Optimal sampling strategy development methodology using maximum a posteriori Bayesian estimation

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.

Population pharmacokinetic analysis for dose regimen optimization of vancomycin in Southern Chinese children

Changes in physiological factors may result in large pharmacokinetic variability of vancomycin in pediatric patients, thereby leading to either supratherapeutic or subtherapeutic exposure and potentially affecting clinical outcomes. This study set out to characterize the disposition of vancomycin, quantify the exposure target and establish an optimal dosage regimen among the Southern Chinese pediatric population. Routine therapeutic drug monitoring data of 453 patients were available. We performed a retrospective population pharmacokinetic analysis of hospitalized children prescribed intravenous vancomycin using NONMEM® software. A one-compartment PPK model of vancomycin with body weight and renal functions as covariates based on a cutoff of 2 years old children was proposed in this study. Both internal and external validation showing acceptable and robust predictive performance of the model to estimate PK parameters. The value of area under the curve over 24 h to minimum inhibitory concentration ratio (AUC0-24/MIC) ≥ 260 was a significant predictor for therapeutic efficacy. Monte Carlo simulations served as a model-informed precision dosing approach and suggested that different optimal dose regimens in various scenarios should be considered rather than flat dosing. The evaluation of vancomycin exposure-efficacy relationship indicated that lower target level of AUC0-24/MIC may be needed to achieve clinical effectiveness in children, which was used to derive the recommended dosing regimen. Further prospective studies will be needed to corroborate and elucidate these results.

Eculizumab dose tapering should take into account the nonlinearity of its pharmacokinetics

AIMS

Eculizumab is a monoclonal antibody targeting complement protein C5 used in renal diseases. As recommended dosing regimen leads to unnecessarily high concentrations in some patients, tailored dosing therapeutic drug monitoring was proposed to reduce treatment cost. The objectives of the present work were (i) to investigate the target-mediated elimination of eculizumab and (ii) whether a pharmacokinetic model integrating a nonlinear elimination allows a better prediction of eculizumab concentrations than a linear model.

METHODS

We analysed 377 eculizumab serum concentrations from 44 patients treated for atypical haemolytic uraemic syndrome and C3 glomerulopathy with a population pharmacokinetic approach. Critical concentrations (below which a non-log-linear decline of concentration over time is evidenced) were computed to estimate the relevance of the target-mediated elimination. Simulations of dosing regimens were then performed to predict probabilities of target attainment (i.e. trough >100 mg/L).

RESULTS

Pharmacokinetics of eculizumab was nonlinear and followed a mixture of first-order (CL = 1.318 mL/day/kg) and Michaelis-Menten elimination (Vmax = 26.07 mg/day, Km = 24.06 mg/L). Volume of distribution (72.39 mL/kg) and clearance were weight-dependent. Critical concentrations (Vmax/CL) ranged from 144.7 to 759.7 mg/L and were inversely related to body weight (P = .013). Nonlinearity was thus noticeable at therapeutic concentrations. Simulations predicted that 1200 mg of eculizumab every 21 days would allow 85% and 76% of patients to maintain a therapeutic exposure, for 50 or 90 kg body weight, respectively.

CONCLUSIONS

Our study investigates the nonlinear elimination of eculizumab and discusses the importance of accounting for eculizumab target-mediated elimination in therapeutic drug monitoring.

Optimal starting dosing regimen of intravenous oxytocin for labor induction based on the population kinetic-pharmacodynamic model of uterine contraction frequency

BACKGROUND

Intravenous oxytocin is commonly used for labor induction. However, a consensus on the initial dosing regimen is lac with conflicting research findings and varying guidelines. This study aimed to develop a population kinetic-pharmacodynamic (K-PD) model for oxytocin-induced uterine contractions considering real-world data and relevant influencing factors to establish an optimal starting dosing regimen for intravenous oxytocin.

METHODS

This retrospective study included pregnant women who underwent labor induction with intravenous oxytocin at Peking University Third Hospital in 2020. A  population K-PD model was developed to depict the time course of uterine contraction frequency (UCF), and covariate screening identified significant factors affecting the pharmacokinetics and pharmacodynamics of oxytocin. Model-based simulations were used to optimize the current starting regimen based on specific guidelines.

RESULTS

Data from 77 pregnant women with 1095 UCF observations were described well by the K-PD model. Parity, cervical dilation, and membrane integrity are significant factors influencing the effectiveness of oxytocin. Based on the model-based simulations, the current regimens showed prolonged onset times and high infusion rates. This study proposed a revised approach, beginning with a rapid infusion followed by a reduced infusion rate, enabling most women to achieve the target UCF within approximately 30 min with the lowest possible infusion rate.

CONCLUSION

The K-PD model of oxytocin effectively described the changes in UCF during labor induction. Furthermore, it revealed that parity, cervical dilation, and membrane integrity are key factors that influence the effectiveness of oxytocin. The optimal starting dosing regimens obtained through model simulations provide valuable clinical references for oxytocin treatment.

Pharmacokinetics of Imatinib Mesylate and Development of Limited Sampling Strategies for Estimating the Area under the Concentration-Time Curve of Imatinib Mesylate in Palestinian Patients with Chronic Myeloid Leukemia

BACKGROUND AND OBJECTIVE

Imatinib is a tyrosine kinase inhibitor used in the treatment of chronic myeloid leukemia (CML). The area under the concentration-time curve (AUC) is a pharmacokinetic parameter that symbolizes overall exposure to a drug, which is correlated with complete cytogenetic and treatment responses to imatinib, as well as its side effects in patients with CML. The limited sampling strategy (LSS) is considered a sufficiently precise and practical method that can be used to estimate pharmacokinetic parameters such as AUC, without the need for frequent, costly, and inconvenient blood sampling. This study aims to investigate the pharmacokinetic parameters of imatinib, develop and validate a reliable and practical LSS for estimating imatinib AUC0-24, and determine the optimum sampling points for predicting the imatinib AUC after the administration of once-daily imatinib in Palestinian patients with CML.

METHOD

Pharmacokinetic profiles, involving six blood samples collected during a 24-h dosing interval, were obtained from 25 Palestinian patients diagnosed with CML who had been receiving imatinib for at least 7 days and had reached a steady-state level. Imatinib AUC0-24 was calculated using the trapezoidal rule, and linear regression analysis was performed to assess the relationship between measured AUC0-24 and concentrations at each sampling time. All developed models were analyzed to determine their effectiveness in predicting AUC0-24 and to identify the optimal sampling time. To evaluate predictive performance, two error indices were employed: the percentage of root mean squared error (% RMSE) and the mean predictive error (% MPE). Bland and Altman plots, along with mountain plots, were utilized to assess the agreement between measured and predicted AUC.

RESULTS

Among the one-timepoint estimations, predicted AUC0-24 based on concentration of imatinib at the eighth hour after administration (C8-predicted AUC0-24) demonstrated the highest correlation with the measured AUC (r2 = 0.97, % RMSE = 6.3). In two-timepoint estimations, the model consisting of C0 and C8 yielded the highest correlation between predicted and measured imatinib AUC (r2 = 0.993 and % RMSE = 3.0). In three-timepoint estimations, the combination of C0, C1, and C8 provided the most robust multilinear regression for predicting imatinib AUC0-24 (r2 = 0.996, % RMSE = 2.2). This combination also outperformed all other models in predicting AUC. The use of a two-timepoint limited sampling strategy (LSS) for predicting AUC was found to be reliable and practical. While C0/C8 exhibited the highest correlation, the use of C0/C4 could be a more practical and equally accurate choice. Therapeutic drug monitoring of imatinib based on C0 can also be employed in routine clinical practice owing to its reliability and practicality.

CONCLUSION

The LSS using one timepoint, especially C0, can effectively predict imatinib AUC. This approach offers practical benefits in optimizing dose regimens and improving adherence. However, for more precise estimation of imatinib AUC, utilizing two- or three-timepoint concentrations is recommended over relying on a single point.

A new pharmacokinetic model of urinary methotrexate to assess adherence in rheumatoid arthritis

BACKGROUND AND OBJECTIVES

Methotrexate (MTX) is the first-line therapy for rheumatoid arthritis (RA). While therapeutic adherence is essential to successful management, no objective MTX assay is currently available. Using population pharmacokinetic modelling (PopPK), our objective was to describe the urinary MTX (MTXu) kinetics in treated patients and to evaluate its abilities to assess the MTX-adherence.

METHODS

The association between urinary methotrexate level and methotrexate administration was assessed using a generalized linear model. Then, a population pharmacokinetic model was developed based on data from 59 patients using with Monolix 2021. R2. Simulations were run to establish a reference kinetic profile and evaluate the proportion of samples predicted as true positives.

RESULTS

Compared to the control group, multivariate analysis showed that MTXu was independently associated with methotrexate administration (p < 0.0001) with a sensitivity and specificity greater than 99%. The final PopPK model selected was a two-compartment model with first-order absorption and elimination. Internal and external validation of the model met all predefined criteria. When using an analytical assay with a LOQ equal to 1 nM, the proportion of samples predicted as true positives is over 90%, as a function of MTX dose (7.5-25 mg/week) and post-administration sampling days (1-7 days).

CONCLUSION

We developed a pharmacokinetic model able to describe expected patterns of urinary methotrexate. This allowed us to propose a new objective test of MTX adherence, which could help in routine practice to differentiate patients who are truly unresponsive to methotrexate from those who are unresponsive because of non-adherence.

Tutorial on model selection and validation of model input into precision dosing software for model-informed precision dosing

There has been rising interest in using model-informed precision dosing to provide personalized medicine to patients at the bedside. This methodology utilizes population pharmacokinetic models, measured drug concentrations from individual patients, pharmacodynamic biomarkers, and Bayesian estimation to estimate pharmacokinetic parameters and predict concentration-time profiles in individual patients. Using these individualized parameter estimates and simulated drug exposure, dosing recommendations can be generated to maximize target attainment to improve beneficial effect and minimize toxicity. However, the accuracy of the output from this evaluation is highly dependent on the population pharmacokinetic model selected. This tutorial provides a comprehensive approach to evaluating, selecting, and validating a model for input and implementation into a model-informed precision dosing program. A step-by-step outline to validate successful implementation into a precision dosing tool is described using the clinical software platforms Edsim++ and MwPharm++ as examples.

Bayesian optimization of tacrolimus exposure in stable kidney transplant patients

STUDY OBJECTIVE

The objective was to compare tacrolimus AUC0-12 determined by Non-Compartmental Analysis (NCA) using intensive sampling to Maximum a Posteriori-Bayesian (MAP-Bayesian) estimates from robust (n = 9 samples/subject) and sparse (n = 2 samples/subject) sampling in 67 stable KTRs and a validation group of similar patients.

DESIGN

This open-label, prospective, single center 12-h PK study included nine serial samples collected in KTRs to determine steady-state NCA tacrolimus AUC0-12 .

SETTING

This study was conducted at a single site within a large, urban hospital in the western New York area.

PATIENTS

This study described tacrolimus pharmacokinetics in stable kidney transplant recipients on maintenance tacrolimus therapy.

INTERVENTION

Robust and sparse AUC0-12 estimates by a MAP-Bayesian approach were obtained using the Advanced Dosing Solutions (AdDS) and ADAPT5 freeware. Limited sampling strategies were evaluated using the original population PK model (n = 67), which was also assessed using a validation group (n = 15). AUC0-12 agreement was tested by paired t-tests with intraclass correlation coefficient (ICC) and Bland Altman analysis.

MEASUREMENTS AND MAIN RESULTS

A total of 35 Black and 32 White stable KTRs (estimated glomerular filtration rate [eGFR] = 55.2 ± 15.7 mL/min/1.73m2 ) received the tacrolimus dose of 3.4 ± 1.7 mg/study with troughs of 6.8 ± 1.8 ng/mL. The NCA-AUC0-12 was 123.8 ± 33.6 μg·h/L compared to MAP-Bayesian estimates for Robust-AUC0-12 of 124.7 ± 33.3 μg·h/L and optimal 2-specimen Sparse-AUC0-12 of 119.7 ± 32.7 μg·h/L for the training group. Comparison of Robust-AUC0-12 to NCA-AUC0-12 had an ICC of 0.96 (p = 0.99) while comparison of Robust-AUC0-12 to Sparse-AUC0-12 using Pre-dose trough [C(t0h )] and 1 h [C(t1h )] resulted in an ICC of 0.93 (p = 0.014). In the validation group, 5 Black and 10 White KTRs (eGFR = 56.4 ± 16.8 mL/min/1.73m2 ) received a mean tacrolimus dose of 1.9 ± 1.2 mg/study with a trough of 6.0 ± 1.7 ng/mL. The validation group's NCA-AUC0-12 (88.4 ± 33.1 μg·h/L) was comparable to Robust-AUC0-12 (85.1 ± 33.8 μg·h/L, ICC = 0.93; p = 0.12) and Sparse-AUC0-12 determined from C(t0h ) and C(t4h ) (86.7 ± 33.9 μg·h/L, ICC = 0.91; p = 0.61).

CONCLUSION

MAP-Bayesian estimation for patient-specific AUC0-12 using sparse, two-specimen sampling is comparable to NCA and may enhance tacrolimus TDM in stable KTRs.

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.

A Method for Evaluating Robustness of Limited Sampling Strategies—Exemplified by Serum Iohexol Clearance for Determination of Measured Glomerular Filtration Rate

In combination with Bayesian estimates based on a population pharmacokinetic model, limited sampling strategies (LSS) may reduce the number of samples required for individual pharmacokinetic parameter estimations. Such strategies reduce the burden when assessing the area under the concentration versus time curves (AUC) in therapeutic drug monitoring. However, it is not uncommon for the actual sample time to deviate from the optimal one. In this work, we evaluate the robustness of parameter estimations to such deviations in an LSS. A previously developed 4-point LSS for estimation of serum iohexol clearance (i.e., dose/AUC) was used to exemplify the effect of sample time deviations. Two parallel strategies were used: (a) shifting the exact sampling time by an empirical amount of time for each of the four individual sample points, and (b) introducing a random error across all sample points. The investigated iohexol LSS appeared robust to deviations from optimal sample times, both across individual and multiple sample points. The proportion of individuals with a relative error greater than 15% (P15) was 5.3% in the reference run with optimally timed sampling, which increased to a maximum of 8.3% following the introduction of random error in sample time across all four time points. We propose to apply the present method for the validation of LSS developed for clinical use.

Developmental Population Pharmacokinetics-Pharmacodynamics of Meropenem in Chinese Neonates and Young Infants: Dosing Recommendations for Late-Onset Sepsis

The pharmacokinetic (PK) studies of meropenem in Chinese newborns with late-onset sepsis (LOS) are still lacking. Causative pathogens of LOS and their susceptibility patterns in China differ from the data abroad. We, therefore, conducted a developmental population pharmacokinetic−pharmacodynamic analysis in Chinese newborns with the goal to optimize meropenem dosing regimens for LOS therapy. An opportunistic sampling strategy was used to collect meropenem samples, followed by model building and validation. A Monte Carlo simulation was performed to show the probability of target attainment (PTA) for various dosages. The information from 78 newborns (postmenstrual age: 27.4−46.1 weeks) was compiled and had a good fit to a 1-compartment model that had first order elimination. The median (range) values of estimated weight−normalized volume of distribution (V)and clearance (CL) were 0.60 (0.51−0.69) L/kg and 0.16 (0.04−0.51) L/h/kg, respectively. Covariate analysis revealed that postnatal age (PNA), gestational age (GA) and current weight (CW) were the most important factors in describing meropenem PK. Simulation results showed for LOS with a minimal inhibitory concentration (MIC) of 8 mg/L, the doses of 30 mg/kg 3 times daily (TID) as a 1-h infusion for newborns with GA ≤ 37 weeks and 40 mg/kg TID as a 3-h infusion for those with GA > 37 weeks were optimal, with PTA of 71.71% and 75.08%, respectively. In conclusion, we proposed an evidence-based dosing regimen of meropenem for LOS in Chinese newborns by using the population pharmacokinetic−pharmacodynamic analysis, based on domestic common pathogens and their susceptibility patterns.

Optimal exposure to docetaxel in adjuvant chemotherapy for early-stage breast cancer

WHAT IS KNOWN AND OBJECTIVE

Drug-induced neutropenia is the main reason for the dose limitation of docetaxel in patients with breast cancer. The area under the drug concentration-time curve (AUC) of docetaxel is associated with neutropenia. However, the optimal exposure to docetaxel for receiving postoperative adjuvant chemotherapy remains unclear. Therefore, we aimed to evaluate the relationship between the docetaxel AUC and neutropenia, identify potential influencing factors, and explore the best monitoring target for docetaxel when treating patients with early-stage breast cancer using a population pharmacokinetic (PopPK) model.

METHODS

Docetaxel plasma concentration, demographics, clinical data, and related laboratory data were collected. PopPK analyses were performed using a nonlinear mixed-effect modelling program. The docetaxel AUC was determined using the maximum a posteriori Bayesian (MAPB) method. The docetaxel exposure-toxicity threshold measured from the AUC for neutropenia was determined using the receiver operating characteristic (ROC) curve. The correlation between docetaxel exposure and neutropenia was analysed using multivariable logistic regression.

RESULTS

Among the 70 participants, 47 (67.1%) developed severe neutropenia. The PopPK analysis showed that the typical drug clearance (CL) rate was 37.4 L/h. Age was a significant covariate of CL rate, and aspartate aminotransferase and albumin levels were covariables of the volume of distribution. The multivariable regression analysis showed that AUC >3.0 mg.h/L (odds ratio [OR], 5.940; 95% confidence interval [CI], 1.693-20.843; P = 0.005), platinum use (OR, 0.156; 95% CI, 0.043-0.562; P = 0.005) and baseline haemoglobin level (OR, 0.938; 95% CI, 0.887-0.993; P = 0.027) were significant factors influencing the occurrence of grade 3/4 neutropenia. The AUC of first cycle may not predict the occurrence rates of grade 3/4 neutropenia in later cycles.

WHAT IS NEW AND CONCLUSION

We developed a docetaxel PopPK model for patients with early-stage breast cancer. Age and AST and ALB levels were significant covariates. AUC estimated using the MAPB method can predict the toxicity of docetaxel in patients with breast cancer. Docetaxel AUC >3.0 mg.h/L, absence of platinum use and low baseline haemoglobin level were risk factors for docetaxel-induced grade 3/4 neutropenia.

STUDY REGISTRATION

Chinese Clinical Trial Center Registry (ChiCTR2200056460).

Personalized tobramycin dosing in children with cystic fibrosis: a comparative clinical evaluation of log-linear and Bayesian methods

BACKGROUND

Children with cystic fibrosis (CF) pulmonary exacerbations receive IV tobramycin therapy, with dosing guided by either log-linear regression (LLR) or Bayesian forecasting (BF).

OBJECTIVES

To compare clinical and performance outcomes for LLR and BF.

PATIENTS AND METHODS

A quasi-experimental intervention study was conducted at a tertiary children's hospital. Electronic medical records were extracted (from January 2015 to September 2021) to establish a database consisting of pre-intervention (LLR) and post-intervention (BF) patient admissions and relevant outcomes. All consecutive patients treated with IV tobramycin for CF pulmonary exacerbations guided by either LLR or BF were eligible.

RESULTS

A total of 376 hospital admissions (LLR = 248, BF = 128) for CF pulmonary exacerbations were included. Patient demographics were similar between cohorts. There were no significant differences found in overall hospital length of stay, rates of re-admission within 1 month of discharge or change in forced expiratory volume in the first second (Δ FEV1) at the end of tobramycin treatment. Patients treated with LLR on average had twice the number of therapeutic drug monitoring (TDM) blood samples collected during a single hospital admission. The timeframe for blood sampling was more flexible with BF, with TDM samples collected up to 16 h post-tobramycin dose compared with 10 h for LLR. The tobramycin AUC0-24 target of ≥100 mg/L·h was more frequently attained using BF (72%; 92/128) compared with LLR (50%; 124/248) (P < 0.001). Incidence of acute kidney injury was rare in both groups.

CONCLUSIONS

LLR and BF result in comparable clinical outcomes. However, BF can significantly reduce the number of blood collections required during each admission, improve dosing accuracy, and provide more reliable target concentration attainment in CF children.

Starting dose selection of palbociclib in Chinese patients with breast cancer based on population kinetic-pharmacodynamic model of neutropenia

Neutropenia is the most common adverse event (AE) of palbociclib, an oral CDK4/6 inhibitor for breast cancer. Neutropenia increases the risk of infection and is even life threatening. Asian patients generally suffer more severe neutropenia from palbociclib treatment, but the label does not recommend a reduction in the starting dose for Asian patients. Therefore, the study aimed to explore the exposure-response (E-R) relationship in Chinese patients and preliminarily generate a scale for starting dose selection of palbociclib in Chinese patients. After comparing the kinetic-pharmacodynamic (K-PD) and the pharmacokinetic/pharmacodynamic (PK/PD) model, a semi-mechanistic K-PD model was selected and developed on the basis of real-world data from 28 patients with breast cancer to describe the time course of longitudinal absolute neutrophil counts (ANC). The longitudinal ANC data were well described by the population K-PD model with reasonable parameters: mean transit time (MTT) of 198 h, feedback parameter (γ) of 0.317, baseline ANC level (Circ₀) of 3.36 × 10⁹ L^-1, drug effect coefficient (k_d) of 0.0349, and drug effect power (β) of 0.383. No covariate was included in the final model. The model showed that palbociclib dose-dependently reduced ANC levels in a Chinese population, and lower baseline ANC level was associated with more severe neutropenia. The dose selection scale suggested that palbociclib 125 mg daily was appropriate for Chinese patients with Circ₀ higher than 3.75 × 10⁹ L^-1. In summary, the K-PD model of palbociclib well described the longitudinal ANC in Chinese patients. Besides, the starting dose selection scale may provide reference for clinicians during individualized therapy.

Improving the efficacy for meropenem therapy requires a high probability of target attainment in critically ill infants and children

Probability of target attainment is the key factor influencing the outcome of meropenem therapy. The objective of the present study was to evaluate the relationship between the time in which the plasma free concentration of meropenem exceeds the minimum inhibitory concentration of pathogens (fT_>MIC) during therapy and the clinical outcome of treatment to optimize meropenem therapy. Critically ill children with infections who had received intravenous meropenem monotherapy were included. The relationship between fT_>MIC of meropenem and effectiveness and safety were explored. Data from 53 children (mean age ± standard deviation, 26 months ± 38) were available for final analysis. Children with fT_>MIC ≥ 5.6 h (n = 14) had a more significant improvement in antibacterial efficacy in terms of decrease in fever (p = 0.02), white blood cell count (p = 0.014), and C-reactive protein (p = 0.02) compared with children with fT_>MIC < 5.6 h (n = 39) after meropenem therapy completed. No drug-related adverse events were shown to have a causal association with meropenem therapy. Our study shows the clinical benefits of sufficient target attainment of meropenem therapy. Meeting a suitable pharmacodynamic target attainment of meropenem is required to ensure better antibacterial efficacy in critically ill infants and children.

Clinical Trial Registration:clinicaltrials.gov, Identifier NCT03643497.

Clinical Utility of A Model-based Amoxicillin Dosage Regimen in Neonates with Early-Onset Sepsis

Early-onset sepsis (EOS) is one of the most significant causes of morbidity and mortality in neonates. Currently, amoxicillin is empirically used to treat neonates with EOS. However, data on its effectiveness in neonates with EOS are still limited. Therefore, we aimed to evaluate the pharmacodynamics (PD) target attainment and effectiveness of a model-based amoxicillin dosage regimen in these neonates. We used a previously developed model and collected additional clinical data from the EOS neonates who used the model-based dosage regimen (25 mg/kg q12h). The primary outcomes were PD target attainment (free drug concentration above MIC during 70% of the dosing interval) and treatment failure rate. The secondary endpoints were length of amoxicillin treatment, duration of hospitalization, etc. Seventy-five neonates (postmenstrual age 28.4-41.6 weeks) were enrolled. A total of 70 (93.3%) neonates reached their PD target using 1 mg/L as the MIC breakpoint. The treatment failure rate was 10.7%.

Optimization of the vancomycin administration regimen by clinical pharmacists based on a population pharmacokinetics model: a prospective interventional study

In vancomycin treatment, the rates of correct blood sampling and initial trough concentrations within the target range are very low. Studies of interventions by clinical pharmacists based on population pharmacokinetics (PPK) models are limited. This study aimed to evaluate the intervention effect of clinical pharmacist-mediated optimization of the vancomycin administration regimen based on a PPK model. Retrospectively enrolled patients constituted the control group, and prospectively enrolled patients constituted the intervention group. The vancomycin administration regimen, trough concentration, pharmacokinetic parameters, and clinical outcomes of the two groups were compared. The control and intervention groups comprised 236 and 138 patients, respectively. Compared with those in the control group, the therapeutic drug monitoring (TDM) and correct TDM sampling time rates in the intervention group were significantly higher (76.92% vs. 43.59%; 63.9% vs. 39.0%, both p < 0.001). The rates of an initial trough concentration within 10-20 mg/L and an adjusted regimen were also significantly higher in the intervention group (55.80% vs. 30.51%, 71.95% vs. 39.18%, both p < 0.001). The rate of an area under the curve (AUC) within 400-650 mg·h/L was higher in the intervention group than in the control group (52.7% vs. 36.6%, p < 0.001). The eradication rates of Gram-positive bacteria were 91.4% in the intervention group and 81.3% in the control group (p = 0.049). Eight patients developed acute kidney injury (AKI) in the control group; however, no AKI occurred in the intervention group (p = 0.029). Intervention by clinical pharmacists can increase the rate of correct sampling time. Using the PPK model combined with Bayesian estimation, clinical pharmacists can greatly increase the trough concentration and AUCs within the target range, especially for adjusted regimens. Higher PK/PD target rates resulted in better Gram-positive bacterial eradication and reduced renal toxicity of vancomycin.

Vancomycin in neonatal sepsis: predictive performance of a Chinese neonatal population pharmacokinetic model and clinical efficacy evaluation

BACKGROUND

In the neonatal population, individual calculation and adjustment of vancomycin (VCM) doses has been recommended based on population pharmacokinetics (PPK) methods.

OBJECTIVE

Our previous study established a Chinese neonatal VCM PPK model. The main goal of this study was to evaluate the predictive performance of this PPK model for VCM trough concentration.

METHODS

The data on neonatal severe infection patients treated with VCM were retrospectively collected. The predictive performance of this PPK model was expressed using mean prediction error (MPE), mean absolute prediction error (MAPE), sensitivity and specificity. Linear regression analysis was used to compare predicted and measured VCM concentrations. We drew the receiver operating characteristic (ROC) curve to evaluate the predictive efficacy of the ratio of area under the concentration-time curve over 24 hours to minimum inhibitory concentration (AUC0-24/MIC) and trough concentration for clinical efficacy.

RESULTS

A total of 40 neonates with Gram-positive bacterial sepsis were included. After VCM treatment, 32 (80%) neonates were clinically cured. Eight cases were a clinical failure: the trough concentrations and AUC0-24 were lower than that of the clinical cure patients (8.70±4.30 vs 14.30±4.50 mg/L, p=0.003; 404.30±122.80 vs 515.40±131.70, p=0.037). The measured and predicted trough concentration were 11.16 (5.96, 16.53) mg/L and 10.13 (6.61, 15.73) mg/L, respectively. The MPE and MAPE were 4.62% and 13.26% (5.30%, 25.88%), respectively. The proportion of MAPE <30% in the adjusted regimen was higher than the initial regimen (89.66% vs 65.00%, p=0.039). Predictions of sensitivity and specificity by this PPK model were 88.24% and 94.29%, respectively. The coefficients of determination of linear regression analysis were 0.9171 and 0.9009 for the initial and adjusted regimen, respectively. The AUC0-24 was correlated with the trough concentration (r=0.587, p<0.001). The ROC curve indicated that the optimal cut-off points for predicting clinical efficacy were AUC0-24/MIC >425.47 and trough concentration >9.45 mg/L.

CONCLUSION

This PPK model has good predictive performance in Chinese neonatal patients. Both AUC0-24/MIC and trough concentration can predict the clinical efficacy of antibacterial treatment.

Establishment and application of population pharmacokinetics model of vancomycin in infants with meningitis

BACKGROUND

To establish a population pharmacokinetics (PPK) model of vancomycin (VCM) for dose individualization in Chinese infants with meningitis.

METHODS

We collected the data of 82 children with meningitis in hospital from July 2014 to June 2016. The initial vancomycin dosage regimen for children was 10 or 15 mg/kg for q12 h, q8 h or q6 h. Serum concentrations were determined by Viva-E Analyzer before and after the fifth administration. The PPK model was developed by nonlinear mixed-effect model software, assessed by the bootstrap method and then tested in 20 infant patients.

RESULTS

The VCM clearance (CL) was increased by body weight (WT) and decreased by blood urea nitrogen (BUN). Pharmacokinetic parameters of VCM were not influenced by co-administered drugs. The trough concentrations of VCM were accurately predicted by the PPK model, with the prediction errors less than 32%.

CONCLUSION

A new individual strategy for VCM regimens was proposed and validated by the PPK model.

Can Published Population Pharmacokinetic Models of Busulfan Be Used for Individualized Dosing in Chinese Pediatric Patients Undergoing Hematopoietic Stem Cell Transplantation? An External Evaluation

Busulfan is a bifunctional alkylating agent that is widely used before hematopoietic stem cell transplantation (HSCT), in combination with other chemotherapeutic drugs. As of 2020, there is no population pharmacokinetic (popPK) model for busulfan in Chinese pediatric patients. A systemic external evaluation of 11 published popPK models was conducted in Chinese pediatric patients undergoing HSCT. Forty pediatric patients were enrolled in this study, with a total of 183 blood concentrations. The relative prediction error (PE%), median PE%, median absolute PE%, and percentage of PE% within ±20% and ±30% were calculated in prediction-based diagnostics. Simulation-based diagnostics were conducted through a prediction- and variability-corrected visual predictive check and the normalized prediction distribution error. The relative individual prediction error was calculated using Bayesian forecasting with 1 to 3 concentration points. The 1-compartment open linear popPK model, which was built by Su-jin Rhee et al (model H), incorporating the patient's body surface area, age, dosing day, and aspartate aminotransferase as significant covariates had preferable predictability than other popPK models. In prediction-based diagnostics, the median PE%, percentage of PE% within ±20%, and percentage of PE% within ±30% of model H were 8.48%, 45.35%, and 59.56%, respectively. The normalized prediction distribution error of model H showed that it followed the normal distribution. Based on Bayesian forecasting, model H showed good predictive performance. Thus, model H was the most appropriate model that can be used clinically for individualized dosage adjustments in Chinese pediatric HSCT patients.

Clinical utiliy of a model-based piperacillin dose in neonates with early-onset sepsis

AIMS

Early-onset sepsis (EOS) is a common disease in neonates with a high morbidity and mortality rate. Piperacillin/tazobactam has been used extensively and empirically for EOS treatment without clinically validated dosing regimens, although the population pharmacokinetics (PPK) of piperacillin in neonates has been reported. Therefore, we wanted to study the effectiveness and tolerance of a PPK model-based dosing regimen of piperacillin/tazobactam in EOS patients.

METHODS

A prospective, single-centre, phase II clinical study of piperacillin/tazobactam in neonates with EOS was conducted. The dosing regimen (90 mg·kg^-1 , q8h) was determined based on a previous piperacillin PPK model in young infants using NONMEM v7.4. The pharmacodynamics (PD) target (70%fT > MIC, free drug concentration above MIC during 70% of the dosing interval) attainment was calculated using NONMEM combined with an opportunistic sampling design. The clinical treatment data were collected.

RESULTS

A total of 52 neonates were screened and 49 neonates completed their piperacillin/tazobactam treatment course and were included in this analysis. The median (range) values of postmenstrual age were 33.57 (range 26.14-41.29) weeks. Forty-seven (96%) neonates reached their PD target. Eight (16%) neonates experienced treatment failure clinically. The mean (SD, range) duration of treatment and length of hospitalization were 100.1 (62.2, 36.2-305.8) hours and 31 (30, 5-123) days. There were no obvious adverse events and no infection-related deaths occurred in the first month of life.

CONCLUSIONS

A model-based dosing regimen of piperacillin/tazobactam was evaluated clinically, was tolerated well and was determined to be effective for EOS treatment.

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.

Development of a population pharmacokinetic model and Bayesian estimators for isoniazid in Tunisian tuberculosis patients

This study aimed to develop a population pharmacokinetic model using full pharmacokinetic (PK) profiles of isoniazid (INH) taking into account demographic and genetic covariates and to develop Bayesian estimators for predicting INH area under the curve (AUC) in Tunisian tuberculosis patients. The INH concentrations in the building data set were fitted using a one- to three-compartment model. The impact of the different covariates was assessed on the PK parameters of the best model. The best limited sampling strategy (LSS) for estimating the INH AUC was selected by comparing the predicted values to an independent data set. INH PK was best described using a three-compartment model with lag-time absorption. The different studied covariates did not have any impact on the PK parameters of the building model. The Bayesian estimation using one-point concentrations gave the lowest values of prediction errors for the C₃ LSS model. This model could be sufficient in routine activity for INH monitoring in this population.

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.

Population pharmacokinetics-pharmacodynamics of ceftazidime in neonates and young infants: Dosing optimization for neonatal sepsis

Ceftazidime is a third-generation cephalosporin with high activity against many pathogens. But the ambiguity and diversity of the dosing regimens in neonates and young infants impair access to effective treatment. Thus, we conducted a population pharmacokinetic study of ceftazidime in this vulnerable population and recommended a model-based dosage regimen to optimize sepsis therapy. Totally 146 neonates and young infants (gestational age (GA): 36-43.4 weeks, postnatal age (PNA): 1-81 days, current weight (CW): 900-4500 g) were enrolled based on inclusion and exclusion criteria. Ceftazidime bloods samples (203) were obtained using the opportunistic sampling strategy and determined by the high-performance liquid chromatography. The population pharmacokinetic-pharmacodynamic analysis was conducted by nonlinear mixed effects model (NONMEM). A one-compartment model with first-order elimination best described the pharmacokinetic data. Covariate analysis showed the significance of GA, PNA, and CW on developmental pharmacokinetics. Monte Carlo simulation was performed based on above covariates and minimum inhibitory concentration (MIC). In the newborns with PNA ≤ 3 days (MIC=8 mg/L), the dose regimen was 25 mg/kg twice daily (BID). For the newborns with PNA > 3 days (MIC=16 mg/L), the optimal dose was 30 mg/kg three times daily (TID) for those with GA ≤ 37 weeks and 40 mg/kg TID for those with GA > 37 weeks. Overall, on the basis of the developmental population pharmacokinetic-pharmacodynamic analysis covering the whole range of neonates and young infants, the evidence-based ceftazidime dosage regimens were proposed to optimize neonatal early-onset and late-onset sepsis therapy.

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.

Determination of vancomycin exposure target and individualised dosing recommendations for neonates: model-informed precision dosing

INTRODUCTION

Few studies incorporating population pharmacokinetic/pharmacodynamic (Pop-PK/PD) modelling have been conducted to quantify the exposure target of vancomycin in neonates. A retrospective observational cohort study was undertaken in neonates to determine this target and dosing recommendations (chictr.org.cn, ChiCTR1900027919).

METHODS

A Pop-PK model was developed to estimate PK parameters. Causalities between acute kidney injury (AKI) occurrence and vancomycin use were verified using Naranjo criteria. Thresholds of vancomycin exposure in predicting AKI or efficacy were identified via classification and regression tree analysis. Associations between exposure thresholds and clinical outcomes, including AKI and efficacy, were analysed by logistic regression. Dosing recommendations were designed using Monte Carlo simulations based on the optimised exposure target.

RESULTS

Pop-PK modelling included 182 neonates with 411 observations. On covariate analysis, neonatal physiological maturation, renal function and concomitant use of vasoactive agents (VAS) significantly affected vancomycin PK. Seven cases of vancomycin-induced AKI were detected. Area under the concentration-time curve from 0-24 hours (AUC_0-24) ≥ 485 mg•h/L was an independent risk factor for AKI after adjusting for VAS co-administration. The clinical efficacy of vancomycin was analysed in 42 patients with blood culture-proven staphylococcal sepsis. AUC_0-24 to minimum inhibitory concentration (AUC_0-24/MIC) ≥ 234 was the only significant predictor of clinical effectiveness. Monte Carlo simulations indicated that regimens in Neonatal Formulary 7 and Red Book (2018) were unsuitable for all neonates.

CONCLUSION

An AUC_0-24 of 240-480 (assuming MIC = 1 mg/L) is a recommended exposure target of vancomycin in neonates. Model-informed dosing regimens are valuable in clinical practice.

Reappraisal of the Optimal Dose of Meropenem in Critically Ill Infants and Children: a Developmental Pharmacokinetic-Pharmacodynamic Analysis

Data of developmental pharmacokinetics (PK) of meropenem in critically ill infants and children with severe infections are limited. We assessed the population PK and defined the appropriate regimen to optimize treatment in this population based on developmental PK-pharmacodynamic (PD) analysis. Blood samples were collected from pediatric intensive care unit patients with severe infection treated with standard dosage regimens for meropenem. Population PK data were analyzed using NONMEM software. Fifty-seven patients (mean age, 2.96 years [range, 0.101 to 14.4]; mean body weight, 15.8 kg [range, 5.0 to 65.0]) were included. A total of 135 meropenem concentrations were obtainable for population PK modeling. The median number of samples per patients was 2 (range, 1 to 4). A two-compartment model with first-order elimination was optimal for PK modeling. Weight and creatinine clearance (estimated by the Schwartz formula) were significantly correlated with the PK parameters of meropenem. The probabilities of target attainment for pathogens with low MICs of 1 and 2 μg/ml were 87.5% and 68.6% following administration of 40 mg/kg/dose (every 8 h [q8h]) as a 4-h infusion and 98.0% and 73.3% with high MICs of 4 and 8 μg/ml following administration of 110 mg/kg/day as a continuous infusion in critically ill infants and children under 70% fT _>MIC (the free time during which the plasma concentration of meropenem exceeds the MIC), respectively. The standard dosage regimens for meropenem did not meet an appropriate PD target, and an optimal dosing regimen was established in critically ill infants and children. (This study has been registered at ClinicalTrials.gov under identifier NCT03643497.).

Therapeutic drug monitoring of β-lactam antibiotics in the ICU

INTRODUCTION

Individualizing antibiotic therapy is paramount to improve clinical outcomes while minimizing the risk of toxicity and antimicrobial therapy. β-lactam antibiotics are amongst the drugs most commonly prescribed in the Intensive Care Unit (ICU). The pharmacokinetics of β-lactam antibiotics are profoundly altered in critically ill patients, leading to the failure of standard drug dosing regimens to result in adequate drug concentrations. Therapeutic Drug Monitoring (TDM) of β-lactam antibiotics is a promising tool to help optimize β-lactam antibiotic therapy.

AREAS COVERED

The rationale behind TDM for β-lactam antibiotics is explained, as well as some more practical aspects such as when to sample, what concentrations to strive for and how to use it in clinical practice. We also discuss microbiological and analytical considerations, knowledge gaps, and future perspectives of β-lactam antibiotics TDM in ICU patients.

EXPERT OPINION

TDM of β-lactam antibiotics has been studied intensively in recent years. While TDM may not yet be widely available, and targets need to be further refined, TDM of β-lactam antibiotics will help to optimize antibiotic therapy in the critically ill patient, as an integrated part of an antimicrobial stewardship program.

Limited Sampling Strategies Using Linear Regression and the Bayesian Approach for Therapeutic Drug Monitoring of Moxifloxacin in Tuberculosis Patients

Therapeutic drug monitoring (TDM) of moxifloxacin is recommended to improve the response to tuberculosis treatment and reduce acquired drug resistance. Limited sampling strategies (LSSs) are able to reduce the burden of TDM by using a small number of appropriately timed samples to estimate the parameter of interest, the area under the concentration-time curve. This study aimed to develop LSSs for moxifloxacin alone (MFX) and together with rifampin (MFX+RIF) in tuberculosis (TB) patients. Population pharmacokinetic (popPK) models were developed for MFX (n = 77) and MFX+RIF (n = 24). In addition, LSSs using Bayesian approach and multiple linear regression were developed. Jackknife analysis was used for internal validation of the popPK models and multiple linear regression LSSs. Clinically feasible LSSs (one to three samples, 6-h timespan postdose, and 1-h interval) were tested. Moxifloxacin exposure was slightly underestimated in the one-compartment models of MFX (mean -5.1%, standard error [SE] 0.8%) and MFX+RIF (mean -10%, SE 2.5%). The Bayesian LSSs for MFX and MFX+RIF (both 0 and 6 h) slightly underestimated drug exposure (MFX mean -4.8%, SE 1.3%; MFX+RIF mean -5.5%, SE 3.1%). The multiple linear regression LSS for MFX (0 and 4 h) and MFX+RIF (1 and 6 h), showed mean overestimations of 0.2% (SE 1.3%) and 0.9% (SE 2.1%), respectively. LSSs were successfully developed using the Bayesian approach (MFX and MFX+RIF; 0 and 6 h) and multiple linear regression (MFX, 0 and 4 h; MFX+RIF, 1 and 6 h). These LSSs can be implemented in clinical practice to facilitate TDM of moxifloxacin in TB patients.

Limited sampling strategy to predict mycophenolic acid area under the curve in pediatric patients with nephrotic syndrome: a retrospective cohort study

PURPOSE

Limited sampling strategy (LSS) is a precise and relatively convenient therapeutic drug monitoring method. We evaluated LSSs for mycophenolic acid (MPA) in children with nephrotic syndrome treated with mycophenolic mofetil (MMF) and validated the LSSs using two different approaches.

METHODS

We measured MPA plasma concentrations in 31 children using HPLC-UV method and received 37 MPA pharmacokinetic profiles (0-12 h). For six children, MPA profiles were estimated twice after two MMF doses. LSSs were developed using multilinear regression with STATISTICA and R software and validated using validation group and bootstrap method, respectively.

RESULTS

The best three time point equations included C₁, C₃, C₆ (good guess 83%, bias - 2.78%; 95% confidence interval (CI) - 9.85-0.46); C₁, C₂, C₆ (good guess 72%, bias 0.72%; 95% CI - 5.33-7.69); and C₁, C₂, C₄ (good guess 72%, bias 2.05%; 95% CI - 4.92-13.01) for STATISTICA software. For R software, the best equations consisted of C₁, C₃, C₆ (good guess 92%, bias - 2.69%; 95% CI - 27.18-33.75); C₀, C₁, C₃ (good guess 84%, bias - 2.11%; 95% CI - 24.19-22.29); and C₀, C₁, C₂ (good guess 84%, bias - 0.48%; 95% CI - 30.77-54.07). During validation, better results were obtained for R evaluations, i.e., bootstrap method.

CONCLUSIONS

The most useful equations included C₀, C₁, C₃ and C₀, C₁, C₂ time points; however, the most precise included C₁, C₃, C₆ time points because of MPA enterohepatic recirculation. Better results were obtained for bootstrap validation due to greater number of patients. Validated LSS should be used only in the population for which it was developed. As there is growing evidence that underexposure of MPA is associated with insufficient treatment response, we recommend the introduction of therapeutic drug monitoring for MPA in children with nephrotic syndrome.

Population Pharmacokinetics and Dosing Optimization of Amoxicillin in Neonates and Young Infants

Amoxicillin is widely used to treat bacterial infections in neonates. However, considerable intercenter variability in dosage regimens of antibiotics exists in clinical practice. The pharmacokinetics of amoxicillin has been described in only a few preterm neonates. Thus, we aimed to evaluate the population pharmacokinetics of amoxicillin through a large sample size covering the entire age range of neonates and young infants and to establish evidence-based dosage regimens based on developmental pharmacokinetics-pharmacodynamics. This is a prospective, multicenter, pharmacokinetic study using an opportunistic sampling design. Amoxicillin plasma concentrations were determined using high-performance liquid chromatography. Population pharmacokinetic analysis was performed using NONMEM. A total of 224 pharmacokinetic samples from 187 newborns (postmenstrual age range, 28.4 to 46.3 weeks) were available for analysis. A two-compartment model with first-order elimination was used to describe population pharmacokinetics. Covariate analysis showed that current weight, postnatal age, and gestational age were significant covariates. The final model was further validated for predictive performance in an independent cohort of patients. Monte Carlo simulation demonstrated that for early-onset sepsis, the currently used dosage regimen (25 mg/kg twice daily [BID]) resulted in 99.0% of premature neonates and 87.3% of term neonates achieving the pharmacodynamic target (percent time above MIC), using a MIC breakpoint of 1 mg/liter. For late-onset sepsis, 86.1% of premature neonates treated with 25 mg/kg three times a day (TID) and 79.0% of term neonates receiving 25 mg/kg four times a day (QID) reached the pharmacodynamic target, using a MIC breakpoint of 2 mg/liter. The population pharmacokinetics of amoxicillin was assessed in neonates and young infants. A dosage regimen was established based on developmental pharmacokinetics-pharmacodynamics.

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.

Prediction of tacrolimus dosage in the early period after heart transplantation: a population pharmacokinetic approach

Aim: The aim of this study was to evaluate tacrolimus population pharmacokinetics and investigate factors that explain tacrolimus variability in adult heart transplant patients. Methods: A total of 707 tacrolimus concentrations from 107 adult heart transplant patients were included in model development. The effects of demographic, clinical factors and CYP3A5 genotype on tacrolimus clearance were evaluated using a nonlinear mixed-effects modeling. 24 patients with 106 tacrolimus concentrations were used for external validation. Results: The pharmacokinetic data were adequately described by a one-compartment model with first-order absorption and elimination. The estimated apparent clearance and volume of distribution of tacrolimus were 13.7 l/h and 791 l, respectively. Tacrolimus apparent clearance was significantly reduced in CYP3A5 nonexpressers (CYP3A5*3/*3), concomitant with azole antifungal drugs and Wuzhi capsule (WZ). A predictive performance was further confirmed in an external validation by Bayesian estimation. Recommended dose regimens were obtained by simulations based on the established model. Conclusion: This is the first population pharmacokinetic study conducted in Chinese heart transplant recipients. These findings are of great importance with regards to tacrolimus dose optimization in heart transplantation patients.

Pilot Study of Model-Based Dosage Individualization of Ganciclovir in Neonates and Young Infants with Congenital Cytomegalovirus Infection

Newborns with congenital cytomegalovirus (CMV) infection are at high risk for developing permanent sequelae. Intravenous ganciclovir therapy is frequently used for the treatment of congenital CMV infection. A target area under the concentration-time curve from 0 to 24 h (AUC_0-24) of 40 to 50 μg · h/ml is recommended. The standard dose has resulted in a large variability in ganciclovir exposure in newborns, indicating the unmet need of dosage individualization for this vulnerable population, but the implementation of this strategy remains challenging in clinical practice. We aim to evaluate the clinical utility of model-based dosage individualization of ganciclovir in newborns using an opportunistic sampling approach. The predictive performance of a published ganciclovir population pharmacokinetic model was evaluated using an independent patient cohort. The individual dose was adjusted based on the target AUC_0-24 to ensure its efficacy. A total of 26 newborns with congenital CMV infection were included in the present study. Only 11 (42.3%) patients achieved the target AUC_0-24 after being given the standard dose. For all the subtherapeutic patients (achieving <80% of the target AUC) (n = 5), a model-based dosage adjustment was performed using the Bayesian estimation method combined with the opportunistic sampling strategy. The adjusted doses were increased by 28.6% to 60.0% in these five patients, and all adapted AUC_0-24 values achieved the target (range, 48.6 to 66.1 μg · h/ml). The clinical utility of model-based dosing individualization of ganciclovir was demonstrated in newborns with congenital CMV infection. The population pharmacokinetic model combined with the opportunistic sampling strategy provides a clinically feasible method to adapt the ganciclovir dose in neonatal clinical practice. (This study has been registered at ClinicalTrials.gov under registration no. NCT03113344.).

Population pharmacokinetics of vancomycin and AUC-guided dosing in Chinese neonates and young infants

OBJECTIVES

To develop a population pharmacokinetic (PK) model for vancomycin in Chinese neonates and infants less than 2 months of age (young infants) with a wide gestational age range, in order to determine the appropriate dosing regimen for this population.

METHODS

We performed a retrospective chart review of patients from the neonatal intensive care unit (NICU) at Children's Hospital of Fudan University to identify neonates and young infants treated with vancomycin from May 2014 to May 2017. Vancomycin concentrations and covariates were utilized to develop a one-compartment model with first-order elimination. The predictive performance of the final model was assessed by both internal and external evaluation, and the relationship between trough concentration and AUC_0-24 was investigated. Monte Carlo simulations were performed to design an initial dosing schedule targeting an AUC_0-24 ≥ 400.

RESULTS

The analysis included a total of 330 concentration-time data points from 213 neonates and young infants with gestational age (GA) and body weight of 25-42 weeks and 0.88-5.1 kg, respectively. Body weight, postmenstrual age (PMA) and serum creatinine level were found to be important factors explaining the between-subject variability in vancomycin PK parameters for this population. Both internal and external evaluation supported the prediction of the final vancomycin PK model. The typical population parameter estimates of clearance and distribution volume for an infant weighing 2.73 kg with a PMA of 39.8 weeks and serum creatinine of 0.28 mg/dL were 0.103 L/h/kg and 0.58 L/kg, respectively. Although vancomycin serum trough concentrations were predictive of the AUC, considerable variability was observed in the achievement of an AUC_0-24/MIC of ≥400. For MIC values of ≤0.5 mg/L, AUC_0-24/MIC ≥400 was achieved for 95% of the newborn infants with vancomycin troughs of 5-10 mg/L. When the MIC increased to 1 mg/L, only 15% of the patients with troughs of 5-10 mg/L achieved AUC_0-24/MIC ≥400. For MIC values of 2 mg/L, no infants achieved the target. Simulations predicted that a dose of at least 14 and 15 mg/kg every 12 h was required to attain the target AUC_0-24 ≥ 400 in 90% of infants with a PMA of 30-32 and 32-34 weeks, respectively. This target was also achieved in 93% of simulated infants in the oldest PMA groups (36-38 and 38-40 weeks, respectively) when the dosing interval was extended to 8 h. For infants with a PMA ≥44 weeks, a dose increase to 18 mg/kg every 8 h was needed. The trough concentrations of 5-15 mg/L were highly predictive of an AUC_0-24 of ≥400 when treating invasive MRSA infections with an MIC of ≤1 mg/L.

CONCLUSIONS

The PK parameters for vancomycin in Chinese infants younger than 2 months of age were estimated using the model developed herein. This model has been used to predict individualized dosing regimens in this vulnerable population in our hospital. A large external evaluation of our model will be conducted in future studies.

Penetration of Cefotaxime into Cerebrospinal Fluid in Neonates and Young Infants

Cefotaxime is the first-line treatment for meningitis in neonates and young infants. However, limited data on cefotaxime cerebrospinal fluid (CSF) concentrations in neonates and young infants were available. The aim of the present study was to evaluate the penetration of cefotaxime into CSF in neonates and young infants. Blood and CSF samples were collected from neonates and young infants treated with cefotaxime using an opportunistic pharmacokinetic sampling strategy, and concentrations were quantified by high-performance liquid chromatography-tandem mass spectrometry. The analysis was performed using NONMEM and R software. Thirty neonates and young infants (postmenstrual age range, 25.4 to 47.4 weeks) were included. A total of 67 plasma samples and 30 CSF samples were available for analysis. Cefotaxime plasma and CSF concentrations ranged from 2.30 to 175.42 mg/liter and from 0.39 to 25.38 mg/liter, respectively. The median ratio of the CSF concentration to the plasma concentration was 0.28 (range, 0.06 to 0.76). Monte Carlo simulation demonstrated that 88.4% and 63.9% of hypothetical neonates treated with 50 mg/kg of body weight three times a day (TID) would reach the pharmacodynamic target (the percentage of the dosing interval that the free antimicrobial drug concentration remains above the MIC, 70%) using the standard EUCAST MIC susceptibility breakpoints of 2 mg/liter and 4 mg/liter, respectively. The penetration of cefotaxime into the CSF of neonates and young infants was evaluated using an opportunistic sampling approach. A dosage regimen of 50 mg/kg TID could cover the most causative pathogens with MICs of <2 mg/liter. Individual dosage adaptation was required for more resistant bacterial strains, such as Staphylococcus aureus.

Clinical Pharmacokinetics and Pharmacodynamics of Monoclonal Antibodies Approved to Treat Rheumatoid Arthritis

Monoclonal antibodies (mAbs) are increasingly used to treat rheumatoid arthritis (RA). At present, anti-tumor necrosis factor-α drugs (infliximab, adalimumab, certolizumab pegol, and golimumab), rituximab, and tocilizumab are approved for RA treatment. This review focuses on the pharmacokinetics and pharmacodynamics of mAbs approved in RA. Being large proteins, mAbs exhibit complex pharmacokinetic and pharmacodynamic properties. In particular, owing to the interactions of mAbs with their antigenic targets, the pharmacokinetics of mAbs depends on target turnover and exhibits non-specific (linear) and target-mediated (often nonlinear) clearances. Their volume of distribution is low (3-4 L) and their elimination half-life usually ranges from 2 to 3 weeks. The inter-individual pharmacokinetic variability of mAbs is usually large and is partly explained by differences in antigenic burden or by anti-drug antibodies, which accelerate mAb elimination. The inter-individual variability of clinical response is large and influenced by the pharmacokinetics. The analysis of mAbs concentration-effect relationship relies more and more often on pharmacokinetic-pharmacodynamic modeling; these models being suitable for dosing optimization. Even if adverse effects of mAbs used in RA are well known, the relationship between mAb concentration and adverse effects is poorly documented, especially for anti-tumor necrosis factor-α mAbs. Overall, RA patients treated with mAbs should benefit from individualized dosing strategies. Because of the complexity of their pharmacokinetics and mechanisms of action, the current dosing strategy of mAbs is not based on sound knowledge. New studies are needed to assess individual dosing regimen, adjusted notably to disease activity.

Population pharmacokinetics of vancomycin in adult Chinese patients with post-craniotomy meningitis and its application in individualised dosage regimens

PURPOSE

Vancomycin (VCM) is a first-line antibacterial drug used to treat post-craniotomy meningitis (PCM). VCM pharmacokinetic parameters are altered in PCM patients, compared to those in other patients. Although VCM population pharmacokinetics (PPK) has been reported, changes in VCM PPK in adult Chinese PCM patients remain unknown. We developed a VCM PPK model in adult Chinese PCM patients and proposed a new strategy for individualising VCM administration using this model.

METHODS

Data was obtained from a prospective study of 100 adult PCM patients in the Neurosurgery Department of the First Affiliated Hospital of Fujian Medical University. The trough concentrations at steady state were determined by enzyme multiplied immunoassay. Nonlinear mixed-effect model software was employed to develop the PPK model. The final model was evaluated using the bootstrap method and normalised prediction error distribution and through the testing of 20 independent adult PCM patients.

RESULTS

VCM clearance in PCM patients was higher than that observed in other patients. Creatinine clearance affected VCM clearance, whereas no co-administered drugs influenced VCM pharmacokinetics. Trough concentrations were accurately predicted by the final model, while the prediction errors were less than ±32 %. Moreover, a new strategy for individualising VCM regimens using the PPK model was proposed and validated.

CONCLUSIONS

A PPK model was developed to estimate the individual clearance in inpatients receiving intravenously infused VCM and could be used to develop individualised dosing of adult Chinese PCM patients.

Population pharmacokinetics and Bayesian estimation of tacrolimus exposure in paediatric liver transplant recipients

AIMS

The objectives of this study were to develop a population pharmacokinetic (PopPK) model for tacrolimus in paediatric liver transplant patients and determine optimal sampling strategies to estimate tacrolimus exposure accurately.

METHODS

Twelve hour intensive pharmacokinetic profiles from 30 patients (age 0.4-18.4 years) receiving tacrolimus orally were analysed. The PopPK model explored the following covariates: weight, age, sex, type of transplant, age of liver donor, liver function tests, albumin, haematocrit, drug interactions, drug formulation and time post-transplantation. Optimal sampling strategies were developed and validated with jackknife.

RESULTS

A two-compartment model with first-order absorption and elimination and lag time described the data. Weight was included on all pharmacokinetic parameters. Typical apparent clearance and central volume of distribution were 12.1 l h(-1) and 31.3 l, respectively. The PopPK approach led to the development of optimal sampling strategies, which allowed estimation of tacrolimus pharmacokinetics and area under the concentration–time curve (AUC) on the basis of practical sampling schedules (three or four sampling times within 4 h) with clinically acceptable prediction error limit. The mean bias and precision of the Bayesian vs. reference (trapezoidal) AUCs ranged from -2.8 to -1.9% and from 7.4 to 12.5%, respectively.

CONCLUSIONS

The PopPK of tacrolimus and empirical Bayesian estimates represent an accurate and convenient method to predict tacrolimus AUC(0-12) in paediatric liver transplant recipients, despite high between-subject variability in pharmacokinetics and patient demographics. The developed optimal sampling strategies will allow the undertaking of prospective trials to define the tacrolimus AUC-based therapeutic window and dosing guidelines in this population.

Optimal design in pediatric pharmacokinetic and pharmacodynamic clinical studies

It is not trivial to conduct clinical trials with pediatric participants. Ethical, logistical, and financial considerations add to the complexity of pediatric studies. Optimal design theory allows investigators the opportunity to apply mathematical optimization algorithms to define how to structure their data collection to answer focused research questions. These techniques can be used to determine an optimal sample size, optimal sample times, and the number of samples required for pharmacokinetic and pharmacodynamic studies. The aim of this review is to demonstrate how to determine optimal sample size, optimal sample times, and the number of samples required from each patient by presenting specific examples using optimal design tools. Additionally, this review aims to discuss the relative usefulness of sparse vs rich data. This review is intended to educate the clinician, as well as the basic research scientist, whom plan on conducting a pharmacokinetic/pharmacodynamic clinical trial in pediatric patients.