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 models of tacrolimus in paediatric solid organ transplant recipients: A systematic review.

AIMS: This study aimed to provide up-to-date information on paediatric population pharmacokinetic models of tacrolimus and to identify factors influencing tacrolimus pharmacokinetic variability. METHODS: Systematic searches in the Web of Science, PubMed, Scopus, Science Direct, Cochrane, EMBASE databases and reference lists of articles were conducted from inception to March 2023. All population pharmacokinetic studies of tacrolimus using nonlinear mixed-effect modelling in paediatric solid organ transplant patients were included. RESULTS: Of the 21 studies reviewed, 62% developed from liver transplant recipients and 33% from kidney transplant recipients. Most studies used a 1-compartment model to describe tacrolimus pharmacokinetics. Body weight was a significant predictor for tacrolimus volume of distribution (Vd/F). The estimated Vd/F for 1-compartment models ranged from 20 to 1890 L, whereas the peripheral volume of distribution (Vp/F) for 2-compartment models was between 290 and 1520 L. Body weight, days post-transplant, CYP3A5 genotype or haematocrit were frequently reported as significant predictors of tacrolimus clearance. The estimated apparent clearance values range between 0.12 and 2.18 L/h/kg, with inter-individual variability from 13.5 to 110.0%. Only 29% of the studies assessed the generalizability of the models with external validation. CONCLUSION: This review highlights the potential factors, modelling approaches and validation methods that impact tacrolimus pharmacokinetics in a paediatric population. The clinician could predict tacrolimus clearance based on body weight, CYP3A5 genotype, days post-transplant or haematocrit. Further research is required to determine the relationship between pharmacogenetics and tacrolimus pharmacodynamics in paediatric patients and confirm the applicability of nonlinear kinetics in this population.

Population Pharmacokinetics/Pharmacodynamics and Clinical Outcomes of Meropenem in Critically Ill Patients.

Several pathophysiological changes can alter meropenem pharmacokinetics in critically ill patients, thereby increasing the risk of subtherapeutic concentrations and affecting therapeutic outcomes. This study aimed to characterize the population pharmacokinetic (PPK) parameters of meropenem, evaluate the relationship between the pharmacokinetic/pharmacodynamic index of meropenem and treatment outcomes, and evaluate the different dosage regimens that can achieve 40%, 75%, and 100% of the dosing interval for which the free plasma concentrations remain above the MIC of the pathogens (fT>MIC) targets. Critically ill adult patients treated with meropenem were recruited for this study. Five blood samples were collected from each patient. PPK models were developed using a nonlinear mixed-effects modeling approach, and the final model was subsequently used for Monte Carlo simulations to determine the optimal dosage regimens. A total of 247 concentrations from 52 patients were available for analysis. The two-compartment model with linear elimination adequately described the data. The mean PPK parameters were clearance (CL) of 4.8 L/h, central volume of distribution (VC) of 11.4 L, peripheral volume of distribution (VP) of 14.6 L, and intercompartment clearance of 10.5 L/h. Creatinine clearance was a significant covariate affecting CL, while serum albumin level and shock status were factors influencing VC and VP, respectively. Although 75% of the drug-resistant infection patients had fT>MIC values of >40%, approximately 83% of them did not survive the infection. Therefore, 40% fT>MIC might not be sufficient for critically ill patients, and a higher target, such as 75 to 100% fT>MIC, should be considered for optimizing therapy. A 75% fT>MIC could be reached using approved doses administered via a 3-h infusion.

Population Pharmacokinetics and Pharmacodynamics of Vancomycin in Pediatric Patients With Various Degrees of Renal Function.

OBJECTIVE: Although vancomycin dosage recommendations in the pediatric setting for methicillin-resistant Staphylococcus aureus (MRSA) infection indicate that ≥60 mg/kg/day is correlated to a desired area under the vancomycin concentration time curve from 0 to 24 hours to minimum inhibitory concentration ratio (AUC0-24 hr/MIC) ≥400, for some patients this dosage is inadequate or relates to toxicity. This study purposed to explore vancomycin dosing for pediatrics with various degrees of renal function. METHODS: Routine monitoring data were retrospectively collected from patients, aged 1 month to 18 years. Population pharmacokinetic analysis was performed by using non-linear mixed-effect model with NONMEM software, and Monte Carlo simulation was conducted by using Crystal Ball software. RESULTS: Two hundred twelve patients with 348 vancomycin serum concentrations were included. Median age was 3.5 years (IQR, 0.9-10.9), median weight was 14.0 kg (IQR, 7.2-30.4), with baseline estimated glomerular filtration rate (eGFR) ranging from 15.5 to 359.3 mL/min/1.73 m2. A 1-compartment model with first-order elimination sufficiently described vancomycin PK. The dosing targeting AUC0-24hr/MIC ≥400 and AUC0-24hr <800 mg•h/L for pediatric patients with eGFRs of 15 to 29, 30 to 59, 60 to 89, 90 to 129, and 130 to 160 mL/min/1.73 m2 was 12.5, 25, 40, 60, and 70 mg/kg/day, respectively. All vancomycin dosing obtained >85% of the cumulative fraction of response across the MIC distribution of MRSA. CONCLUSIONS: Vancomycin dosing of 12.5, 25, 40, 60, and 70 mg/kg/day is suggested for pediatric patients with eGFRs of 15 to 29, 30 to 59, 60 to 89, 90 to 129, and 130 to 160 mL/min/1.73 m2, respectively.

Comparison of area under the curve for vancomycin from one- and two-compartment models using sparse data.

BACKGROUND AND OBJECTIVE: Vancomycin pharmacokinetics have been described by both one- and two-compartment models. One-compartment models are widely used to predict the area under the curve (AUC), a useful parameter for determining the efficacy and safety of vancomycin, based on sparse data collected during therapeutic drug monitoring. It is uncertain whether AUCs from one-compartment models with sparsely sampled data can sufficiently represent the true AUC. This study aimed to compare AUC estimates from one- and two-compartment models using sparse data. The reliability of AUCs from models constructed with trough-only data was also assessed. METHODS: A previously published robust model was used to simulate vancomycin concentration points at 15 min intervals in 100 patients. From these simulated data, the reference AUC (AUCref) was calculated and two depleted dataset versions (trough-only and peak-trough datasets) were also created. One- and two-compartment models were built from the depleted datasets with the use of NONMEM. Vancomycin 24-hour AUC was calculated from concentration-time profiles of each model by a linear trapezoidal formula at three different time periods: 0-24 hours (AUC0-24), 24-48 hours (AUC24-48) and 0-48 hours (AUCavg). The deviation of each of the AUCs from the AUCref was examined to assess the AUC predictability of models from sparse data. The difference in AUCs between one- and two-compartment models was analysed from statistical and clinical perspectives. RESULTS: When assessing the deviation of each AUC from the AUCref, the one-compartment model from both peak-trough and trough-only data could adequately represent the true AUC with no statistically significant differences. Two-compartment model from peak-trough data also provided similar AUC estimates with the AUCref. However, AUCs from the two-compartment model with trough-only data did not adequately represent the true AUC, with significant differences of 25.16% for AUC0-24, 15.92% for AUC24-48 and 19.45% for AUCavg. CONCLUSION: Regardless of statistically significant differences between AUCs from one- and two-compartment models, the level of difference was acceptable from the clinical perspective, being <17% in models from peak-trough data. Therefore, both one- and two-compartment models with sparse data having at least a pair of peak-trough data per patient could be reliable for predicting AUC. Furthermore, AUCs of the one-compartment model from trough-only data did not show a significant difference from the AUCref. Hence, one-compartment models developed from trough-only data could be useful for predicting AUC when models with rich data are not available for the intended population. However, it is suggested that the use of the two-compartment model built from trough-only data should be avoided.

Dose recommendations for intravenous colistin in pediatric patients from a prospective, multicenter, population pharmacokinetic study.

OBJECTIVES: The aim of this study was to describe the population pharmacokinetics of intravenous colistin use in children and to propose optimal dosage regimens. METHODS: A prospective, multicenter, population pharmacokinetic (PPK) study was conducted. Phoenix 64 version 8.3 was used for the PPK analysis. Simulations were performed to estimate the probability of target attainment for patients achieving target plasma colistin average steady-state concentrations (Css,avg). RESULTS: A total of 334 plasma colistin concentrations were obtained from 79 pediatric patients with a median age (interquartile range) of 2.6 years (0.8-6.8 years); 73 (92.4%) were admitted to intensive care units. Colistin pharmacokinetics were adequately described by a one-compartment model with first-order elimination along with serum creatinine (SCr) as a significant covariate in colistin clearance. The simulation demonstrated that the recommended dose of 5 mg of colistin base activity (CBA)/kg/day resulted in 18.2-63.0% probability of achieving a target Css,avg of 2 mg/l. With a lower targeted Css,avg of 1 mg/l, colistin dosing with 7.5 mg and 5 mg of CBA/kg/day were adequate for children with SCr levels of 0.1-0.3 mg/dl and >0.3 mg/dl, respectively. CONCLUSIONS: SCr is a significant covariate in colistin clearance in children. Colistin dosing should be selected according to the patient's SCr level and the desired target Css,avg.

Population pharmacokinetics of oral levofloxacin in healthy volunteers and dosing optimization for multidrug-resistant tuberculosis therapy.

Levofloxacin is considered a key component of a multidrug-resistant tuberculosis (MDR-TB) regimen. However, there is considerable concern regarding the subtherapeutic concentrations of the currently used doses and the development of drug resistance. Therefore, this study aimed to describe the population pharmacokinetics (PPK) of oral levofloxacin in healthy volunteers and to evaluate the probability of target attainment (PTA) in an attempt to optimize the dosing regimens for MDR-TB therapy. Data of levofloxacin in healthy volunteers from a previous study were used to construct a PPK model. Monte Carlo simulations were performed to derive the PTAs of various regimens. A two-compartment model with linear elimination and transit absorption compartments best described the pharmacokinetics (PK) of levofloxacin. The estimated PK parameters (interindividual variability, %) were: apparent clearance 8.32 L h-1 (22.6%), apparent central volume of distribution 35.8 L (45.2%), apparent peripheral volume of distribution 39.7 L, intercompartmental clearance 40.6 L h-1 (43.8%), absorption rate constant 7.45 h-1 (150%), mean absorption transit time 0.355 h (52.4%), and total number of transit compartments 6.01 (131.9%). Monte Carlo simulations using levofloxacin 750-1000 mg yielded a probability of achieving a target free area under the concentration-time curve/minimum inhibitory concentration (MIC) of 100 at greater than 90% for Mycobacterium tuberculosis with an MIC < 0.5 mg L-1 , while a dose of 1500 mg was required for strains with an MIC of 1 mg L-1 . A higher dose of levofloxacin might be needed to treat tuberculosis. However, further studies on the efficacy and safety of this dose are needed to confirm our findings.

Aloe vera and health outcomes: An umbrella review of systematic reviews and meta-analyses.

This umbrella review aims to summarize the effects of Aloe vera on health outcomes and assess the strength of evidence. PubMed, Scopus, Embase, Cochrane database of systematic reviews, CINAHL, and AMED were searched from inception to October, 2019 for systematic reviews and meta-analyses of clinical trials that investigated the effects of Aloe vera on health outcomes. Two independent reviewers extracted data, assessed the methodological quality, and rated the credibility of evidence according to established criteria. Ten articles reporting 71 unique outcomes of Aloe vera were included. Of these, 47 (67%) were nominally statistically significant based on random-effects model (p ≤ .05). Only 3 outcomes were supported by highly suggestive evidence, whereas 42 outcomes were supported by weak evidence. The highly suggestive evidence supported benefits of Aloe vera in the prevention of second-degree infusion phlebitis (RR: 0.18, 95% CI: 0.10-0.32, p-value: 1.75 × 10-9 ) and chemotherapy-induced phlebitis based on overall incidence (OR: 0.13, 95% CI: 0.08-0.20, p-value: 9.68 × 10-20 ) and incidence of the second degree of severity (OR: 0.10, 95% CI: 0.07-0.14, p-value: 3.41 × 10-35 ). However, the majority of the evidence were limited by small sample size and poor methodological quality. Therefore, despite the overall favorable effect of Aloe vera, more robust studies are needed.

Evaluation of Intravenous Fosfomycin Disodium Dosing Regimens in Critically Ill Patients for Treatment of Carbapenem-Resistant Enterobacterales Infections Using Monte Carlo Simulation.

There are limited intravenous fosfomycin disodium (IVFOS) dosing regimens to treat carbapenem-resistant Enterobacterales (CRE) infections. This study aimed to use Monte Carlo simulation (MCS) for evaluation of IVFOS dosing regimens in critically ill patients with CRE infections. The dosing regimens in critically ill patients with various creatinine clearance were evaluated with MCS using minimum inhibitory concentration (MIC) distributions of fosfomycin against CRE clinical isolates in Thailand and the 24 h area under the plasma drug concentration-time curve over the minimum inhibitory concentration (AUC0-24/MIC) of ≥21.5 to be a target for IVFOS. The achieved goal of the probability of target attainment (PTA) and a cumulative fraction of response (CFR) were ≥90%. A total of 129 non-duplicated CRE clinical isolates had MIC distributions from 0.38 to >1024 mg/L. IVFOS 8 g every 8 h, 1 h, or 4 h infusion, could achieve approximately 90% PTA of AUC0-24/MIC target to treat CRE infections with MICs ≤ 128 mg/L. According to PTA target, an IVFOS daily dose to treat carbapenem-resistant Escherichia coli based on Clinical Laboratory Standards Institute (CLSI) breakpoints for urinary tract infections and one to treatment for CRE infections based on the European Committee on Antimicrobial Susceptibility Testing (EUCAST) breakpoints were 16 g/day and 8 g/day, respectively. All dosing regimens of IVFOS against CRE achieved CFR ≤ 70%. This study proposes the IVFOS dosing regimens based on CLSI and EUCAST breakpoints for the treatment of CRE infections. However, further clinical studies are needed to confirm the results of these findings.

Optimizing Vancomycin Use Through 2-Point AUC-Based Therapeutic Drug Monitoring in Pediatric Patients.

The 24-hour vancomycin area under the serum concentration-time curve (AUC24 ) divided by the minimum inhibitory concentration (MIC) (AUC24 /MIC) is more closely related to patient outcomes than serum trough concentrations (Ctrough ). Two-point simplified equations for calculating AUC based on serum peak concentrations (Cpeak ) and Ctrough , named equation A (EqA) and equation B (EqB), have recently been adopted into clinical use for adult pediatric patients. We aimed to find the agreement between predicted AUC24 using the reference method (ref) relative to EqA and EqB and the correlation between Ctrough and AUC24 . From June to December 2018, 43 pediatric patients with normal renal function, receiving 15 mg/kg of vancomycin intravenously every 6 hours, were enrolled. The pediatric patients' median age was 2.2 years (range 0.1-15.3). At steady state, vancomycin Cpeak and Ctrough were measured at 2 hours after infusion completion and within 30 minutes before the next dosing, respectively. AUC24 was estimated using ref, EqA, and EqB. From Bland-Altman analysis, the 2 AUC24 s estimated by ref and EqA showed less bias than those estimated by ref and EqB (bias 1.3 and -72.1 mg⋅h/L, respectively). Ctrough and AUC24 using either ref or EqA were correlated more closely (r2 = 0.94) than with EqB (r2 = 0.86). Assuming a vancomycin MIC of 1 mg/L, an AUC24 ≥400 mg⋅h/L was targeted. Regardless of the method used, AUC24 ≥400 mg⋅h/L was never seen with Ctrough <8 mg/L but was always seen with Ctrough >10 mg/L. In conclusion, EqA based on the 2 measured serum concentrations was sufficiently accurate for AUC24 estimation. Ctrough >10 mg/L correlated highly to AUC24 ≥400 mg⋅h/L.

Population pharmacokinetics and pharmacodynamics of piperacillin in critically ill patients during the early phase of sepsis.

This study aimed to characterize the population pharmacokinetics (PKs) of piperacillin and investigate probability of target attainment (PTA) and cumulative fraction of response (CFR) of various dosage regimens in critically ill patients during the early phase of sepsis. Forty-eight patients treated with piperacillin/tazobactam were recruited. Five blood samples were drawn before and during 0-0.5, 0.5-2, 2-4 and 4-6 or 8 h after administration. Population PKs was analyzed using NONMEM®. The PTA of 90%fT>MIC target and CFR were determined by Monte Carlo simulation. The two compartment model best described the data. Piperacillin clearance (CL) was 5.37 L/h, central volume of distribution (V1) was 9.35 L, and peripheral volume of distribution was 7.77 L. Creatinine clearance (CLCr) and mean arterial pressure had a significant effect on CL while adjusted body weight had a significant impact on V1. Subtherapeutic concentrations can occur during the early phase of sepsis in critically ill patients with normal renal function. The usual dosage regimen, 4 g of piperacillin infused over 0.5 h every 6 h, could not achieve the target for susceptible organisms with MIC 16 mg/L in patients with CLCr ≥ 60 mL/min. Our proposed regimen for the patients with CLCr 60-120 mL/min was an extended 2 h infusion of 4 g of piperacillin every 6 h. Most regimens provided CFR ≥ 90% for the E. coli infection while there was no dosage regimen achieved a CFR of 90% for the P. aeruginosa infection.

Evaluation of FOCEI and SAEM Estimation Methods in Population Pharmacokinetic Analysis Using NONMEM® Across Rich, Medium, and Sparse Sampling Data.

BACKGROUND AND OBJECTIVES: First-order conditional estimation with interaction (FOCEI) is one of the most commonly used estimation methods in nonlinear mixed effects modeling, while the stochastic approximation expectation maximization (SAEM) is the newer estimation algorithm. This work aimed to compare the performance of FOCEI and SAEM methods when using NONMEM® with the classical one- and two-compartment models across rich, medium, and sparse data. METHODS: One- and two-compartment models of the previous studies were used to simulate data in three scenarios: rich, medium, and sparse data. For each scenario, there were 100 data sets, containing 100 individuals in each data set. Every data set was estimated with both FOCEI and SAEM methods. The simulation and estimation were performed using NONMEM®. The completion rates, percentage of relative estimation errors (%RERs), root mean square errors (RMSEs), and runtimes were considered to assess the completion, accuracy, precision, and speed of estimation, respectively. RESULTS: Both FOCEI and SAEM methods provided comparable completion rates, median %RERs (ranged from - 9.03 to 3.27% for FOCEI and - 9.17 to 3.27% for SAEM) and RMSEs (ranged from 0.0004 to 1.244 for FOCEI and 0.0004 to 1.131 for SAEM) for most parameters in both models across three scenarios. The run times were much shorter with FOCEI (ranged from 0.18 to 0.98 min) compared to SAEM method (ranged from 4.64 to 12.03 min). CONCLUSIONS: For the classical one- and two-compartment models, FOCEI method exhibited comparable performance similar to SAEM method but with significantly shorter runtimes across rich, medium, and sparse sampling scenarios.

Population Pharmacokinetics and Pharmacodynamics Modeling To Optimize Dosage Regimens of Sulbactam in Critically Ill Patients with Severe Sepsis Caused by Acinetobacter baumannii.

Sulbactam is being considered as an alternative concomitant medication with other effective antibiotics for the treatment of multidrug-resistant (MDR) Acinetobacter baumannii infections. Pathophysiological changes in critically ill patients with severe sepsis, resulting in altered pharmacokinetic (PK) patterns for antibiotics, are important factors in determining therapeutic success. The aims of this study were (i) to examine the population PK parameters and (ii) to assess the probability of target attainment (PTA) for sulbactam in patients with severe sepsis caused by A. baumannii PK studies were carried out following administration of 2 g of sulbactam every 12 h on the 4th day of drug administration in 27 patients, and a Monte Carlo simulation was performed to determine the PTA of achieving 40% exposure time during which the plasma drug concentration remained above the MIC (T>MIC) and 60% T>MIC The central and peripheral volumes of distribution were 14.56 and 9.55 liters, respectively, and total clearances of sulbactam were 2.26 liters/h and 7.64 liters/h in patients aged >65 years and ≤65 years, respectively. The high PTAs (≥90%) for targets of 40% T>MIC and 60% T>MIC with a MIC of 4 µg/ml were observed when sulbactam was administered by a 4-h infusion of 1 g every 12 h and 1 g every 8 h, respectively. Sulbactam would be an alternative antibiotic option to coadminister with colistin for the treatment of infections caused by MDR A. baumannii However, for pathogens with MICs of >4 µg/ml, higher dosage regimens of sulbactam are required.

Population pharmacokinetics and Monte Carlo dosing simulations of meropenem during the early phase of severe sepsis and septic shock in critically ill patients in intensive care units.

Pathophysiological changes during the early phase of severe sepsis and septic shock in critically ill patients, resulting in altered pharmacokinetic (PK) patterns for antibiotics, are important factors influencing therapeutic success. The aims of this study were (i) to reveal the population PK parameters and (ii) to assess the probability of target attainment (PTA) for meropenem. The PK studies were carried out following administration of 1 g of meropenem every 8 h during the first 24 h of severe sepsis and septic shock in nine patients, and a Monte Carlo simulation was performed to determine the PTA of achieving 40% exposure time during which the free plasma drug concentration remains above the MIC (fT>MIC) and 80% fT>MIC. The volume of distribution (V) and total clearance (CL) of meropenem in these patients were 23.7 liters and 7.82 liters/h, respectively. For pathogens with MICs of 4 µg/ml, the PTAs of 40% fT>MIC following administration of meropenem as a 1-h infusion of 1 g every 8 h and a 4-h infusion of 0.5 g every 8 h were 92.52% and 90.29%, respectively. For pathogens with MICs of 2 µg/ml in immunocompromised hosts, the PTAs of 80% fT>MIC following administration of 1-h and 4-h infusions of 2 g of meropenem every 8 h were 84.32% and 94.72%, respectively. These findings indicated that the V of meropenem was greater and the CL of meropenem was lower than the values obtained in a previous study with healthy subjects. The maximum recommended dose, i.e., 2 g of meropenem every 8 h, may be required for treatment of life-threatening infections in this patient population.