oral administration to prevent rejection in renal transplant recipients, and is rapidly converted into mycophenolic acid (MPA), the active metabolite, by hydrolysis in vivo. The area under the concentration-time curve (AUC(0-12 h)) of MPA is considered to be an effective pharmacokinetics parameter for predicting acute rejection. However, frequent blood sampling is required to calculate AUC(0-12 h), which imposes a burden on patients and providers. Therefore, we examined a limited sampling strategy (LSS) for estimation of MPA-AUC(0-12 h) using only a trough level (C0) and two points including C0 in Japanese living-related renal transplant recipients with concomitant extended-release tacrolimus (ER-TAC). The present study suggests that better estimation of MPA-AUC(0-12 h) can be obtained by using two points including C0 as compared with only C0 regardless of transplant progress. Furthermore, blood collection points showing the highest estimation of MPA-AUC(0-12 h) by adding to C0 were C4 at pre-transplantation (Tx) and 1 month post-Tx, and C6 at 3 months post-Tx. We conjecture that changes in renal function and serum albumin (Alb) accompanying transplant progress are aggravating factors in terms of estimation, because there was also a significant difference in the reciprocal of serum creatinine (1/Scr) and Alb between pre-Tx and post-Tx in this study. In conclusion, the present study provides useful information for effective and efficient monitoring of MPA levels in Japanese living-related renal transplant recipients.

A limited sampling strategy for estimation of the area under the curve (0 to 8 hours) of mycophenolic acid administered three times daily to liver transplant recipients

Objectives. Gastrointestinal side-effects caused by mycophenolic acid (MPA) are frequent in liver transplant recipients, and in these cases a switch from two to three daily doses is usually recommended. However, a limited sampling strategy for the estimation of MPA area under the curve from 0 to 8 hours (AUC(0–8h)) has not been made.Design and methods. In 22 liver transplant patients who were administered MPA three times daily, the trapezoidal extrapolated MPA AUC(0–8h) values using a sampling time from 0 to 2 hours were calculated.Results. A tentative therapeutic range for MPA AUC(0–8h) of about 20–40 μg.h/mL is proposed, and in the 13 patients with supratherapeutic values the total leukocyte blood count was significantly lower than in the 9 patients with AUC(0–8h) ≤ 40 μg.h/mL (P < 0.001). Significant negative correlations were found between the total leukocyte blood count and the MPA trough levels (r = −0.458; P < 0.05), AUC(0–8h) (r = −0.479; P < 0.05), and AUC(0–2h) (r = −0.437; P < 0.05). A significant correlation was found between the trapezoidal extrapolated AUC(0–8h) and trapezoidal AUC(0–2h) results (r = 0.850; P < 0.001).Conclusions. The trapezoidal extrapolated AUC(0–8h), and possibly trapezoidal AUC(0–2h), may be useful for routine therapeutic MPA monitoring in liver transplant recipients in which the dosing frequency is increased from twice to three times a day.

Development of a Predictive Limited Sampling Strategy for Estimation of Mycophenolic Acid Area Under the Concentration Time Curve in Patients Receiving Concomitant Sirolimus or Cyclosporine

Limited sampling strategies for estimation of the area under the concentration time curve (AUC) for mycophenolic acid (MPA) co-administered with sirolimus (SRL) have not been previously evaluated. The authors developed and validated 68 regression models for estimation of MPA AUC for two groups of patients, one with concomitant SRL (n = 24) and the second with concomitant cyclosporine (n=14), using various combinations of time points between 0 and 4 hours after drug administration. To provide as robust a model as possible, a dataset-splitting method similar to a bootstrap was used. In this method, the dataset was randomly split in half 100 times. Each time, one half of the data was used to estimate the equation coefficients, and the other half was used to test and validate the models. Final models were obtained by calculating the median values of the coefficients. Substantial differences were found in the pharmacokinetics of MPA between these groups. The mean MPA AUC as well as the standard deviation was much greater in the SRL group, 56.4 +/- 23.5 mg.h/L, compared with 30.4 +/- 11.0 mg.h/L in the cyclosporine group (P < 0.001). Mean maximum concentration was also greater in the SRL group: 16.4 +/- 7.7 mg/L versus 11.7 +/- 7.1mg/L (P < 0.005). The second absorption peak in the pharmacokinetic profile, presumed to result from enterohepatic recycling of glucuronide MPA, was observed in 70% of the profiles in the SRL group and in 35% of profiles from the cyclosporine group. Substantial differences in the predictive performance of the regression models, based on the same time points, were observed between the two groups. The best model for the SRL group was based on 0 (trough) and 40 minutes and 4 hour time points with R2, root mean squared error, and predictive performance values of 0.82, 10.0, and 78%, respectively. In the cyclosporine group, the best model was 0 and 40 minutes and 2 hours, with R2, RMSE, and predictive performance values of 0.86, 4.1, and 83%, respectively. The model with 2 hours as the last time point is also recommended for the SRL group for practical reasons, with the above parameters of 0.77, 11.3, and 69%, respectively.

Limited Sampling Strategy for Predicting Area Under the Concentration‐Time Curve of Mycophenolic Acid in Adult Lung Transplant Recipients

To develop limited sampling strategies for estimation of mycophenolic acid exposure (by determining area under the concentration-time curve [AUC]) in lung transplant recipients by using sampling times within 2 hours after drug administration and a maximum of three plasma samples. Prospective, open-label clinical study. Lung transplant clinic in Vancouver, British Columbia, Canada. Nineteen adult (mean age 48.3 yrs) lung transplant recipients who were receiving mycophenolate mofetil therapy along with cyclosporine (9 patients) or tacrolimus (10 patients). Eleven blood samples were collected from each of the 19 patients over 12 hours: immediately before (0 hr) and 0.3, 0.6, 1, 1.5, 2, 4, 6, 8, 10, and 12 hours after administration of mycophenolate mofetil. Mycophenolic acid levels in plasma were determined by a high-performance liquid chromatography-ultraviolet detection method. The 19 patients were randomly divided into index (10 patients) and validation (9 patients) groups. Limited sampling strategies were developed with multiple regression analysis by using data from the index group. Data from the validation group were used to test each strategy. Bias and precision of each limited sampling strategy were determined by calculating the mean prediction error and the root mean square error, respectively. The correlation between AUC and single concentrations was generally poor (r2= 0.18-0.73). Two single-concentration strategies, eight two-concentration strategies, and eight three-concentration strategies matched our criteria. However, the best overall limited sampling strategies (and their predictive performance) were the following: log AUC = 0.241 log C0 + 0.406 log C2 + 1.140 (bias -5.82%, precision 5.97%, r2= 0.828) and log AUC = 0.202 log C0 + 0.411 log C1.5 + 1.09 (bias -5.71%, precision 6.94%, r2= 0.791), where Cx is mycophenolic acid concentration at time x hours. Two-concentration limited sampling strategies provided minimally biased and highly precise estimation of mycophenolic acid AUC in lung transplant recipients. These optimal and most clinically feasible limited sampling strategies are based collectively on the number of blood samples required, r2 value, bias, and precision.

Maximum a posteriori Bayesian estimation of epirubicin clearance by limited sampling.

To develop a limited sampling strategy for estimation of epirubicin clearance. The data set comprised 1051 concentrations measured in 105 patients with advanced or metastatic breast cancer treated with epirubicin alone. Ten limited sampling designs comprising two or three blood samples were proposed, taken at times identified by D-optimality from population pharmacokinetic parameter estimates. The data set was then truncated to include the sampling times for each of the designs. MAP Bayesian estimates of clearance were generated for each design and compared with clearance estimates obtained using all the data. The limited sampling designs were also validated using a separate data set obtained from 18 patients with either breast cancer or hepatocellular carcinoma. The sensitivity of the best limited sampling designs to sample time recording errors of 0-10% or 10-20% was then assessed using a simulated data set including 200 patients. The optimum sampling times were: end of the injection and 18 min, 40 min, 3 h, 10 h and 48 h after the start of the injection. The best three-sample design included samples at 40 min, 3 h and 48 h and gave unbiased estimates of clearance with an imprecision of 9.1% (95% CI 7.3, 10.5). The best two sample design included samples at 3 and 48 h and gave unbiased estimates of clearance with an imprecision of 12.4% (95% CI 9.6, 14.6). Using the validation data set, these two and three sample designs gave unbiased estimates of clearance with an imprecision of 5.6% (95% CI 3.7, 7.0) and 4.2% (95% CI 2.6, 5.3), respectively. Simulations that included 0-10% or 10-20% errors in the recording of the blood sampling times had negligible effects on the bias and imprecision of clearance estimates. Limited sampling designs have been identified and validated that estimate epirubicin clearance with adequate precision and without bias from two or three blood samples. These designs also allow flexibility in blood sample collection and are robust with regard to sample time recording errors.

A limited sampling strategy for estimation of the cladribine plasma area under the concentration versus time curve after intermittent i.v. infusion, s.c. injection, and oral administration.

Cladribine is a newly developed antimetabolite with promising activity in lymphoproliferative disorders. Recent pharmacokinetics investigations have suggested that there is a relationship between its plasma area under the concentration versus time curve (AUC) and the degree of neutropenia posttreatment as well as the therapeutic outcome in hairy-cell leukemia. To enable a simple estimation of the plasma AUC, a limited sampling strategy was developed. Stepwise linear regression was used to determine which were the most important data points for estimation of the plasma AUC after 2-h i.v. infusion, s.c. injection (5 mg/m2), and oral administration (10 mg/m2) in 27 patients. The most important data points after i.v. infusion in 12 patients were 1, 4, and 24 h, in order of importance. The AUC could be estimated as 2.9081 x C1h + 5.1851 x C4h + 20.3265 x C24h. The accuracy and precision (mean value +/- SD for the determined/estimated AUC was 0.99 +/- 0.053) of the model could not be increased by the addition of more data points. A somewhat lower accuracy and precision (0.96 +/- 0.089) was seen with the 2-, 4-, and 24-h data points. These were used to test the regression technique prospectively for the estimation of the AUC after i.v. administration in another set of 10 patients. The accuracy and precision of the estimation of the AUC was similar in this group (1.01 +/- 0.109). In all, 11 patients were treated orally (10 mg/m2) and 10 patients were treated by s.c. injection (5 mg/m2). The most important data points for estimation of the AUC were 2.5, 24, and 0.5 h after oral administration (AUC = 0.8630 x C0.5h + 4.2337 x C2.5h + 45.4364 x C24h) and 9, 1, and 16 h after s.c. injection (AUC = 1.8821 x C1h + 16.4256 x C9h + 25.4518 x C16h). The accuracy and precision were 1.01 +/- 0.064 after oral dosing and 0.99 +/- 0.11 after s.c. injection. The derived mathematical models are reliable for estimation of the plasma AUC of cladribine after 2-h i.v. infusion, oral administration, and s.c. injection.