Beyond cyclosporine: a systematic review of limited sampling strategies for other immunosuppressants

Limited Sampling Strategies Fail to Accurately Predict Mycophenolic Acid Area Under the Curve in Kidney Transplant Recipients and the Impact of Enterohepatic Recirculation

BACKGROUND

Therapeutic drug monitoring for mycophenolic acid (MPA) is challenging due to difficulties in measuring the area under the curve (AUC). Limited sampling strategies (LSSs) have been developed for MPA therapeutic drug monitoring but come with risk of unacceptable performance. The authors hypothesized that the poor predictive performance of LSSs were due to the variability in MPA enterohepatic recirculation (EHR). This study is the first to evaluate LSSs models performance in the context of EHR.

METHODS

Adult kidney transplant recipients (n = 84) receiving oral mycophenolate mofetil underwent intensive MPA pharmacokinetic sampling. MPA AUC0-12hr and EHR were determined. Published MPA LSSs in kidney transplant recipients receiving tacrolimus were evaluated for their predictive performance in estimating AUC0-12hr in our full cohort and separately in individuals with high and low EHR.

RESULTS

None of the evaluated LSS models (n = 12) showed good precision or accuracy in predicting MPA AUC0-12hr in the full cohort. In the high EHR group, models with late timepoints had better accuracy but low precision, except for 1 model with late timepoints at 6 and 10 hours postdose, which had marginally acceptable precision. For all models, the good guess of predicted AUC0-12hr (±15% of observed AUC0-12hr) was highly variable (range, full cohort = 19%-61.9%; high EHR = 4.5%-65.9%; low EHR = 27.5%-62.5%).

CONCLUSIONS

The predictive performance of the LSS models varied according to EHR status. Timepoints ≥5 hours postdose in LSS models are essential to capture EHR. Models and strategies that incorporate EHR during development are required to accurately ascertain MPA exposure.

Simulation-Based Optimization of Sampling Schedules for Model-Informed Precision Dosing of Once-Daily and 4-Times-Daily Busulfan in Pediatric Patients

BACKGROUND

Therapeutic drug monitoring (TDM) is crucial in optimizing the outcomes of hematopoietic stem cell transplantation by guiding busulfan (Bu) dosing. Limited sampling strategies show promise for efficiently adjusting drug doses. However, comprehensive assessments and optimization of sampling schedules for Bu TDM in pediatric patients are limited. We aimed to establish optimal sampling designs for model-informed precision dosing (MIPD) of once-daily (q24h) and 4-times-daily (q6h) Bu administration in pediatric patients.

METHODS

Simulated data sets were used to evaluate the population pharmacokinetic model-based Bayesian estimation of the area under the concentration-time curve (AUC) for different limited sampling strategy designs. The evaluation was based on the mean prediction error for accuracy and root mean square error for precision. These findings were validated using patient-observed data. In addition, the MIPD protocol was implemented in the Tucuxi software, and its performance was assessed.

RESULTS

Our Bayesian estimation approach allowed for flexible sampling times while maintaining mean prediction error within ±5% and root mean square error below 10%. Accurate and precise AUC0-24h and cumulative AUC estimations were obtained using 2-sample and single-sample schedules for q6h and q24h dosing, respectively. TDM on 2 separate days was necessary to accurately estimate cumulative exposure, especially in patients receiving q6h Bu. Validation with observed patient data confirmed the precision of the proposed limited sampling scenarios. Implementing the MIPD protocol in Tucuxi software yielded reliable AUC estimations.

CONCLUSIONS

Our study successfully established precise limited sampling protocols for MIPD of Bu in pediatric patients. Our findings underscore the importance of TDM on at least 2 occasions to accurately achieve desired Bu exposures. The developed MIPD protocol and its implementation in Tucuxi software provide a valuable tool for routine TDM in pediatric hematopoietic stem cell transplantation.

Limited Sampling Strategies for Estimating Busulfan Area Under the Concentration-Time Curve: Based on Peak and Trough Concentrations in Saliva

Therapeutic drug monitoring for busulfan is currently performed by multiple plasma sampling. Saliva is considered a noninvasive therapeutic drug monitoring matrix. This study aimed to investigate intravenous busulfan pharmacokinetics (PK) in plasma and saliva, and establish a limited sampling strategy (LSS) for predicting the area under the concentration-time curve from time zero to infinity in plasma (AUC0-∞,p) by using saliva samples. Therefore, the PK of busulfan was studied in 37 Chinese patients. Pearson correlation analysis was used to evaluate the correlation between the AUC of busulfan in plasma and saliva. LSS models were established by the multiple linear regression analysis. The prediction error, the mean prediction error, and the root mean square error were used to evaluate the predictive accuracy. The agreement between the predicted and observed AUC0-∞ in saliva was investigated by the intraclass correlation coefficient and Bland-Altman analysis. The accuracy and robustness of the models were evaluated by using the bootstrap procedure. The result of PK analysis 62.2% of patients (23/37) was within the target range of AUC0-∞,p . A good correlation between saliva and plasma busulfan AUC0-∞ was observed (r = 0.63, p < .01). The bias and precision of the models 7 and 13 were less than 15%. The intraclass correlation coefficient exceeded 0.9, and the limits of agreement were within ±15%. The 2-point LSS model in saliva is a convenient and desirable approach to predict the AUC0-∞ of 4 times daily intravenous busulfan in plasma, which can be used to design personalized dosing for busulfan.

Topotecan clearance based on a single sample and a population pharmacokinetic model: Application to a pediatric high-risk neuroblastoma clinical trial

BACKGROUND

Topotecan, an antitumor drug with systemic exposure (SE)-dependent activity against many pediatric tumors has wide interpatient pharmacokinetic variability, making it challenging to attain the desired topotecan SE. The study objectives were to update our topotecan population pharmacokinetic model, to evaluate the feasibility of determining individual topotecan clearance using a single blood sample, and to apply this approach to topotecan data from a neuroblastoma trial to explore exposure-response relationships.

PROCEDURE

Our previous population pharmacokinetic and covariate model was updated using data from 13 clinical pediatric studies. A simulation-based Bayesian analysis was performed to determine if a single blood sample could be sufficient to estimate individual topotecan clearance. Following the Bayesian approach, single pharmacokinetic samples collected from a Children's Oncology Group Phase III clinical trial (ANBL0532; NCT0056767) were analyzed to estimate individual topotecan SE. Associations between topotecan SE and toxicity or early response were then evaluated.

RESULTS

The updated population model included the impact of patient body surface area (BSA), age, and renal function on topotecan clearance. The Bayesian analysis with the updated model and single plasma samples showed that individual topotecan clearance values were estimated with good precision (mean absolute prediction error ≤16.2%) and low bias (mean prediction error ≤7.2%). Using the same approach, topotecan SE was derived in patients from ANBL0532. The exposure-response analysis showed an increased early response after concomitant cyclophosphamide and topotecan up to a topotecan SE of 45 h ng/mL.

CONCLUSIONS

A simple single-sample approach during topotecan therapy could guide dosing for patients, resulting in more patients reaching target attainment.

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.

Limited sampling strategies for therapeutic drug monitoring of anti-tuberculosis medications: A systematic review of their feasibility and clinical utility

Therapeutic drug monitoring (TDM) is recommended for medications with high inter-individual variability, narrow therapeutic index drugs, possible drug-drug interactions, drug toxicity, and subtherapeutic concentrations, as well as to assess noncompliance. The area under the plasma concentration-time curve (AUC) is a significant pharmacokinetic parameter since it calculates the drug's total systematic exposure in the body. However, multiple blood samples from the patient are required to calculate the area under the curve, which is inconvenient for both the patient and the healthcare professional. To alleviate the issue, the limited sampling strategy (LSS) was devised, in which sampling is minimized while obtaining complete and precise findings to anticipate the area under the curve. One can reduce costs, labor, and discomfort for patients and healthcare workers by applying this limited sampling strategy. This article examines a systematic evaluation of all the limited sampling done in anti-tuberculosis (anti-TB) medications resulting from the literature search of several research papers. This article also briefly describes the two methodologies: Multiple regression analysis (MRA) and the Bayesian approach used to develop a limited sampling strategy model. Anti-TB medications have been found to have considerable inter-individual variability, and isoniazid has a narrow therapeutic index, both of which are criteria for therapeutic drug monitoring. To avoid multi-drug resistance and therapy failure, it is proposed that limited sampling strategy-based therapeutic drug monitoring of anti-TB medications be undertaken to generate an individualized dose regimen, particularly for individuals at high risk of treatment failure or delayed response.

Evaluation of limited-sampling strategies to calculate AUC(0–24) and the role of CYP3A5 in Chilean pediatric kidney recipients using extended-release tacrolimus

Background: Kidney transplantation (KTx) requires immunosuppressive drugs such as Tacrolimus (TAC) which is mainly metabolized by CYP3A5. TAC is routinely monitored by trough levels (C0) although it has not shown to be a reliable marker. The area-under-curve (AUC) is a more realistic measure of drug exposure, but sampling is challenging in pediatric patients. Limited-sampling strategies (LSS) have been developed to estimate AUC. Herein, we aimed to determine AUC(0–24) and CYP3A5 genotype in Chilean pediatric kidney recipients using extended-release TAC, to evaluate different LSS-AUC(0–24) formulas and dose requirements.

Patients and methods: We analyzed pediatric kidney recipients using different extended-release TAC brands to determine their trapezoidal AUC(0–24) and CYP3A5 genotypes (SNP rs776746). Daily TAC dose (TAC-D mg/kg) and AUC(0–24) normalized by dose were compared between CYP3A5 expressors (*1/*1 and *1/*3) and non-expressors (*3/*3). We evaluated the single and combined time-points to identify the best LSS-AUC(0–24) model. We compared the performance of this model with two pediatric LSS-AUC(0–24) equations for clinical validation.

Results: Fifty-one pharmacokinetic profiles were obtained from kidney recipients (age 13.1 ± 2.9 years). When normalizing AUC(0–24) by TAC-D significant differences were found between CYP3A5 expressors and non-expressors (1701.9 vs. 2718.1 ng*h/mL/mg/kg, p &lt; 0.05). C0 had a poor fit with AUC(0–24) (r2 = 0.5011). The model which included C0, C1 and C4, showed the best performance to predict LSS-AUC(0–24) (r2 = 0.8765) and yielded the lowest precision error (7.1% ± 6.4%) with the lowest fraction (9.8%) of deviated AUC(0–24), in comparison to other LSS equations.

Conclusion: Estimation of LSS-AUC(0–24) with 3 time-points is an advisable and clinically useful option for pediatric kidney recipients using extended-release TAC to provide better guidance of decisions if toxicity or drug inefficacy is suspected. The different CYP3A5 genotypes associated with variable dose requirements reinforce considering genotyping before KTx. Further multi-centric studies with admixed cohorts are needed to determine the short- and long-term clinical benefits.

Evaluation of Limited Sampling Strategies for Bayesian Estimation of Daptomycin Area Under the Concentration-Time Curve: A Short Communication

PURPOSE

Increasing evidence supports daptomycin therapeutic drug monitoring. The author's reference center used to perform therapeutic drug monitoring in patients who receive high-dose daptomycin for bone and joint infections, with a three-sample strategy to estimate the daptomycin daily area under the concentration-time curve (AUC). The objective of this study was to evaluate simpler strategies based on only 2 or 1 sample(s).

METHODS

The authors used the BestDose software to estimate the daptomycin AUC after Bayesian posterior estimation of individual pharmacokinetic (PK) parameters at steady state. The reference AUC (AUCfull) was based on 3 samples obtained predose (T0) and approximately 1 hour (T1) and 6 hours (T6) after the start of a 30-minute infusion of IV daptomycin. It was compared with the AUC based on all possible 2-sample and 1-sample strategies. Bias, imprecision, regression, and Bland-Altman plots were used to assess the performance of the alternative strategies.

RESULTS

Data from 77 patients were analyzed. The mean AUCfull value was 936 ± 373 mg·h/L. The best 2-sample strategy was T0 + T6, with a mean prediction bias of 0.13 mg·h/L and absolute imprecision of 3%. The T0 + T1 strategy also performed well with a mean bias of -10 mg·h/L and imprecision of 3%. The best 1-sample strategy was the T6 sample only with a bias of 2.19 mg·h/L and imprecision of 6%.

CONCLUSIONS

Bayesian estimation of daptomycin AUC based on a two-sample strategy was associated with negligible bias and imprecision compared with the author's usual three-sample strategy. The trough and peak strategy may shorten and simplify patient visits and reduce assay labor and costs.

Evaluation and Validation of the Limited Sampling Strategy of Polymyxin B in Patients with Multidrug-Resistant Gram-Negative Infection

Polymyxin B (PMB) is the final option for treating multidrug-resistant Gram-negative bacterial infections. The acceptable pharmacokinetic/pharmacodynamic target is an area under the concentration–time curve across 24 h at a steady state (AUC_ss,24h) of 50–100 mg·h/L. The limited sampling strategy (LSS) is useful for predicting AUC values. However, establishing an LSS is a time-consuming process requiring a relatively dense sampling of patients. Further, given the variability among different centers, the predictability of LSSs is frequently questioned when it is extrapolated to other clinical centers. Currently, limited data are available on a reliable PMB LSS for estimating AUC_ss,24h. This study assessed and validated the practicability of LSSs established in the literature based on data from our center to provide reliable and ready-made PMB LSSs for laboratories performing therapeutic drug monitoring (TDM) of PMB. The influence of infusion and sampling time errors on predictability was also explored to obtain the optimal time points for routine PMB TDM. Using multiple regression analysis, PMB LSSs were generated from a model group of 20 patients. A validation group (10 patients) was used to validate the established LSSs. PMB LSSs from two published studies were validated using a dataset of 30 patients from our center. A population pharmacokinetic model was established to simulate the individual plasma concentration profiles for each infusion and sampling time error regimen. Pharmacokinetic data obtained from the 30 patients were fitted to a two-compartment model. Infusion and sampling time errors observed in real-world clinical practice could considerably affect the predictability of PMB LSSs. Moreover, we identified specific LSSs to be superior in predicting PMB AUC_ss,24h based on different infusion times. We also discovered that sampling time error should be controlled within −10 to 15 min to obtain better predictability. The present study provides validated PMB LSSs that can more accurately predict PMB AUC_ss,24h in routine clinical practice, facilitating PMB TDM in other laboratories and pharmacokinetics/pharmacodynamics-based clinical studies in the future.

Clinical validation of a liquid chromatography-tandem mass spectrometry method for the quantification of calcineurin and mTOR inhibitors in dried matrix on paper discs

Introduction

Advances in liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) have enabled the quantification of immunosuppressants using microsampling techniques. In this context, dried matrix on paper discs (DMPD) could be a useful alternative to conventional venipuncture. Although analytical validation is necessary to establish the suitability of method performance, it is not sufficient to proceed with its implementation into routine clinical practice. Also necessary is that equivalence between sampling methods be demonstrated in a clinical validation study.

Objetives

To clinically validate a LC-MS/MS method for the quantification of tacrolimus, sirolimus, everolimus and cyclosporin A using DMPD.

Methods

According to the recommendations of international guidelines, at least 40 whole blood (WB) and DMPD paired samples for each analyte were collected by skilled technicians and analyzed using LC-MS/MS. Results were evaluated in terms of statistical agreement and bias values at medical decision points.

Results

For all analytes, Passing-Bablok regression analysis revealed that confidence intervals (CIs) for slopes and intercepts included 1 and 0, respectively. It also showed that biases at medical decision points were not clinically relevant. No statistically significant differences between DMPD and WB were found using difference plots and agreement analysis. In this regard, CIs for bias estimators included 0, and more than 95% of the results fell within the limits of agreement.

Conclusion

The feasibility of the clinical application of simultaneous quantification of tacrolimus, sirolimus, everolimus and cyclosporin A in DMPD was demonstrated. Results showed that this microsampling technique is interchangeable with conventional WB sampling when specimens are collected by trained personnel.

Population Pharmacokinetic Modelling and Limited Sampling Strategies for Therapeutic Drug Monitoring of Pyrazinamide in Patients with Tuberculosis

Pyrazinamide is one of the first-line antituberculosis drugs. The efficacy of pyrazinamide is associated with the ratio of 24-h area under the concentration-time curve (AUC₂₄) to MIC. The objective of this study was to develop and validate a limited sampling strategy (LSS) based on a population pharmacokinetic (popPK) model to predict AUC₂₄. A popPK model was developed using an iterative two-stage Bayesian procedure and was externally validated. Using data from 20 treatment-naive adult tuberculosis (TB) patients, a one compartment model with transit absorption and first-order elimination best described pyrazinamide pharmacokinetics and fed state was the only significant covariate for absorption rate constant (k_a). External validation, using data from 26 TB patients, showed that the popPK model predicted AUC₂₄ with a slight underestimation of 2.1%. LSS were calculated using Monte Carlo simulation (n = 10,000). External validation showed LSS with time points 0 h, 2 h, and 6 h performed best with RMSE of 9.90% and bias of 0.06%. Food slowed absorption of pyrazinamide, but did not affect bioavailability, which may be advantageous in case of nausea or vomiting in which food can be used to diminish these effects. In this study, we successfully developed and validated a popPK model and LSS, using 0 h, 2 h, and 6 h postdose samples, that could be used to perform therapeutic drug monitoring (TDM) of pyrazinamide in TB patients.

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

PURPOSE

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 (AUC_0-12h) in the PBMC of Chinese renal transplant patients.

METHODS

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 AUC_0-12h 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 AUC_0-12h in the PMBC of renal transplant patients were established, and the bias and precision of various equations were identified and compared.

RESULTS

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 AUC_0-12h in PBMCs than those with the 6986 AA or GA genotype (P = 0.026). Conversely, patients with the ABCB1 3435TT genotype had a higher AUC_0-12h 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 AUC_0-12h was C₂-C₄-C₆-C₁₀ (r² = 0.989). The model with C_0.5-C₆ (r² = 0.849) can be used for outpatients who need monitoring to be performed in a short period.

CONCLUSIONS

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 AUC_0-12h in Chinese renal transplant patients. This approach may provide convenience and the possibility for clinical monitoring of TAC intracellular exposure.

Easy and reliable maximum a posteriori Bayesian estimation of pharmacokinetic parameters with the open-source R package mapbayr

Pharmacokinetic (PK) parameter estimation is a critical and complex step in the model‐informed precision dosing (MIPD) approach. The mapbayr package was developed to perform maximum a posteriori Bayesian estimation (MAP‐BE) in R from any population PK model coded in mrgsolve. The performances of mapbayr were assessed using two approaches. First, “test” models with different features were coded, for example, first‐order and zero‐order absorption, lag time, time‐varying covariates, Michaelis–Menten elimination, combined and exponential residual error, parent drug and metabolite, and small or large inter‐individual variability (IIV). A total of 4000 PK profiles (combining single/multiple dosing and rich/sparse sampling) were simulated from each test model, and MAP‐BE of parameters was performed in both mapbayr and NONMEM. Second, a similar procedure was conducted with seven “real” previously published models to compare mapbayr and NONMEM on a PK outcome used in MIPD. For the test models, 98% of mapbayr estimations were identical to those given by NONMEM. Some discordances could be observed when dose‐related parameters were estimated or when models with large IIV were used. The exploration of objective function values suggested that mapbayr might outdo NONMEM in specific cases. For the real models, a concordance close to 100% on PK outcomes was observed. The mapbayr package provides a reliable solution to perform MAP‐BE of PK parameters in R. It also includes functions dedicated to data formatting and reporting and enables the creation of standalone Shiny web applications dedicated to MIPD, whatever the model or the clinical protocol and without additional software other than R.

Exposure levels of mycophenolic acid are associated with comorbidities in children with systemic lupus erythematosus

INTRODUCTION

Little is known about the relationship between exposure levels of mycophenolic acid (MPA), the active metabolite of mycophenolate mofetil (MMF), and comorbidities of systemic lupus erythematosus (SLE) in children. This study aims to explore this association.

METHODS

Longitudinal data from SLE children, who were taking MMF for immunosuppression and under therapeutic drug monitoring (TDM), were retrospectively collected. Area under the concentration-time curve of mycophenolic acid (MPA) over 24 hours (AUC_0-24h) was estimated with Bayesian methods. Logistic regression and random forest models were used to explore the association between comorbidities and MPA exposure levels.

RESULTS

This study included 107 children with 358 times of follow-up (median age 169.02 months). The incidence of diabetes, acute kidney injury (AKI), or pneumonia was significantly associated with AUC_0-24h (odds ratio [OR] 0.991, 95% confidence interval [CI] 0.982-0.999), SLE duration (OR 1.012, 95% CI 1.002-1.022), lymphocyte percentage (OR 0.959, 95% CI 0.925-0.991), plasma albumin levels (OR 0.891, 95% CI 0.843-0.940), use of aspirin (OR 0.292, 95% CI 0.126-0.633) and hydroxychloroquine (OR 0.407, 95% CI 0.184-0.906). The random forest model showed that albumin and AUC_0-24h were two important predictors. The case group (with the three comorbidities) had a mean AUC_0-24h of 73.63 mg · h/L, while the control group had a mean AUC_0-24h of 100.39 mg · h/L.

CONCLUSIONS

Increased levels of MPA exposure are associated with decreased incidence odds of diabetes, AKI or pneumonia in SLE children. An AUC_0-24h of 100.39 mg · h/L or an AUC_0-12h of 50.20 mg · h/L could be used as the targeted exposure level for clinical practice.

Tacrolimus Area Under the Concentration Versus Time Curve Monitoring, Using Home-Based Volumetric Absorptive Capillary Microsampling

BACKGROUND

Therapeutic drug monitoring (TDM) of tacrolimus (Tac) is mandatory in renal transplant recipients (RTxR). Area under the concentration versus time curve (AUC) is the preferred measure for Tac exposure; however, for practical purposes, most centers use trough concentrations as a clinical surrogate. Limited sampling strategies in combination with population pharmacokinetic model-derived Bayesian estimators (popPK-BE) may accurately predict individual AUC. The use of self-collected capillary microsamples could simplify this strategy. This study aimed to investigate the potential of AUC-targeted Tac TDM using capillary microsamples in combination with popPK-BE.

METHODS

A single-center prospective pharmacokinetic study was conducted in standard-risk RTxR (n = 27) receiving Tac twice daily. Both venous and capillary microsamples (Mitra; Neoteryx, Torrance, CA) were obtained across 2 separate 12-hour Tac dosing intervals (n = 13 samples/AUC). Using popPK-BE, reference AUC (AUCref) was determined for each patient using all venous samples. Different limited sampling strategies were tested for AUC predictions: (1) the empiric sampling scheme; 0, 1, and 3 hours after dose and (2) 3 sampling times determined by the multiple model optimal sampling time function in Pmetrics. Agreement between the predicted AUCs and AUCref were evaluated using C-statistics. Accepted agreement was defined as a total deviation index ≤±15%.

RESULTS

The AUC from capillary microsamples revealed high accuracy and precision compared with venous AUCref, and 85% of the AUCs had an error within ±11.9%. Applying microsamples at 0, 1, and 3 hours after dose predicted venous AUCref with acceptable agreement. Patients performed self-sampling with acceptable accuracy.

CONCLUSIONS

Capillary microsampling is patient-centered, making AUC-targeted TDM of Tac feasible without extended hospital stays. Samples obtained 0, 1, and 3 hours after dose, combined with popPK-BE, accurately predict venous Tac AUC.

Limited Sampling Strategy for Estimation of Mycophenolic Acid Exposure in Adult Chinese Heart Transplant Recipients

Background: With the increasing use of mycophenolic acid (MPA) formulations in organ transplantation, the need for personalized immunosuppressive therapy has become well recognized based on therapeutic drug monitoring (TDM) for avoidance of drug-related toxicity while maintaining efficacy. Few studies have assessed area under the 12 h concentration-time curve of MPA (MPA-AUC_0–12h) in heart transplant recipients who received mycophenolate mofetil (MMF) dispersible tablets (MMFdt). The aim of the study was to investigate the pharmacokinetics (PK) of MMFdt combined with tacrolimus and further to develop a practical method for estimation of MPA-AUC_0–12h using a limited sampling strategy (LSS).

Methods: A prospective study in a single center was performed in patients who continuously administrated with MMFdt or MMF capsule (MMFc) for at least 7 days after cardiac transplantation from 2018 to 2020. A total of 48 Chinese adult heart transplant recipients were enrolled. Blood samples were collected before and 0.5, 1, 1.5, 2, 4, 6, 8, 10 and 12 h after MMF administration. The validated high-performance liquid chromatography combined with tandem mass spectrometry method was used to measure MPA concentrations. Non-compartmental pharmacokinetic (PK) analysis was applied to calculate the data obtained from individual recipients by WinNonlin. LSS models were developed for MPA-AUC_0–12h prediction with multivariate stepwise regression analysis.

Results: A large inter-individual variability was observed in AUC_0–12h, T_max, C_max, MRT_0–12h, t_1/2 and CL/F after multiple dosing of MMFdt. However, no significant differences were observed between main PK parameters of MMFdt and MMFc. The best estimation of MPA-AUC_0–12h was achieved with four points: MPA-AUC_0–12h = 8.424 + 0.781 × C_0.5 + 1.263 × C₂ + 1.660 × C₄ + 3.022 × C₆ (R² = 0.844). The mean prediction error (MPE) and mean absolute prediction error (MAPE) of MPA-AUC_0–12h were 2.09 ± 14.05% and 11.17 ± 8.52%, respectively. Both internal and external validations showed good applicability for four-point LSS equation.

Conclusion: The results provide strong evidence for the use of LSS model other than a single time-point concentration of MPA when performing TDM. A four-point LSS equation using the concentrations at 0.5, 2, 4, 6 h is recommended to estimate MPA-AUC_0–12h during early period after transplantation in Chinese adult heart transplant recipients receiving MMFdt or MMFc. However, proper internal and external validations with more patients should be conducted in the future.

Optimal sampling strategies for darunavir and external validation of the underlying population pharmacokinetic model

PURPOSE

A variety of diagnostic methods are available to validate the performance of population pharmacokinetic models. Internal validation, which applies these methods to the model building dataset and to additional data generated through Monte Carlo simulations, is often sufficient, but external validation, which requires a new dataset, is considered a more rigorous approach, especially if the model is to be used for predictive purposes. Our first objective was to validate a previously published population pharmacokinetic model of darunavir, an HIV protease inhibitor boosted with ritonavir or cobicistat. Our second objective was to use this model to derive optimal sampling strategies that maximize the amount of information collected with as few pharmacokinetic samples as possible.

METHODS

A validation dataset comprising 164 sparsely sampled individuals using ritonavir-boosted darunavir was used for validation. Standard plots of predictions and residuals, NPDE, visual predictive check, and bootstrapping were applied to both the validation set and the combined learning/validation set in NONMEM to assess model performance. D-optimal designs for darunavir were then calculated in PopED and further evaluated in NONMEM through simulations.

RESULTS

External validation confirmed model robustness and accuracy in most scenarios but also highlighted several limitations. The best one-, two-, and three-point sampling strategies were determined to be pre-dose (0 h); 0 and 4 h; and 1, 4, and 19 h, respectively. A combination of samples at 0, 1, and 4 h was comparable to the optimal three-point strategy. These could be used to reliably estimate individual pharmacokinetic parameters, although with fewer samples, precision decreased and the number of outliers increased significantly.

CONCLUSIONS

Optimal sampling strategies derived from this model could be used in clinical practice to enhance therapeutic drug monitoring or to conduct additional pharmacokinetic studies.

Evaluation of Bayesian Forecasting Methods for Prediction of Tacrolimus Exposure Using Samples Taken on Two Occasions in Adult Kidney Transplant Recipients

BACKGROUND

Bayesian forecasting-based limited sampling strategies (LSSs) for tacrolimus have not been evaluated for the prediction of subsequent tacrolimus exposure. This study examined the predictive performance of Bayesian forecasting programs/services for the estimation of future tacrolimus area under the curve (AUC) from 0 to 12 hours (AUC0-12) in kidney transplant recipients.

METHODS

Tacrolimus concentrations were measured in 20 adult kidney transplant recipients, 1 month post-transplant, on 2 occasions one week apart. Twelve samples were taken predose and 13 samples were taken postdose at the specified times on the first and second sampling occasions, respectively. The predicted AUC0-12 (AUCpredicted) was estimated using Bayesian forecasting programs/services and data from both sampling occasions for each patient and compared with the fully measured AUC0-12 (AUCmeasured) calculated using the linear trapezoidal rule on the second sampling occasion. The bias (median percentage prediction error [MPPE]) and imprecision (median absolute prediction error [MAPE]) were determined.

RESULTS

Three programs/services were evaluated using different LSSs (C0; C0, C1, C3; C0, C1, C2, C4; and all available concentrations). MPPE and MAPE for the prediction of fully measured AUC0-12 were <15% for each program/service (with the exclusion of when only C0 was used), when using estimated AUC from data on the same (second) occasion. The MPPE and MAPE for the prediction of a future fully measured AUC0-12 were <15% for 2 programs/services (and for the third when participants who had a tacrolimus dose change between sampling days were excluded), when the occasion 1-AUCpredicted, using C0, C1, and C3, was compared with the occasion 2-AUCmeasured.

CONCLUSIONS

All 3 Bayesian forecasting programs/services evaluated had acceptable bias and imprecision for predicting a future AUC0-12, using tacrolimus concentrations at C0, C1, and C3, and could be used for the accurate prediction of tacrolimus exposure in adult kidney transplant recipients.

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.

Validation of a simple liquid chromatography coupled to tandem mass spectrometry method for the simultaneous determination of tacrolimus, sirolimus, everolimus and cyclosporin A in dried matrix on paper discs

INTRODUCTION

Due to its high specificity and sensitivity, liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) is the gold standard method for immunosuppressant quantification in therapeutic drug monitoring. In this context, dried blood spots (DBS) have become a promising strategy as a sample collection procedure. Although the advantages of DBS over venipuncture are well known, this approach has limitations that strongly influence the acceptance of analytical results. Among them, the most important is hematocrit (Ht). The easiest way of overcoming this problem is by analyzing complete spots. In this strategy, called dried matrix on paper discs (DMPD), blood is volumetrically applied on pre-punched discs.

OBJECTIVES

To validate an LC-MS/MS method for the quantification of tacrolimus, sirolimus, everolimus and cyclosporin A using DMPD.

METHODS

The procedure was validated according to international guidelines using a commercial kit. The following performance parameters were evaluated: selectivity, carryover, linearity, accuracy, precision, lower limit of quantitation, relative recovery, commutability and stability. In addition, a method comparison study was performed to evaluate the clinical influence of Ht on the results.

RESULTS

All performance parameters were within acceptance criteria and, hence, it was determined that the validated method is fit for the intended purpose. Likewise, calculated bias values on medical decision levels showed that there was no clinical influence of Ht on the results.

CONCLUSION

Unlike other similar methodologies that have been published, here, a simple method has been fully validated. This is the first LC-MS/MS methodology adapting a commercial kit to use DMPD as a sampling strategy.

Immunosuppressant quantification in intravenous microdialysate - towards novel quasi-continuous therapeutic drug monitoring in transplanted patients

OBJECTIVES

Therapeutic drug monitoring (TDM) plays a crucial role in personalized medicine. It helps clinicians to tailor drug dosage for optimized therapy through understanding the underlying complex pharmacokinetics and pharmacodynamics. Conventional, non-continuous TDM fails to provide real-time information, which is particularly important for the initial phase of immunosuppressant therapy, e.g., with cyclosporine (CsA) and mycophenolic acid (MPA).

METHODS

We analyzed the time course over 8 h of total and free of immunosuppressive drug (CsA and MPA) concentrations measured by liquid chromatography-tandem mass spectrometry (LC-MS/MS) in 16 kidney transplant patients. Besides repeated blood sampling, intravenous microdialysis was used for continuous sampling. Free drug concentrations were determined from ultracentrifuged EDTA-plasma (UC) and compared with the drug concentrations in the respective microdialysate (µD). µDs were additionally analyzed for free CsA using a novel immunosensor chip integrated into a fluorescence detection platform. The potential of microdialysis coupled with an optical immunosensor for the TDM of immunosuppressants was assessed.

RESULTS

Using LC-MS/MS, the free concentrations of CsA (fCsA) and MPA (fMPA) were detectable and the time courses of total and free CsA comparable. fCsA and fMPA and area-under-the-curves (AUCs) in µDs correlated well with those determined in UCs (r≥0.79 and r≥0.88, respectively). Moreover, fCsA in µDs measured with the immunosensor correlated clearly with those determined by LC-MS/MS (r=0.82).

CONCLUSIONS

The new microdialysis-supported immunosensor allows real-time analysis of immunosuppressants and tailor-made dosing according to the AUC concept. It readily lends itself to future applications as minimally invasive and continuous near-patient TDM.

Population pharmacokinetics of mycophenolic acid in pediatric patients with juvenile dermatomyositis and optimization of limited sampling strategy

Juvenile dermatomyositis (JDM) is a rare systemic autoimmune disease specifically affecting children. Mycophenolate mofetil (MMF) is an immunosuppressant used to treat JDM. Mycophenolic acid (MPA) is an active metabolite of MMF. This study aimed to develop a population pharmacokinetic (PPK) model of MPA in children with JDM and optimize the limited sampling strategy (LSS). Fifteen JDM patients treated with MMF, at a median age of 7.35 (range, 3.09-16.1) years, were included. Blood samples were collected at 30 minutes pre-dose, 20 minutes, 60 minutes and 180 minutes post-dose to measure the MPA concentrations. Data were retrospectively collected from the electronic medical records. A two-compartment model with first-order absorption, lag time in absorption, and first-order elimination was developed. Height and co-administered cotrimoxazole were added as the covariates to the model. Concentrations at different time points were simulated and area under the concentration-time curve (AUC_0-12 h) was calculated. By removing one sampling point at a time, AUC_0-12 h from three-point sampling strategy was re-calculated via Bayesian approach. AUC_0-12 h from the three-point sampling strategy (by removing the point at 20 minutes post-dose) had the strongest correlation with AUC_0-12 h from the four-point sampling strategy (Pearson's r = 0.971).

Optimal Sampling Strategies for Therapeutic Drug Monitoring of First-Line Tuberculosis Drugs in Patients with Tuberculosis

Background

The 24-h area under the concentration–time curve (AUC₂₄)/minimal inhibitory concentration ratio is the best predictive pharmacokinetic/pharmacodynamic (PK/PD) parameter of the efficacy of first-line anti-tuberculosis (TB) drugs. An optimal sampling strategy (OSS) is useful for accurately estimating AUC₂₄; however, OSS has not been developed in the fed state or in the early phase of treatment for first-line anti-TB drugs.

Methods

An OSS for the prediction of AUC₂₄ of isoniazid, rifampicin, ethambutol and pyrazinamide was developed for TB patients starting treatment. A prospective, randomized, crossover trial was performed during the first 3 days of treatment in which first-line anti-TB drugs were administered either intravenously or in fasting or fed conditions. The PK data were used to develop OSS with best subset selection multiple linear regression. The OSS was internally validated using a jackknife analysis and externally validated with other patients from different ethnicities and in a steady state of treatment.

Results

OSS using time points of 2, 4 and 8 h post-dose performed best. Bias was < 5% and imprecision was < 15% for all drugs except ethambutol in the fed condition. External validation showed that OSS_2-4-8 cannot be used for rifampicin in steady state conditions.

Conclusion

OSS at 2, 4 and 8 h post-dose enabled an accurate and precise prediction of AUC₂₄ values of first-line anti-TB drugs in this population.

Trial Registration

ClinicalTrials.gov (NCT02121314).

Protein binding of rifampicin is not saturated when using high-dose rifampicin

BACKGROUND

Higher doses of rifampicin are being investigated as a means to optimize response to this pivotal TB drug. It is unknown whether high-dose rifampicin results in saturation of plasma protein binding and a relative increase in protein-unbound (active) drug concentrations.

OBJECTIVES

To assess the free fraction of rifampicin based on an in vitro experiment and data from a clinical trial on high-dose rifampicin.

METHODS

Protein-unbound rifampicin concentrations were measured in human serum spiked with increasing total concentrations (up to 64 mg/L) of rifampicin and in samples obtained by intensive pharmacokinetic sampling of patients who used standard (10 mg/kg daily) or high-dose (35 mg/kg) rifampicin up to steady-state. The performance of total AUC0-24 to predict unbound AUC0-24 was evaluated.

RESULTS

The in vitro free fraction of rifampicin remained unaltered (∼9%) up to 21 mg/L and increased up to 13% at 41 mg/L and 17% at 64 mg/L rifampicin. The highest (peak) concentration in vivo was 39.1 mg/L (high-dose group). The arithmetic mean percentage unbound to total AUC0-24in vivo was 13.3% (range = 8.1%-24.9%) and 11.1% (range = 8.6%-13.6%) for the standard group and the high-dose group, respectively (P = 0.214). Prediction of unbound AUC0-24 based on total AUC0-24 resulted in a bias of -0.05% and an imprecision of 13.2%.

CONCLUSIONS

Plasma protein binding of rifampicin can become saturated, but exposures after high-dose rifampicin are not high enough to increase the free fraction in TB patients with normal albumin values. Unbound rifampicin exposures can be predicted from total exposures, even in the higher dose range.

Model-Based Evaluation of Linear Limited and Bayesian Sparse Sampling for Therapeutic Monitoring of Recombinant Coagulation Factor IX

Dosing of coagulation factor products is mainly determined based on a patient's body weight; however, several studies have reported high interindividual variability in their pharmacokinetics (PK). The objective of this study was to develop and evaluate 2 sparse sampling methods for the estimation of AUC of recombinant factor IX (BeneFIX) as proof of concept for dose individualization. A population pharmacokinetic model was used to generate the plasma factor IX activity-versus-time data. The linear limited sampling model (LLSM) was developed based on the correlation of factor IX activity versus AUC_0-72 hours following screening of several blood sampling times in adolescent and adult subjects (n = 90 subjects). Factor IX trough concentrations were predicted from a relationship established from AUC versus factor IX activity measured 72 hours postdosing. Using the best selected sampling time, the LLSM and Bayesian model were validated in separate data sets (n = 75 subjects). Using the LLSM and Bayesian analysis, a blood sample at 24 hours predicted AUC with bias and root mean square error < 5% and < 15%, respectively. The predicted trough concentrations were ≥1 IU/dL in 99% and 100% of subjects by the LLSM and Bayesian model, respectively. The average factor IX dose for a target AUC of 800 IU·h/dL was 61, 60, and 63 IU/kg using the extensive (reference), LLSM and Bayesian model, respectively. Overall, the AUC, trough concentrations and individualized dosing of recombinant factor IX could be reasonably predicted using the LLSM and Bayesian model.

Pharmacokinetic analysis for model-supported therapeutic drug monitoring of busulfan in Japanese pediatric hematopoietic stem cell transplantation recipients

This prospective observational study analyzed the pharmacokinetics of busulfan in Japanese children and evaluated the predicting accuracy of previous pediatric PPK models of busulfan. This study enrolled five patients (aged 2-12 years, BW 14-48 kg) receiving a busulfan-based conditioning regimen for hematopoietic stem cell transplantation at our hospital between January 2017 and December 2018. All patients received a 2-hour intravenous busulfan infusion four times daily for a total of 16 doses. After the infusions, 51 plasma samples were collected with the plasma busulfan concentration measured by liquid chromatography-tandem mass spectrometry. PPK model fitting was analyzed using the (%MPE) and the (%MAPE). Limited sampling strategies for estimating busulfan AUC were also evaluated. High interpatient variability was observed in the PK parameters. The most suitable PPK model that reflected our data was McCune's two-compartment model (%MPE -8.7, %MAPE 19.3). A combination sampling method using the busulfan concentration at 2 and 6 hours after the start of the first busulfan dose was found to be able to estimate AUC_4 day . These results provide useful information on busulfan therapeutic drug monitoring in the Japanese pediatric population.

Official International Association for Therapeutic Drug Monitoring and Clinical Toxicology Guideline: Development and Validation of Dried Blood Spot-Based Methods for Therapeutic Drug Monitoring

Dried blood spot (DBS) analysis has been introduced more and more into clinical practice to facilitate Therapeutic Drug Monitoring (TDM). To assure the quality of bioanalytical methods, the design, development and validation needs to fit the intended use. Current validation requirements, described in guidelines for traditional matrices (blood, plasma, serum), do not cover all necessary aspects of method development, analytical- and clinical validation of DBS assays for TDM. Therefore, this guideline provides parameters required for the validation of quantitative determination of small molecule drugs in DBS using chromatographic methods, and to provide advice on how these can be assessed. In addition, guidance is given on the application of validated methods in a routine context. First, considerations for the method development stage are described covering sample collection procedure, type of filter paper and punch size, sample volume, drying and storage, internal standard incorporation, type of blood used, sample preparation and prevalidation. Second, common parameters regarding analytical validation are described in context of DBS analysis with the addition of DBS-specific parameters, such as volume-, volcano- and hematocrit effects. Third, clinical validation studies are described, including number of clinical samples and patients, comparison of DBS with venous blood, statistical methods and interpretation, spot quality, sampling procedure, duplicates, outliers, automated analysis methods and quality control programs. Lastly, cross-validation is discussed, covering changes made to existing sampling- and analysis methods. This guideline of the International Association of Therapeutic Drug Monitoring and Clinical Toxicology on the development, validation and evaluation of DBS-based methods for the purpose of TDM aims to contribute to high-quality micro sampling methods used in clinical practice.

Exposure-Toxicity Association of Cyclophosphamide and Its Metabolites in Infants and Young Children with Primary Brain Tumors: Implications for Dosing

PURPOSE

To characterize the population pharmacokinetics of cyclophosphamide, active 4-hydroxy-cyclophosphamide (4OH-CTX), and inactive carboxyethylphosphoramide mustard (CEPM), and their associations with hematologic toxicities in infants and young children with brain tumors. To use this information to provide cyclophosphamide dosing recommendations in this population.

PATIENTS AND METHODS

Patients received four cycles of a 1-hour infusion of 1.5 g/m² cyclophosphamide. Serial samples were collected to measure cyclophosphamide, 4OH-CTX, and CEPM plasma concentrations. Population pharmacokinetic modeling was performed to identify the patient characteristics influencing drug disposition. Associations between drug exposures and metrics reflecting drug-induced neutropenia, erythropenia, and thrombocytopenia were investigated. A Bayesian approach was developed to predict 4OH-CTX exposure using only cyclophosphamide and CEPM plasma concentrations.

RESULTS

Data from 171 patients (0.07-4.9 years) were adequately fitted by a two-compartment (cyclophosphamide) and one-compartment model (metabolites). Young infants (<6 months) exhibited higher mean 4OH-CTX exposure than did young children (138.4 vs. 107.2 μmol/L·h, P < 0.0001). No genotypes exhibited clinically significant influence on drug exposures. Worse toxicity metrics were significantly associated with higher 4OH-CTX exposures. Dosing simulations suggested decreased cyclophosphamide dosage to 1.2 g/m² for young infants versus 1.5 g/m² for children to attain similar 4OH-CTX exposure. Bayesian-modeled 4OH-CTX exposure predictions were precise (mean absolute prediction error 14.8% ± 4.2%) and had low bias (mean prediction error 4.9% ± 5.1%).

CONCLUSIONS

A 4OH-CTX exposure-toxicity association was established, and a decreased cyclophosphamide dosage for young infants was suggested to reduce toxicity in this population. Bayesian modeling to predict 4OH-CTX exposure may reduce clinical processing-related costs and provide insights into further exposure-response associations.

Limited sampling strategy to predict the area under the curve of tacrolimus in Mexican renal transplant pediatric patients receiving Prograf® or non-innovator formulations

TDM of tacrolimus is usually performed with trough levels (C_0h ). However, in pediatric patients, C_0h may not be an adequate marker. The AUC is considered a more suitable indicator of drug exposure. As several blood samples are needed for the estimation of AUC, and LSS for predicting tacrolimus AUC and optimizing the dose adjustment have been proposed. Moreover, in emerging countries such as Mexico, non-innovator formulations, which bioequivalence has not been demonstrated, are frequently used. Hence, the aim of this study was to develop and validate a LSS to predict the tacrolimus AUC_0-12h in Mexican pediatric kidney transplant recipients who received either Prograf^® or non-innovator tacrolimus formulations. A total of 56 pharmacokinetic profiles were randomized into two groups: model development (n = 28) and model validation (n = 28). The limited sampling equations were obtained after a stepwise multiple regression using AUC as the dependent variable and tacrolimus blood concentrations, quantified by CMIA, at different time points as the independent variables. The final equation included observed concentrations at 1 hour (C_1h ) and 4 hours (C_4h ) after dose administration. The predictive performance of the model was adequate in terms of both, bias and precision. Results strongly suggest that the clinical use of this LSS could provide an ethical, cost-, and time-effective method in the TDM of tacrolimus in pediatric patients with kidney transplant. The model proved to be adequate with either Prograf^® or non-innovator tacrolimus formulations of dubious bioequivalence.

Population Pharmacokinetic Analysis of Immediate-Release Oral Tacrolimus Co-administered with Mycophenolate Mofetil in Corticosteroid-Free Adult Kidney Transplant Recipients

BACKGROUND AND OBJECTIVE

Tacrolimus is the mainstay calcineurin inhibitor frequently administered with mycophenolic acid with or without corticosteroids to prevent graft rejection in adult kidney transplant recipients. The primary objective of this study was to develop and evaluate a population pharmacokinetic model characterizing immediate-release oral tacrolimus co-administered with mycophenolate mofetil (a pro-drug of mycophenolic acid) in adult kidney transplant recipients on corticosteroid-free regimens. The secondary objective was to investigate the effects of clinical covariates on the pharmacokinetics of tacrolimus, emphasizing the interacting effects of mycophenolic acid.

METHODS

Population modeling and evaluation were conducted with Monolix (Suite-2018R1) using the stochastic approximation expectation-maximization algorithm in 49 adult subjects (a total of 320 tacrolimus whole-blood concentrations). Effects of clinical variables on tacrolimus pharmacokinetics were determined by population covariate modeling, regression modeling, and categorical analyses.

RESULTS

A two-compartment, first-order absorption with a lag-time, linear elimination, and constant error model best represented the population pharmacokinetics of tacrolimus. The apparent clearance value for tacrolimus was 17.9 l/h (6.95% relative standard error) in our model, which is lower compared with similar subjects on corticosteroid-based therapy. The glomerular filtration rate had significant effects on the apparent clearance and central compartment volume of distribution. Conversely, mycophenolic acid did not affect the apparent clearance of tacrolimus.

CONCLUSION

We have developed and internally evaluated a novel population pharmacokinetic model for tacrolimus co-administered with mycophenolate mofetil in corticosteroid-free adult kidney transplant patients. These findings are clinically important and provide further reasons for conducting therapeutic drug monitoring in this specific population.

The impact of tacrolimus exposure on extrarenal adverse effects in adult renal transplant recipients

AIMS

Tacrolimus has been associated with notable extrarenal adverse effects (AEs), which are unpredictable and impact patient morbidity. The association between model-predicted tacrolimus exposure metrics and standardized extrarenal AEs in stable renal transplant recipients was investigated and a limited sampling strategy (LSS) was developed to predict steady-state tacrolimus area under the curve over a 12-h dosing period (AUC_ss,0-12h ).

METHODS

All recipients receiving tacrolimus and mycophenolic acid ≥6 months completed a 12-h cross-sectional observational pharmacokinetic-pharmacodynamic study. Patients were evaluated for the presence of individual and composite gastrointestinal, neurological, and aesthetic AEs during the study visit. The associations between AEs and tacrolimus exposure metrics generated from a published population pharmacokinetic model were investigated using a logistic regression analysis in NONMEM 7.3. An LSS was determined using a Bayesian estimation method with the same patients.

RESULTS

Dose-normalized tacrolimus AUC_ss,0-12h and apparent clearance were independently associated with diarrhoea, dyspepsia, insomnia and neurological AE ratio. Dose-normalized tacrolimus maximum concentration was significantly correlated with skin changes and acne. No AE associations were found with trough concentrations. Using limited sampling at 0, 2h; 0, 1, 4h; and 0, 1, 2, 4h provided a precise and unbiased prediction of tacrolimus AUC (root mean squared prediction error < 10%), which was not well characterized using trough concentrations only (root mean squared prediction error >15%).

CONCLUSIONS

Several AEs (i.e. diarrhoea, dyspepsia, insomnia and neurological AE ratio) were associated with tacrolimus dose normalized AUC_ss,0-12h and clearance. Skin changes and acne were associated with dose-normalized maximum concentrations. To facilitate clinical implementation, a LSS was developed to predict AUC_ss,0-12h values using sparse patient data to efficiently assess projected immunosuppressive exposure and potentially minimize AE manifestations.

Evaluation of Multiple Linear Regression-Based Limited Sampling Strategies for Enteric-Coated Mycophenolate Sodium in Adult Kidney Transplant Recipients

BACKGROUND

Although multiple linear regression-based limited sampling strategies (LSSs) have been published for enteric-coated mycophenolate sodium, none have been evaluated for the prediction of subsequent mycophenolic acid (MPA) exposure. This study aimed to examine the predictive performance of the published LSS for the estimation of future MPA area under the concentration-time curve from 0 to 12 hours (AUC0-12) in renal transplant recipients.

METHODS

Total MPA plasma concentrations were measured in 20 adult renal transplant patients on 2 occasions a week apart. All subjects received concomitant tacrolimus and were approximately 1 month after transplant. Samples were taken at 0, 0.33, 0.5, 1, 1.5, 2, 2.5, 3, 3.5, 4, 6, and 8 hours and 0, 0.25, 0.5, 0.75, 1, 1.25, 1.5, 2, 3, 4, 6, 9, and 12 hours after dose on the first and second sampling occasion, respectively. Predicted MPA AUC0-12 was calculated using 19 published LSSs and data from the first or second sampling occasion for each patient and compared with the second occasion full MPA AUC0-12 calculated using the linear trapezoidal rule. Bias (median percentage prediction error) and imprecision (median absolute prediction error) were determined.

RESULTS

Median percentage prediction error and median absolute prediction error for the prediction of full MPA AUC0-12 were <15% for 4 LSSs, using the data from the same (second) occasion. One equation (1.583C1 + 0.765C2 + 0.369C2.5 + 0.748C3 + 1.518C4 + 2.158C6 + 3.292C8 + 3.6690) showed bias and imprecision <15% for the prediction of future MPA AUC0-12, where the predicted AUC0-12 from the first occasion was compared with the full AUC0-12 from the second. All LSSs with an acceptable predictive performance included concentrations taken at least 6 hours after the dose.

CONCLUSIONS

Only one LSS had an acceptable bias and precision for future estimation. Accurate dosage prediction using a multiple linear regression-based LSS was not possible without concentrations up to at least 8 hours after the dose.

Population Pharmacokinetics of Tacrolimus in Transplant Recipients: What Did We Learn About Sources of Interindividual Variabilities?

Tacrolimus, a calcineurin inhibitor, is a common immunosuppressant prescribed after organ transplantation and has notable inter- and intrapatient pharmacokinetic variability. The sources of variability have been investigated using population pharmacokinetic modeling over the last 2 decades. This article provides an updated synopsis on published nonlinear mixed-effects analyses developed for tacrolimus in transplant recipients. The objectives were to establish a detailed overview of the current data and to investigate covariate relationships determined by the models. Sixty-three published analyses were reviewed, and data regarding the study design, modeling approach, and resulting findings were extracted and summarized. Most of the studies investigated tacrolimus pharmacokinetics in adult and pediatric renal and liver transplants after administration of the immediate-release formulation. Model structures largely depended on the study sampling strategy, with ∼50% of studies developing a 1-compartment model using trough concentrations and a 2-compartment model with delayed absorption from intensive sampling. The CYP3A5 genotype, as a covariate, consistently impacted tacrolimus clearance, and dosing adjustments were required to achieve similar drug exposure among patients. Numerous covariates were identified as sources of interindividual variability on tacrolimus pharmacokinetics with limited consistency across these studies, which may be the result of the study designs. Additional analyses are required to further evaluate the potential impact of these covariates and the clinical implementation of these models to guide tacrolimus dosing recommendations. This article may be useful for guiding the design of future population pharmacokinetic studies and provides recommendations for the selection of an existing optimal model to individualize tacrolimus therapy.

Comparative Analysis of Ampicillin Plasma and Dried Blood Spot Pharmacokinetics in Neonates

BACKGROUND

Dried blood spot (DBS) is a practical sampling strategy for pharmacokinetic studies in neonates. The utility of DBS to determine the population pharmacokinetics (pop-PK) of ampicillin, as well as accuracy versus plasma samples, was evaluated.

METHODS

An open-label, multicenter, opportunistic, prospective study was conducted in neonates. Ampicillin concentrations from plasma and DBS (CONCPlasma and CONCDBS) were measured by liquid chromatographic tandem mass spectrometry and analyzed using pop-PK and statistical (including transformation) approaches.

RESULTS

A total of 29 paired plasma and DBS samples from 18 neonates were analyzed. The median (range) gestational age and postnatal age were 37 (27-41) weeks and 8 (1-26) days, respectively. The geometric mean of CONCDBS to CONCPlasma ratio was 0.56. Correlation analysis demonstrated strong association between CONCPlasma and CONCDBS (r = 0.902, analysis of variance P < 0.001). Using linear regression transformation, the estimated CONCPlasma (eCONCPlasma) was derived using (CONCDBS - 3.223)/0.51. The median bias and geometric mean ratio improved to -11% and 0.88 (Wilcoxon signed-rank test, P < 0.001), respectively, when comparing eCONCPlasma to CONCPlasma. Furthermore, using pop-PK modeling, the median bias (interquartile range) for clearance and individual predicted concentrations improved to 8% (-11 to 50) and -8% (-34 to 11), respectively, when eCONCPlasma was used.

CONCLUSIONS

After transformation, DBS sampling accurately predicted ampicillin exposure in neonates.

What is the role for population pharmacokinetics in hemophilia?

Prevention of bleeding in hemophilia requires that plasma levels of the deficient factor exceed the desired minimum target level. Large interindividual variability suggests that knowledge of individual pharmacokinetic (PK) would help to achieve this goal, simultaneously minimizing infusion frequency and the amount of concentrate used. Population PK (PopPK) allows for the incorporation of determinants of interpatient variability and eliminates the need for extensive postinfusion plasma sampling. Barriers to implementation of PopPK are the need for concentrate specific models, Bayesian calculation power, specific expertise for validation and appraisal of forecasted estimates. The Web Accessible Population Pharmacokinetic Service – Hemophilia ( www.wapps-hemo.org ), developed by an international research network of hemophilia centers will test if PK-guided dose individualization can improve patient important outcomes in hemophilia.

Dried Blood Spot sampling in psychiatry: Perspectives for improving therapeutic drug monitoring

Assessment of drug concentrations is indicated to guide dosing of a selected number of drugs used in psychiatry. Conventionally this is done by vena puncture. Novel sampling strategies such as dried blood spot (DBS) sampling have been developed for various drugs, including antipsychotics, antidepressants and mood-stabilizers. DBS sampling is typically performed by means of a finger prick. This method allows for remote sampling, which means that patients are not required to travel to a health care facility. The number of DBS assays for drugs used in psychiatry has increased over the last decade and includes antidepressants (tricyclic and serotonin and/or norepinephrine reuptake inhibitors), mood stabilizers and first- and second-generation antipsychotics. Available assays often comply with analytical validation criteria but are seldom used in routine clinical care. Little attention has been paid to the clinical validation and implementation processes of home sampling. Ideally, not only medicines but also clinical chemistry parameters should be measured within the same sample. This article reflects on the position of DBS remote sampling in psychiatry and provides insight in the requisites of making such a sampling tool successful.

Data Analysis Protocol for the Development and Evaluation of Population Pharmacokinetic Models for Incorporation Into the Web-Accessible Population Pharmacokinetic Service - Hemophilia (WAPPS-Hemo)

BACKGROUND

Hemophilia is an inherited bleeding disorder caused by a deficiency in a specific clotting factor. This results in spontaneous bleeding episodes and eventual arthropathy. The mainstay of hemophilia treatment is prophylactic replacement of the missing factor, but an optimal regimen remains to be determined. Rather, individualized prophylaxis has been suggested to improve both patient safety and resource utilization. However, uptake of this approach has been hampered by the demanding sampling schedules and complex calculations required to obtain individual estimates of pharmacokinetic (PK) parameters. The use of population pharmacokinetics (PopPK) can alleviate this burden by reducing the number of plasma samples required for accurate estimation, but few tools incorporating this approach are readily available to clinicians.

OBJECTIVE

The Web-accessible Population Pharmacokinetic Service - Hemophilia (WAPPS-Hemo) project aims to bridge this gap by providing a Web-accessible service for the reliable estimation of individual PK parameters from only a few patient samples. This service is predicated on the development of validated brand-specific PopPK models.

METHODS

We describe the data analysis plan for the development and evaluation of each PopPK model to be incorporated into the WAPPS-Hemo platform. The data sources and structure of the dataset are discussed first, followed by the procedures for handling both data below limit of quantification (BLQ) and absence of such BLQ data. Next, we outline the strategies for building the appropriate structural and covariate models, including the possible need for a process algorithm when PK behavior varies between subjects or significant covariates are not provided. Prior to use in a prospective manner, the models will undergo extensive evaluation using a variety of techniques such as diagnostic plots, bootstrap analysis and cross-validation. Finally, we describe the incorporation of a validated PopPK model into the Bayesian post hoc model to produce individualized estimates of PK parameters.

RESULTS

Dense PK data has been collected for more than 20 brands of factor concentrate from both industry-sponsored and investigator-driven studies. The model development process is underway for the majority of molecules, with refinement and validation to be completed in 2017. Further, the WAPPS-Hemo co-investigator network has contributed more than 300 PK assessments for use in model development and evaluation. This constitutes the largest repository of this type of PK data globally.

CONCLUSIONS

The WAPPS-Hemo service aims to eliminate barriers to the uptake of individualized PK-tailored hemophilia treatment. By incorporating this tool into routine practice, clinicians can implement a personalized dosing strategy without performing rigorous sampling or complex calculations. This service is centred on validated models developed according to the robust approach to PopPK modeling described herein.

CLINICALTRIAL

ClinicalTrials.gov NCT02061072; https://clinicaltrials.gov/ct2/show/NCT02061072 (Archived by WebCite at http://www.webcitation.org/6mRIXJh55).

Clinical pharmacy service practice in a Chinese tertiary hospital

Clinical pharmacy service is focused on the rationality and safety of medication therapy. Clinical pharmacists play an important role in designing therapeutic regimen, preventing medication errors, reducing the incidence of adverse drug reaction, and saving medical costs. Although clinical pharmacy service in China is in its early stage, its development is rapid. In this manuscript, the working model of clinical pharmacists in a Chinese tertiary hospital is introduced, including ward rounds, consultation, stewardship of antimicrobial therapy, drug adverse reaction monitoring, therapeutic drug monitoring, clinical pharmacokinetics and pharmacogenetics, and training system. With the efforts of clinical pharmacists, there will be a significant increase in the optimization of medication therapy and a notable reduction in preventable adverse drug events as well as health-care cost in China.

The use of pharmacokinetics in dose individualization of factor VIII in the treatment of hemophilia A

INTRODUCTION

Hemophilia A is a bleeding disorder resulting from a lack of clotting factor VIII (FVIII), and treatment typically consists of prophylactic replacement of the deficient factor. However, high between subject variability precludes the development of a 'one size fits all' dosing strategy and necessitates an individualized approach. We sought to summarize the data on the pharmacokinetics of FVIII available as a basis for the development of population pharmacokinetic models to be used in dose tailoring. Areas covered: We reviewed the pharmacokinetics of FVIII as used for the treatment of hemophilia A, with a focus on the variability observed between patients and the application of pharmacokinetic methods to dose individualization. We also explored the covariates affecting pharmacokinetic parameters, the differences between plasma-derived and recombinant FVIII and the development of extended half-life products. Expert opinion: The pharmacokinetics of factor VIII in patients with hemophilia shows a high interpatient variability, and is affected by age, weight, level of von Willebrand factor, and blood group. A population approach to estimating individual pharmacokinetics is likely to provide the most successful strategy to tailor factor concentrate dosing to the individual needs and to ensure optimal patient outcomes, while also improving the cost-effectiveness of prophylactic replacement therapy.

Validation of a 2-Point Limited Sampling Strategy to Predict the Tacrolimus Area-Under-the-12-Hour-Curve in Kidney Transplant Recipients

BACKGROUND

Limited sampling strategies (LSS) have been proposed for predicting total exposure of tacrolimus, a widely used immunosuppressant in transplantation. This study aims to validate the equation developed by Wong et al for estimation of the tacrolimus area-under-the-concentration-over-12-hour-curve (AUC0-12) and to assess the effects of hemoglobin and duration of tacrolimus therapy on predictive performance of the equation in adult kidney transplant recipients.

METHODS

Seven time point blood concentration profiles were collected from 31 stable kidney transplant recipients who received oral tacrolimus twice daily. The chemiluminescent microparticle immunoassay method was used to determine the tacrolimus concentration. Measured AUC0-12 (AUCm) was calculated by the linear trapezoidal rule. Predicted AUC0-12 (AUCp) was calculated using the equation that used tacrolimus concentrations measured at 2 hours (C2) and 4 hours (C4) after dose: 16.2 + 2.4(C2) + 5.9(C4). Predictive performance of the equation was determined by calculating bias and precision. Agreement between AUCp and AUCm was assessed. The effects of hemoglobin and duration of tacrolimus therapy on bias and precision were also evaluated.

RESULTS

The median (interquartile range) of AUCm was 133.00 (98.25, 185.70) ng·h·mL. The AUCp well correlated with the AUCm (r = 0.962, P < 0.001). The equation had a mean percentage prediction error of -2.22% (95% CI, -5.14 to 0.71), mean absolute percentage prediction error of 6.67% (95% CI, 4.92-8.42), and root mean squared error (%CV) of 14.08 (10.29%) ng·h·mL. A Bland-Altman plot showed good agreement between AUCp and AUCm with a mean bias of -5.43 ng·h·mL (95% CI, -10.28 to -0.59). The hemoglobin level and duration of tacrolimus therapy did not influence the predictive performance of the equation.

CONCLUSIONS

The equation had low bias and high precision in predicting the AUC0-12 of tacrolimus. The equation is a simple and reliable tool for estimating tacrolimus exposure.