Population pharmacokinetic modeling of dolutegravir/lamivudine to support a once-daily fixed-dose combination regimen in virologically suppressed adults living with HIV-1.

A fixed-dose combination (FDC) of 50 mg dolutegravir and 300 mg lamivudine is indicated for the treatment of HIV-1 infection. This analysis aimed to characterize the population pharmacokinetics (PK) of dolutegravir and lamivudine based on data from a phase 3 study (TANGO) in virologically suppressed adults living with HIV-1 switching to dolutegravir/lamivudine FDC. These analyses included 362 participants who contributed 2,629 dolutegravir and 2,611 lamivudine samples collected over 48 weeks. A one-compartment model with first-order absorption and elimination parameterized by apparent oral clearance (CL/F), apparent volume of distribution (V/F), and absorption rate constant (Ka) described dolutegravir PK. Covariate search yielded body weight, bilirubin, and ethnicity as predictors of CL/F, and weight was predictive for V/F. The estimates of CL/F, V/F, and Ka were 0.858 L/h, 16.7 L, and 2.15 h-1, respectively. A two-compartment model with first-order absorption and elimination parameterized by CL/F, apparent intercompartmental clearance (Q/F), apparent central volume of distribution (V2/F), apparent peripheral volume of distribution (V3/F), and Ka described lamivudine PK. Covariate search yielded eGFR and race as predictors of CL/F, and weight was predictive for V2/F. The estimated parameter values were CL/F = 19.6 L/h, Q/F = 2.97 L/h, V2/F = V3/F = 105 L, and Ka = 2.30 h-1. The steady-state prediction suggested that the effect of covariates dolutegravir and lamivudine exposures was small (<20%) and not clinically relevant. Therefore, no dose adjustments are recommended based on these analyses. The results support the use of dolutegravir/lamivudine FDC in the treatment of HIV-1 infection in adults.CLINICAL TRIALSThis study is registered with ClinicalTrials.gov as NCT03446573.

High-dose methotrexate pharmacokinetics and its impact on prognosis of paediatric acute lymphoblastic leukaemia patients: A population pharmacokinetic study.

This study delivers a comprehensive evaluation of the efficacy and pharmacokinetics of high-dose methotrexate (HDMTX) in a large cohort of Chinese paediatric acute lymphoblastic leukaemia patients. A total of 533 patients were included in the prognostic analysis. An association was observed between lower steady-state MTX concentrations (<56 µmol/L) and poorer outcomes in intermediate-/high-risk (IR/HR) patients. Subgroup analysis further revealed that this relationship between concentrations and prognosis was even more pronounced in patients with MLL rearrangements. In contrast, such an association did not emerge within the low-risk patient group. Additionally, utilizing population pharmacokinetic modelling (6051 concentrations from 815 patients), we identified the significant impact of physiological maturation, estimated glomerular filtration rate, sex and concurrent dasatinib administration on MTX pharmacokinetics. Simulation-based recommendations include a reduced dosage regimen for those with renal insufficiency and a specific 200 mg/kg dosage for infants under 1 year. The findings underscore the critical role of HDMTX in treating IR/HR populations and call for a reassessment of its application in lower-risk groups. An individualized pharmacokinetic dosage regimen could achieve the most optimal results, ensuring the largest proportion of steady-state concentrations within the optimal range.

The cycle effect quantified: reduced tumour uptake in subsequent cycles of [177Lu]Lu-HA-DOTATATE during peptide receptor radionuclide therapy.

BACKGROUND: Clear evidence regarding the effect of reduced tumour accumulation in later peptide receptor radionuclide therapy (PRRT) cycles is lacking. Therefore, we aimed to quantify potential cycle effects for patients treated with [177Lu]Lu-HA-DOTATATE using a population pharmacokinetic (PK) modelling approach. METHODS: A population PK model was developed using imaging data from 48 patients who received multiple cycles of [177Lu]Lu-HA-DOTATATE. The five-compartment model included a central, kidney, spleen, tumour and lumped rest compartment. Tumour volume and continued use of long-acting somatostatin analogues (SSAs) were tested as covariates in the model. In addition, the presence of a cycle effect was evaluated by relating the uptake rate in a specific cycle as a fraction of the (tumour or organ) uptake rate in the first cycle. RESULTS: The final PK model adequately captured observed radioactivity accumulation in kidney, spleen and tumour. A higher tumour volume was identified to increase the tumour uptake rate, where a twofold increase in tumour volume resulted in a 2.3-fold higher uptake rate. Also, continued use of long-acting SSAs significantly reduced the spleen uptake rate (68.4% uptake compared to SSA withdrawal (10.5% RSE)). Lastly, a cycle effect was significantly identified, where tumour uptake rate decreased to 86.9% (5.3% RSE) in the second cycle and even further to 79.7% (5.6% RSE) and 77.6% (6.2% RSE) in the third and fourth cycle, respectively, compared to cycle one. CONCLUSIONS: Using a population PK modelling approach, the cycle effect of reduced tumour uptake in subsequent PRRT cycles was quantified. Our findings implied that downregulation of target receptors is probably not the major cause of the cycle effect, due to a plateau in the decrease of tumour uptake in the fourth cycle.

A population pharmacokinetic model for sertraline in women during the perinatal period-A contribution from the ConcePTION project.

AIMS: Sertraline is frequently prescribed for mental health conditions in both pregnant and breastfeeding women. According to the limited available data, only small amounts of sertraline are transferred into human milk, yet with a large amount of unexplained interindividual variability. This study aimed to develop a population pharmacokinetic (popPK) model to describe the pharmacokinetics of sertraline during the perinatal period and explain interindividual variability. METHODS: Pregnant women treated with sertraline were enrolled in the multicenter prospective cohort SSRI-Breast Milk study. A popPK model for sertraline maternal plasma and breast milk concentrations was developed and allowed estimating the milk-to-plasma ratio (MPR). An additional fetal compartment allowed cord blood concentrations to be described. Several covariates were tested for significance. Ultimately, model-based simulations allowed infant drug exposure through placenta and breast milk under various conditions to be predicted. RESULTS: Thirty-eight women treated with sertraline were included in the study and provided 89 maternal plasma, 29 cord blood and 107 breast milk samples. Sertraline clearance was reduced by 42% in CYP2C19 poor metabolizers compared to other phenotypes. Doubling milk fat content increased the MPR by 95%. Simulations suggested a median daily infant dosage of 6.9 µg kg-1 after a 50 mg maternal daily dose, representing 0.95% of the weight-adjusted maternal dose. Median cord blood concentrations could range from 3.29 to 33.23 ng mL-1 after maternal daily doses between 25 and 150 mg. CONCLUSIONS: Infant exposure to sertraline, influenced by CYP2C19 phenotype and breast milk fat content, remains low, providing reassurance regarding the use of sertraline during pregnancy and breastfeeding.

Development of a population pharmacokinetic model for the novel long-acting injectable antipsychotic risperidone ISM®.

AIMS: The aims of this study were to develop a population pharmacokinetic (PK) model for risperidone ISM® and to investigate the relationships between active moiety exposure, as described by apparent clearance (CL40), and several covariates using all data from five clinical studies. METHODS: A population PK model was developed using active moiety concentrations from a study in healthy volunteers and two studies in patients with schizophrenia. Data from a comparative bioavailability study in medically stable patients and a Phase III study in patients with acute exacerbation of schizophrenia were then incorporated, using empirical Bayesian feedback and model refinement in NONMEM. Finally, covariate analysis was performed on CL40. RESULTS: The final model adequately described the pharmacokinetics of 6288 active moiety concentrations in 17 healthy volunteers and 430 patients with schizophrenia. This one-compartment disposition model had a complex absorption process, combining a small amount immediately entering the central active moiety compartment, two first-order absorption processes and a combined zero-order and first order process, with first-order elimination from the central compartment. Significant covariates on CL40 were BMI and sex. Goodness-of-fit (GOF) plots and visual predictive checks (VPC) confirmed acceptable description of the data. CONCLUSIONS: The population PK model adequately described active moiety concentrations from five clinical studies after risperidone ISM® administration. Relationships between active moiety exposure and covariates were defined in order to facilitate simulations for future studies. The model showed that risperidone ISM® rapidly achieves therapeutic plasma levels within the first hours after the first injection that are maintained sustainedly throughout the whole dosing interval following once-monthly gluteal injections of 100 mg and 75 mg.

Pharmacokinetic-pharmacodynamic modelling and simulation of methotrexate dosing in patients with rheumatoid arthritis.

AIMS: To develop a non-linear mixed-effects population pharmacokinetic and pharmacodynamic (PK-PD) model describing the change in the concentration of methotrexate polyglutamates in erythrocytes (ery-MTX-PGn with "n" number of glutamate, representing PK component) and how this relates to modified 28-joint Disease Activity Score incorporating erythrocyte sedimentation rate (DAS-28-3) for rheumatoid arthritis (RA), representing PD component. METHODS: An existing PK model was fitted to data from a study consisting of 117 RA patients. The estimation of population PK-PD parameters was performed using stochastic approximation expectation maximisation algorithm in Monolix 2021R2. The model was used to perform Monte Carlo simulations of a loading dose regimen (50mg subcutaneous methotrexate as loading doses, then 20mg weekly oral methotrexate) compared to a standard dosing regimen (10mg weekly oral methotrexate for 2 weeks, then 20mg weekly oral methotrexate). RESULTS: Every 40 nmol/L increase in ery-MTX-PG3-5 total concentration correlated with 1-unit reduction in DAS-28-3. Significant covariate effects on the therapeutic response of methotrexate included the use of prednisolone in the first 4 weeks (positive use correlated with 25% reduction in DAS-28-3 when other variables were constant) and patient age (every 10-year increase in age correlated with 3.4% increase in DAS-28-3 when other variables were constant). 4 methotrexate loading doses led to a higher percentage of patients achieving a good/moderate response compared to the standard regimen (Week 4: 87.6% vs. 39.8%; Week 10: 64.7% vs. 57.0%). CONCLUSIONS: A loading dose regimen was more likely to achieve higher ery-MTX-PG concentration and better therapeutic response after 4 weeks of methotrexate treatment.

How to handle a missed or delayed dose of lacosamide in pediatric patients with epilepsy? a mode-informed individual dosing.

This study aims to investigate the effects on the pharmacokinetic (PK) of lacosamide (LCM), and to guide the individual dosing regimens for children and ones with poor medication adherence. Population PK research was performed based on 164 plasma samples of 113 pediatric patients aged from 1.75 to 14.42 years old. The PK characteristic of LCM was developed by a one-compartment model with first-order elimination. The typical value of apparent clearance (CL) and apparent volume of distribution (Vd) was 1.91 L·h-1 and 56.53 L respectively. In the final model, the variability of CL was significantly associated with the body surface area (BSA) and elevated uric acid (UA) level. In contrast, the impact of some prevalent anti-seizure medicines, such as valproic acid, levetiracetam, oxcarbazepine, lamotrigine, and perampanel, and gene polymorphisms of Cytochrome P450 (CYP)2C19, ATP-binding cassette (ABC)B1, and ABCC2 had no clinical significance on the PK parameters of LCM. BSA-based dosing regimen of LCM was provided according to Monte Carlo simulation approach; while the dosage should reduce half in patients with an UA level of more than 400 µmol·L-1 comparing with an UA level of 100 µmol·L-1. Individualize remedial doses of about 0.5- to 1.5-fold of regular doses were recommended in six common scenarios of missed or delayed doses, that depended on the delayed time. In current study, the population PK model of LCM in children with epilepsy was developed successfully. The BSA-based dosing regimen and individualized remedial strategy were recommended to guarantee the precise administration of LCM.

External validation of population pharmacokinetic models of tacrolimus in Thai adult liver transplant recipients.

OBJECTIVE: Several population pharmacokinetic models of tacrolimus in liver transplant patients were built, and their predictability was evaluated in their settings. However, the extrapolation in the prediction was unclear. This study aimed to evaluate the predictive performance of published tacrolimus models in adult liver transplant recipients using data from the Thai population as an external dataset. METHODS: The selected published models were systematically searched and evaluated for their quality. The external dataset of patients who underwent the first liver transplant and received immediate-release tacrolimus was used to assess the predictive performance of each selected model. Trough concentrations between 3 and 6 months were retrospectively collected to evaluate the predictability of each model using prediction-based diagnostics, simulation-based diagnostics, and Bayesian forecasting. RESULTS: Sixty-seven patients with 360 trough concentrations and eight selected published models were included in this study. None of the models met the predictive precision criteria in prediction-based diagnostics. Meanwhile, four published population pharmacokinetic models showed a normal distribution in NPDE testing. Regarding Bayesian forecasting, all models improved their forecasts with at least one prior information data point. CONCLUSION: Bayesian forecasting is more accurate and precise than other testing methods for predicting drug concentrations. However, none of the evaluated models provides satisfactory predictive performance for generalization to Thai liver transplant patients. This underscores the need for future research to develop population PK models tailored to the Thai population. Such efforts should consider the inclusion of nonlinear pharmacokinetics and region-specific factors, including genetic variability, to improve model accuracy and applicability.

Population pharmacokinetic analyses of methotrexate in pediatric patients: a systematic review.

BACKGROUND AND OBJECTIVES: Methotrexate is widely utilized in the chemotherapy of malignant tumors and autoimmune diseases in the pediatric population, but dosing can be challenging. Several population pharmacokinetic models were developed to characterize factors influencing variability and improve individualization of dosing regimens. However, significant covariates included varied across studies. The primary objective of this review was to summarize and discuss population pharmacokinetic models of methotrexate and covariates that influence pharmacokinetic variability in pediatric patients. METHODS: Systematic searches were conducted in the PubMed and EMBASE databases from inception to 7 July 2023. Reporting Quality was evaluated based on a checklist with 31 items. The characteristics of studies and information for model construction and validation were extracted, summarized, and discussed. RESULTS: Eighteen studies (four prospective studies and fourteen retrospective studies with sample sizes of 14 to 772 patients and 2.7 to 93.1 samples per patient) were included in this study. Two-compartment models were the commonly used structural models for methotrexate, and the clearance range of methotrexate ranged from 2.32 to 19.03 L/h (median: 6.86 L/h). Body size and renal function were found to significantly affect the clearance of methotrexate for pediatric patients. There were limited reports on the role of other covariates, such as gene polymorphisms and co-medications, in the pharmacokinetic parameters of methotrexate pediatric patients. Internal and external evaluations were used to assess the performance of the population pharmacokinetic models. CONCLUSION: A more rigorous external evaluation needs to be performed before routine clinical use to select the appropriate PopPK model. Further research is necessary to incorporate larger cohorts or pool analyses in specific susceptible pediatric populations to improve the understanding of predicted exposure profiles and covariate identification.

Fixed parameters in the population pharmacokinetic modeling of valproic acid might not be suitable: external validation in Chinese adults with epilepsy or after neurosurgery.

PURPOSE: This study aims to assess the predictive performance of published valproic acid (VPA) population pharmacokinetic (PPK) models using an external data set in Chinese adults with epilepsy or after neurosurgery. METHODS: A total of 384 concentrations from 290 Chinese adults with epilepsy or after neurosurgery were used for external validation. Data on published VPA PPK models were extracted from the literature. Prediction-based diagnostics (such as F20 and F30), simulation-based diagnostics, and Bayesian forecasting were used to evaluate the predictability of models. RESULTS: The results of prediction-based diagnostics of all models were unsatisfactory. Models B, F, and H showed the best prediction performance in simulation-based diagnostics and Bayesian forecasting, demonstrating superior precision and accuracy. Bayesian forecasting demonstrated significant improvements in the model predictability. CONCLUSION: The published PPK models showed extensive variation in predictive performance for extrapolation among Chinese adults with epilepsy or after neurosurgery patients. Fixed parameters of Vd and Ka in the PPK modeling of VPA might be the reason for the unsatisfied predictive performance. Bayesian forecasting significantly improved model predictability and may help to individualize VPA dosing.

Meropenem pharmacokinetic/pharmacodynamic target attainment and clinical response in ICU patients: A prospective observational study.

BACKGROUND: Several studies report lack of meropenem pharmacokinetic/pharmacodynamic (PK/PD) target attainment (TA) and risk of therapeutic failure with intermittent bolus infusions in intensive care unit (ICU) patients. The aim of this study was to describe meropenem TA in an ICU population and the clinical response in the first 72 h after therapy initiation. METHODS: A prospective observational study of ICU patients ≥18 years was conducted from 2014 to 2017. Patients with normal renal clearance (NRC) and augmented renal clearance (ARC) and patients on continuous renal replacement therapy (CRRT) were included. Meropenem was administered as intermittent bolus infusions, mainly at a dose of 1 g q6h. Peak, mid, and trough levels were sampled at 24, 48, and 72 h after therapy initiation. TA was defined as 100% T > 4× MIC or trough concentration above 4× MIC. Meropenem PK was estimated using traditional calculation methods and population pharmacokinetic modeling (P-metrics®). Clinical response was evaluated by change in C-reactive protein (CRP), Sequential Organ Failure Assessment (SOFA) score, leukocyte count, and defervescence. RESULTS: Eighty-seven patients were included, with a median Simplified Acute Physiology (SAPS) II score 37 and 90 days mortality rate of 32%. Median TA was 100% for all groups except for the ARC group with 45.5%. Median CRP fell from 175 (interquartile range [IQR], 88-257) to 70 (IQR, 30-114) (p < .001) in the total population. A reduction in SOFA score was observed only in the non-CRRT groups (p < .001). CONCLUSION: Intermittent meropenem bolus infusion q6h gives satisfactory TA in an ICU population with variable renal function and CRRT modality, except for ARC patients. No consistent relationship between TA and clinical endpoints were observed.

Population pharmacokinetic/pharmacodynamic modeling of nifekalant injection with varies dosing plan in Chinese volunteers: a randomized, blind, placebo-controlled study.

Nifekalant hydrochloride is a class III antiarrhythmic agent which could increase the duration of the action potential and the effective refractory period of ventricular and atrial myocytes by blocking the K+ current. Nifekalant is used to prevent ventricular tachycardia/ventricular fibrillation. QT interval prolongation is the main measurable drug effect. However, due to the complicated dosing plan in clinic, the relationship among dosage, time, drug concentration and efficacy is not fully understood. In this study, a single-center, randomized, blind, dose-ascending, placebo-controlled study was conducted to explore the intrinsic characteristics of nifekalant injection in healthy Chinese volunteers by a population pharmacokinetic (PK)-pharmacodynamic (PD) model approach. 42 subjects were enrolled in this study and received one of three dose plans (loading dose on Day 1 (0.15, 0.3 or 0.5 mg/kg), loading dose followed by maintenance dose (0.2, 0.4 or 0.8 mg/kg/h) on Day 4) or vehicle. Blood samples were drawn for PK evaluation, and ECGs were recorded for QTc calculation at the designed timepoints. No Torsades de Pointes occurred during the study. The popPK model of nifekalant injection could be described by a two-compartment model with first-order elimination. The population mean clearance (CL) was 53.8 L/h. The population mean distribution volume of the central (Vc) and peripheral (Vp) compartments was 8.27 L and 45.6 L, respectively. A nonlinear dose-response (Emax) model well described the pharmacodynamic effect (QTc interval prolongation) of nifekalant. The Emax and EC50 from current study were 101 ms and 342 ng/mL, respectively.

Subgroup identification-based model selection to improve the predictive performance of individualized dosing.

Currently, model-informed precision dosing uses one population pharmacokinetic model that best fits the target population. We aimed to develop a subgroup identification-based model selection approach to improve the predictive performance of individualized dosing, using vancomycin in neonates/infants as a test case. Data from neonates/infants with at least one vancomycin concentration was randomly divided into training and test dataset. Population predictions from published vancomycin population pharmacokinetic models were calculated. The single best-performing model based on various performance metrics, including median absolute percentage error (APE) and percentage of predictions within 20% (P20) or 60% (P60) of measurement, were determined. Clustering based on median APEs or clinical and demographic characteristics and model selection by genetic algorithm was used to group neonates/infants according to their best-performing model. Subsequently, classification trees to predict the best-performing model using clinical and demographic characteristics were developed. A total of 208 vancomycin treatment episodes in training and 88 in test dataset was included. Of 30 identified models from the literature, the single best-performing model for training dataset had P20 26.2-42.6% in test dataset. The best-performing clustering approach based on median APEs or clinical and demographic characteristics and model selection by genetic algorithm had P20 44.1-45.5% in test dataset, whereas P60 was comparable. Our proof-of-concept study shows that the prediction of the best-performing model for each patient according to the proposed model selection approaches has the potential to improve the predictive performance of model-informed precision dosing compared with the single best-performing model approach.

Optimizing anidulafungin exposure across a wide adult body size range.

Echinocandins like anidulafungin are first-line therapies for candidemia and invasive candidiasis, but their dosing may be suboptimal in obese patients. Our objective was to quantify anidulafungin exposure in a cohort of adults across a wide body size range to test if body size affects anidulafungin pharmacokinetics (PK). We enrolled 20 adults between the ages of 18 and 80 years, with an equal distribution of patients above and below a body mass index of 30 kg/m2. A single 100-mg dose of anidulafungin was administered, followed by intensive sampling over 72 h. Population PK analysis was used to identify and compare covariates of anidulafungin PK parameters. Monte Carlo simulations were performed to compute the probability of target attainment (PTA) based on alternative dosing regimens. Participants (45% males) had a median (range) age of 45 (21-78) years and a median (range) weight of 82.7 (42.4-208.3) kg. The observed median (range) of AUC0-∞ was 106.4 (51.9, 138.4) mg∙h/L. Lean body weight (LBW) and adjusted body weight (AdjBW) were more influential than weight as covariates of anidulafungin PK parameters. The conventional 100 mg daily maintenance is predicted to have a PTA below 90% in adults with an LBW > 55 kg or an AdjBW > 75 kg. A daily maintenance dose of 150-200 mg is predicted in these heavier adults. Anidulafungin AUC0-∞ declines with increasing body size. A higher maintenance dose will increase the PTA compared to the current approach in obese patients.

Systematic Evaluation of Pharmacokinetic Models for Model-Informed Precision Dosing of Meropenem in Critically Ill Patients Undergoing Continuous Renal Replacement Therapy.

The altered pharmacokinetics of renally cleared drugs such as meropenem in critically ill patients receiving continuous renal replacement therapy (CRRT) might impact target attainment. Model-informed precision dosing (MIPD) is applied to individualize meropenem dosing. However, most population pharmacokinetic (PopPK) models developed to date have not yet been evaluated for MIPD. Eight PopPK models based on adult CRRT patients were identified in a systematic literature research and encoded in NONMEM 7.4. A data set of 73 CRRT patients from two different study centers was used to evaluate the predictive performance of the models using simulation and prediction-based diagnostics for i) a priori dosing based on patient characteristics only and ii) Bayesian dosing by including the first measured trough concentration. Median prediction error (MPE) for accuracy within |20%| (95% confidence intervals including zero) and median absolute prediction error (MAPE) for precision ≤ 30% were considered clinically acceptable. For a priori dosing, most models (n = 5) showed accuracy and precision MPE within |20%| and MAPE <35%. The integration of the first measured meropenem concentration improved the predictive performance of all models (median MAPE decreased from 35.4 to 25.0%; median MPE decreased from 21.8 to 4.6%). The best predictive performance for intermittent infusion was observed for the O'Jeanson model, including residual diuresis as covariate (a priori and Bayesian dosing MPE within |2%|, MAPE <30%). Our study revealed the O'Jeanson model as the best-predicting model for intermittent infusion. However, most of the selected PopPK models are suitable for MIPD in CRRT patients when one therapeutic drug monitoring sample is available.

Effects of Body Mass and Age on the Pharmacokinetics of Subcutaneous or Hyaluronidase-facilitated Subcutaneous Immunoglobulin G in Primary Immunodeficiency Diseases.

PURPOSE: To assess the pharmacokinetics (PK) of subcutaneous immunoglobulin (SCIG) and hyaluronidase-facilitated SCIG (fSCIG) therapy across body mass index (BMI) and age categories in patients with primary immunodeficiency diseases (PIDD) previously treated with intravenous immunoglobulin (IVIG). METHODS: Using our previously published integrated population PK model based on data from eight clinical trials, simulations were conducted to examine the effects of BMI and age on serum immunoglobulin G (IgG) PK after administration of SCIG 0.15 g/kg weekly or fSCIG 0.6 g/kg every 4 weeks in patients switching from stable IVIG. Patients were assumed to have baseline IgG trough concentrations of 7 g/L (hypothetical protective threshold). RESULTS: Mean steady-state serum IgG trough values (Cmin,ss or trough) increased with BMI and age. Mean Cmin,ss was 18% (SCIG) and 16% (fSCIG) higher in the obese than the healthy BMI group. Pediatric patients aged < 18 years had 8-22% (SCIG) and 4-20% (fSCIG) lower mean Cmin,ss values than adults, with the youngest group (2- < 6 years) having the lowest Cmin,ss. All patients across populations maintained Cmin,ss IgG concentrations of ≥ 7 g/L after switching to SCIG or fSCIG. CONCLUSION: Both SCIG and fSCIG successfully maintained trough values at or above the hypothetical protective threshold after switching from stable IVIG, irrespective of BMI or age. Differences in trough values between BMI groups and age groups (≤ 22%) may not warrant SCIG or fSCIG dose adjustments based on BMI or age alone; instead, the dosing paradigm should be guided by prior IVIG dose, individual IgG monitoring, and clinical findings.

Adaptation of a population pharmacokinetic model to inform tacrolimus therapy in heart transplant recipients.

AIM: Existing tacrolimus population pharmacokinetic models are unsuitable for guiding tacrolimus dosing in heart transplant recipients. This study aimed to develop and evaluate a population pharmacokinetic model for tacrolimus in heart transplant recipients that considers the tacrolimus-azole antifungal interaction. METHODS: Data from heart transplant recipients (n = 87) administered the oral immediate-release formulation of tacrolimus (Prograf®) were collected. Routine drug monitoring data, principally trough concentrations, were used for model building (n = 1099). A published tacrolimus model was used to inform the estimation of Ka , V2 /F, Q/F and V3 /F. The effect of concomitant azole antifungal use on tacrolimus CL/F was quantified. Fat-free mass was implemented as a covariate on CL/F, V2 /F, V3 /F and Q/F on an allometry scale. Subsequently, stepwise covariate modelling was performed. Significant covariates influencing tacrolimus CL/F were included in the final model. Robustness of the final model was confirmed using prediction-corrected visual predictive check (pcVPC). The final model was externally evaluated for prediction of tacrolimus concentrations of the fourth dosing occasion (n = 87) from one to three prior dosing occasions. RESULTS: Concomitant azole antifungal therapy reduced tacrolimus CL/F by 80%. Haematocrit (∆OFV = -44, P < .001) was included in the final model. The pcVPC of the final model displayed good model adequacy. One recent drug concentration is sufficient for the model to guide tacrolimus dosing. CONCLUSION: A population pharmacokinetic model that adequately describes tacrolimus pharmacokinetics in heart transplant recipients, considering the tacrolimus-azole antifungal interaction was developed. Prospective evaluation is required to assess its clinical utility to improve patient outcomes.

Population pharmacokinetics of subcutaneous alemtuzumab in kidney transplantation.

AIM: Alemtuzumab is a monoclonal antibody used as induction immunosuppressive therapy in kidney transplantation. It targets CD52 on lymphocytes, inducing profound immune cell depletion upon administration. Owing to its off-label status in kidney transplantation, its pharmacokinetic characteristics are largely unknown in this setting, and its current fixed dosing algorithm originates from other populations. We developed a population pharmacokinetic model for alemtuzumab in kidney transplant recipients and investigated the potential of personalized alemtuzumab therapy. METHODS: In total, 362 pharmacokinetic observations drawn 0-165 days after transplantation were available from 61 adult kidney transplant recipients who received two consecutive doses of 15 mg alemtuzumab subcutaneously. A population pharmacokinetic model was developed using nonlinear mixed-effects modelling and applied to simulate various dosing regimens. RESULTS: The alemtuzumab concentration-time data were best described by a two-compartmental model with first-order absorption and parallel first-order and time-varying concentration-dependent elimination, with between-subject variability on the first-order elimination (39.6%) and central distribution volume (39.6%). Alemtuzumab pharmacokinetics varied with body size, rendering lighter individuals exposed to lympholytic alemtuzumab concentrations (>0.1 mg/L) for prolonged durations as compared to their heavier peers. This between-subject variability could be reduced through lean bodyweight-adjusted dosing, showing a twofold to threefold reduction in the slope of the median alemtuzumab exposure over the bodyweight range. CONCLUSION: Alemtuzumab displays substantial pharmacokinetic variability in kidney transplant recipients, which may warrant a personalized treatment strategy. Lean bodyweight-adjusted dosing poses an option for individualized dosing, but further evaluation of its potential clinical benefit is warranted.

Tacrolimus population pharmacokinetics in adult heart transplant patients.

INTRODUCTION: Tacrolimus is an immunosuppressant largely used in heart transplantation. However, the calculation of its exposure based on the area under the curve (AUC) requires the use of a population pharmacokinetic (PK) model. The aims of this work were (i) to develop a population PK model for tacrolimus in heart transplant patients, (ii) to derive a maximum a posteriori Bayesian estimator (MAP-BE) based on a limited sampling strategy (LSS) and (iii) to estimate probabilities of target attainment (PTAs) for AUC and trough concentration (C0). MATERIAL AND METHODS: Forty-seven PK profiles (546 concentrations) of 18 heart transplant patients of the Pharmacocinétique des Immunosuppresseurs chez les patients GREffés Cardiaques study receiving tacrolimus (Prograf®) were included. The database was split into a development (80%) and a validation (20%) set. PK parameters were estimated in MONOLIX® and based on this model a Bayesian estimator using an LSS was built. Simulations were performed to calculate the PTA for AUC and C0. RESULTS: The best model to describe the tacrolimus PK was a two-compartment model with a transit absorption and a linear elimination. Only the CYP3A5 covariate was kept in the final model. The derived MAP-BE based on the LSS (0-1-2 h postdose) yielded an AUC bias ± SD = 2.7 ± 10.2% and an imprecision of 9.9% in comparison to the reference AUC calculated using the trapezoidal rule. PTAs based on AUC or C0 allowed new recommendations to be proposed for starting doses (0.11 mg·kg-1 ·12 h-1 for the CYP3A5 nonexpressor and 0.22 mg·kg1 ·12 h-1 for the CYP3A5 expressor). CONCLUSION: The MAP-BE developed should facilitate estimation of tacrolimus AUC in heart transplant patients.

Population Pharmacokinetic Model of Methotrexate in Brazilian Pediatric Patients with Acute Lymphoblastic Leukemia.

OBJECTIVES: Methotrexate (MTX) is subject to therapeutic drug monitoring because of its high pharmacokinetic variability and safety risk outside the therapeutic window. This study aimed to develop a population pharmacokinetic model (popPK) of MTX for Brazilian pediatric acute lymphoblastic leukemia (ALL) patients who attended the Hospital de Clínicas de Porto Alegre, Brazil. METHODS: The model was developed using NONMEM 7.4 (Icon®), ADVAN3 TRANS4, and FOCE-I. To explain inter-individual variability, we evaluated covariates from demographic, biochemical, and genetic data (single nucleotide polymorphisms [SNPs] related to the transport and metabolism of drugs). RESULTS: A two-compartment model was built using 483 data points from 45 patients (0.33-17.83 years of age) treated with MTX (0.25-5 g/m2) in different cycles. Serum creatinine (SCR), height (HT), blood urea nitrogen (BUN) and a low BMI stratification (according to the z-score defined by the World Health Organization [LowBMI]) were added as clearance covariates. The final model described MTX clearance as [Formula: see text]. In the two-compartment structural model, the central and peripheral compartment volumes were 26.8 L and 8.47 L, respectively, and the inter-compartmental clearance was 0.218 L/h. External validation of the model was performed through a visual predictive test and metrics using data from 15 other pediatric ALL patients. CONCLUSION: The first popPK model of MTX was developed for Brazilian pediatric ALL patients, which showed that inter-individual variability was explained by renal function and factors related to body size.