Vancomycin AUC0-24 estimation using first-order pharmacokinetic methods in pediatric patients.

INTRODUCTION: The optimal dosing and monitoring of vancomycin in pediatrics is still unknown but has evolved to emphasize area under the curve over 24 h (AUC0-24) over minimum concentration (Cmin) monitoring. Real-world data supporting the feasibility of two-concentration kinetics with first-order equations for the estimation of vancomycin AUC0-24 in pediatric patients are lacking. OBJECTIVES: To describe the interplay of vancomycin dose, AUC0-24, and Cmin using first-order equations within four pediatric age groups. METHODS: This is a single-center, retrospective cohort study analyzing pediatric patients (<18 years) receiving intravenous vancomycin between 2020 and 2022. Included patients received at least 24 h of intravenous vancomycin with two concentrations obtained within 96 h of therapy initiation. Patients with baseline renal dysfunction were excluded. Patients were divided into four age categories: neonates (≤28 days), infants (29 days to <1 year), children (1-12 years), and adolescents (13-17 years). First-order equations were utilized to estimate pharmacokinetic parameters and AUC0-24. RESULTS: Overall, 219 patients (median age of 6 years [IQR 1-12]) met inclusion criteria. The median vancomycin daily dose was 30 mg/kg in neonates, 70 mg/kg in infants and children, and 52 mg/kg in adolescents. Median Cmin and AUC0-24 values among all age groups were 8.68 mg/L and 505 mg * h/L, respectively. For AUC0-24 values outside of the therapeutic range (400-600 mg * h/L), more values were SUPRAtherapeutic (>600 mg * h/L) than SUBtherapeutic (<400 mg * h/L). The overall trend within our data showed suboptimal correlation between Cmin and AUC0-24. However, 71% of patients with Cmin values of 5-10 mg/L had an AUC0-24 within the therapeutic range of 400-600 mg * h/L, whereas 23 patients (92%) with a SUPRAtherapeutic AUC0-24 had a Cmin value ≥15 mg/L. Approximately 10% of patients experienced acute kidney injury. CONCLUSIONS: Our data describe the relationship between vancomycin dose, Cmin, and AUC0-24 in pediatric patients. We demonstrated the feasibility of using first-order equations to estimate AUC0-24, using two concentrations obtained at steady state to monitor efficacy and safety in pediatric patients receiving intravenous vancomycin. Our data showed suboptimal correlation between AUC0-24 and Cmin, which indicates that Cmin should not be used as a surrogate marker for a therapeutic AUC0-24 in pediatric patients. In alignment with the 2020 vancomycin consensus guidelines, we suggest utilizing AUC0-24 for efficacy and safety monitoring.

Bayesian Vancomycin Model Selection for Therapeutic Drug Monitoring in Neonates.

BACKGROUND AND OBJECTIVE: Pharmacokinetic models can inform drug dosing of vancomycin in neonates to optimize therapy. However, the model selected needs to describe the intended population to provide appropriate dose recommendations. Our study aims to identify the population pharmacokinetic (PopPK) model(s) with the best performance to predict vancomycin exposure in neonates in our hospital. METHODS: Relevant published PopPK models for vancomycin in neonates were selected based on demographics and vancomycin dosing strategy. The predictive performance of the models was evaluated in Tucuxi using a local cohort of 69 neonates. Mean absolute error (MAE), relative bias (rBias) and relative root mean square error (rRMSE) were used to quantify the accuracy and precision of the predictive performance of each model for three different approaches: a priori, a posteriori, and Bayesian forecasting for the next course of therapy based on the previous course predictions. A PopPK model was considered clinically acceptable if rBias was between ± 20 and 95% confidence intervals included zero. RESULTS: A total of 25 PopPK models were identified and nine were considered suitable for further evaluation. The model of De Cock et al. 2014 was the only clinically acceptable model based on a priori [MAE 0.35 mg/L, rBias 0.8 % (95% confidence interval (CI) - 7.5, 9.1%), and rRMSE 8.9%], a posteriori [MAE 0.037 mg/L, rBias - 0.23% (95% CI - 1.3, 0.88%), and rRMSE 6.02%] and Bayesian forecasting for the next courses [MAE 0.89 mg/L, rBias 5.45% (95% CI - 8.2, 19.1%), and rRMSE 38.3%) approaches. CONCLUSIONS: The De Cock model was selected based on a comprehensive approach of model selection to individualize vancomycin dosing in our neonates.

Utility of cystatin C and serum creatinine-based glomerular filtration rate equations in predicting vancomycin clearance: A population pharmacokinetics analysis in elderly Chinese patients.

Renal function is an important factor affecting the pharmacokinetics of vancomycin. The renal function in elderly patients gradually decreases with age. An accurate estimated glomerular filtration rate (GFR) is essential in drug dosing. The study aimed to determine the most appropriate renal function estimation equations to describe vancomycin pharmacokinetics in elderly patients using population pharmacokinetic analysis. Data were obtained retrospectively from elderly patients aged ≥65 years who received vancomycin for infection from September 2016 to January 2022. Renal function was estimated using the Cockcroft-Gault equation (CG), Modification of Diet in Renal Disease equation (MDRD), three Chronic Kidney Disease Epidemiology Collaboration equations (CKD-EPIcys-scr , CKD-EPIscr , and CKD-EPIcys ) and two Berlin Initiative Study equations (BIS-1 and BIS-2). The CKD-EPIcys-scr and BIS-2 equations were based on cystatin C (Cys C) and serum creatinine (Scr). The others were based on Cys C or Scr. A nonlinear mixed effects model (NONMEM) was used to develop the population pharmacokinetic model. A total of 471 serum concentrations from 313 elderly patients were used to develop the population pharmacokinetic model. Weight and GFR were identified as significant covariates affecting the pharmacokinetics of vancomycin. Cys C and Scr-based GFR (CKD-EPIcys-scr and BIS-2) yielded significant improvement performance compared with the other equations in model building. The interindividual variability of CL was reduced from 49.4% to 23.6% and 49.4% to 23.7% in CKD-EPIcys-scr and BIS-2 based models, respectively. However, greater interindividual variabilities of CL (from 26.6% to 29.0%) were represented in the other five models which were based on either Cys C or Scr. The GFR estimated by EPIcys-scr and BIS-2 equations and vancomycin CL exhibited a good correlation (r = 0.834 and 0.833). In the external validation with 124 serum concentrations, the predictive performances of the CKD-EPIcys-scr and BIS-2 based models (the mean relative prediction errors were less than 1%, the mean relative absolute prediction errors were about 23%) were also superior to the other five models (the mean relative prediction errors were about 2%, the mean relative absolute prediction errors were greater than 25%) which are based on either Cys C or Scr. In this study, we determined that the equation used to estimate GFR can affect the population pharmacokinetic model fitting result. Population pharmacokinetics model with CKD-EPIcys-scr or BIS-2 can be used to optimize vancomycin dosage in elderly Chinese patients.

How to Dose Vancomycin in Overweight and Obese Patients with Varying Renal (Dys)function in the Novel Era of AUC 400-600 mg·h/L-Targeted Dosing.

BACKGROUND AND OBJECTIVE: The latest vancomycin guideline recommends area under the curve (AUC)-targeted dosing and monitoring for efficacy and safety. However, guidelines for AUC-targeted starting dosing in patients with obesity and/or renal insufficiency are currently lacking. This study quantifies the pharmacokinetics (PK) of vancomycin in this population and provides AUC-targeted dosing recommendations. METHODS: Vancomycin concentrations (n = 1188) from therapeutic drug monitoring of 210 overweight and obese patients with varying degrees of renal (dys)function from the ward (74.8%) and intensive care unit (ICU, 25.2%) were pooled with published rich concentration-time data (n = 207) from 20 (morbidly) obese subjects undergoing bariatric surgery. A population model was developed using NONMEM 7.4. Stochastic simulations were performed to design dosing guidelines targeting an AUC24 between 400-600 mg·h/L. RESULTS: Vancomycin clearance (CL) was found to increase linearly with total bodyweight and with renal function (CKD-EPI) in a power relation. Additionally, CL proved 15.5% lower in ICU patients. Our model shows that, to reach the target AUC between 400 and 600 mg·h/L in the first 48 h, two loading doses are required for both continuous infusion and intermittent dosing regimens. Maintenance doses were found to require adjustment for total bodyweight, renal function, and ICU admission status. With this guideline, the median AUC24 is well within the target from the start of the treatment onwards. CONCLUSIONS: To achieve safe and effective vancomycin exposure for maintenance doses in overweight and obese patients, renal function, total bodyweight, and ICU admission status should be taken into account. TRIAL REGISTRATION: The AMIGO trial was registered in the Dutch Trial Registry [NTR6058].

Therapeutic drug monitoring of vancomycin and meropenem: Illustration of the impact of inaccurate information in dose administration time.

OBJECTIVES: To illustrate the impact of errors in documented dose administration time on therapeutic drug monitoring (TDM)-based target attainment evaluation for vancomycin and meropenem, and to explore the influence of drug and patient characteristics, and TDM sampling strategies. METHODS: Bedside observations of errors in documented dose administration times were collected. Population pharmacokinetic simulations were performed for vancomycin and meropenem, evaluating different one- and two-sampling strategies for populations with estimated creatinine clearance (CLcr) of 30, 80 or 130 mL/min. The impact of errors was evaluated as the proportion of individuals incorrectly considered to have reached the target. RESULTS: Of 143 observed dose administrations, 97% of doses were given within ±30 min of the documented time. For vancomycin, a +30 min error was predicted to result in a 0.1-3.9 percentage point increase of cases incorrectly evaluated as reaching area under the concentration-time curve during a 24-hour period (AUC24)/minimum inhibitory concentration (MIC) >400, with the largest increase for patients with augmented renal clearance and peak and trough sampling. For meropenem, a +30 min error resulted in a 1.3-6.4 and 0-20 percentage point increase of cases incorrectly evaluated as reaching 100% T>MIC, and 50% T>MIC, respectively. Overall, mid-dose and trough sampling was most favourable for both antibiotics. CONCLUSIONS: For vancomycin, simulations indicate that TDM-based target attainment evaluation is robust with respect to the observed errors in dose administration time of ±30 min; however, the errors had a potentially clinically important impact in patients with augmented renal clearance. For meropenem, extra measures to promote correct documentation are warranted when using TDM, as the impact of errors was evident even in patients with normal renal function.

External Validation of Obese/Critically Ill Vancomycin Population Pharmacokinetic Models in Critically Ill Patients Who Are Obese.

Obesity combined with critical illness might increase the risk of acquiring infections and hence mortality. In this patient population the pharmacokinetics of antimicrobials vary significantly, making antimicrobial dosing challenging. The objective of this study was to assess the predictive performance of published population pharmacokinetic models of vancomycin in patients who are critically ill or obese for a cohort of critically ill patients who are obese. This was a multi-center retrospective study conducted at 2 hospitals. Adult patients with a body mass index of ≥30 kg/m2 were included. PubMed was searched for published population pharmacokinetic studies in patients who were critically ill or obese. External validation was performed using Monolix software. A total of 4 models were identified in patients who were obese and 5 models were identified in patients who were critically ill. In total, 138 patients who were critically ill and obese were included, and the most accurate models for these patients were the Goti and Roberts models. In our analysis, models in patients who were critically ill outperformed models in patients who were obese. When looking at the most accurate models, both the Goti and the Roberts models had patient characteristics similar to ours in terms of age and creatinine clearance. This indicates that when selecting the proper model to apply in practice, it is important to account for all relevant variables, besides obesity.

Pharmacokinetics of Locally Applied Antibiotic Prophylaxis for Implant-Based Breast Reconstruction.

Importance: Antibiotic irrigation of breast implants is widely used internationally, but no clinical study has investigated the pharmacokinetics of antibiotic prophylaxis in the breast implant pocket. Objectives: To evaluate how long locally applied gentamicin, cefazolin, and vancomycin concentrations in the implant pocket remain above the minimum inhibitory concentration (MIC) for the most common bacterial infections and to measure systemic uptake. Design, Setting, and Participants: This prospective cohort study was performed at the Department of Plastic Surgery and Burns Treatment, Rigshospitalet, Copenhagen, Denmark, between October 25, 2021, and September 22, 2022, among 40 patients undergoing implant-based breast reconstruction who were part of the ongoing BREAST-AB trial (Prophylactic Treatment of Breast Implants With a Solution of Gentamicin, Vancomycin and Cefazolin Antibiotics for Women Undergoing Breast Reconstructive Surgery: a Randomized Controlled Trial). Patients were randomized to receive locally applied gentamicin, cefazolin, and vancomycin or placebo. Samples were obtained from the surgical breast drain and blood up to 10 days postoperatively. Exposures: The breast implant and the implant pocket were irrigated with 160 µg/mL of gentamicin, 2000 µg/mL of cefazolin, and 2000 µg/mL of vancomycin in a 200-mL saline solution. Main Outcomes and Measures: The primary outcome was the duration of antibiotic concentrations above the MIC breakpoint for Staphylococcus aureus according to the Clinical and Laboratory Standards Institute: gentamicin, 4 µg/mL; cefazolin, 2 µg/mL; and vancomycin, 2 µg/mL. Secondary outcomes included the time above the MIC for Pseudomonas aeruginosa and other relevant bacteria, as well as systemic uptake. Results: The study included 40 patients (median age, 44.6 years [IQR, 38.3-51.4 years]; median body mass index, 23.9 [IQR, 21.7-25.9]) with a median number of 3 drain samples (range, 1-10 drain samples) and 2 blood samples (range, 0-6 blood samples). Vancomycin and cefazolin remained above the MIC for S aureus significantly longer than gentamicin (gentamicin, 0.9 days [95% CI, 0.5-1.2 days] for blood samples vs 6.9 days [95% CI, 2.9 to 10.9 days] for vancomycin [P = .02] vs 3.7 days [95% CI, 2.2-5.2 days] for cefazolin [P = .002]). The gentamicin level remained above the MIC for P aeruginosa for 1.3 days (95% CI, 1.0-1.5 days). Only cefazolin was detectable in blood samples, albeit in very low concentrations (median concentration, 0.04 µg/mL [range, 0.007-0.1 µg/mL]). Conclusions and Relevance: This study suggests that patients treated with triple-antibiotic implant irrigation during breast reconstruction receive adequate prophylaxis for S aureus and other common implant-associated, gram-positive bacteria. However, the protection against P aeruginosa may be inadequate.

Population Pharmacokinetic Analysis of Vancomycin in Patients with Solid or Hematological Malignancy in Relation to the Quick Sequential Organ Failure Assessment Scores.

BACKGROUND AND OBJECTIVE: It remains unclear whether sepsis in patients with malignancy interferes with the predictive performance of the dose-estimation formulas. The quick sequential organ failure assessment (qSOFA) score can help identify patients with poor outcomes because of sepsis-associated organ damage. Vancomycin, an important antibiotic, treats systemic infections (sepsis) caused by methicillin-resistant Staphylococcus aureus. We aimed to clarify whether including the qSOFA score in a standard population pharmacokinetic (PopPK) assessment may improve the predictive performance of vancomycin doses in patients with malignancy. METHODS: This was a retrospective, observational study. Serum vancomycin concentration-time datasets were obtained from the therapeutic drug monitoring records of St. Luke's International Hospital (Tokyo, Japan) from January 2011 to August 2016. Clinical and laboratory data of the relevant patients were retrieved from electronic health records. PopPK analysis was performed using the NONMEM program, which includes creatinine clearance (CLCr), blood neutrophil counts, qSOFA scores, and type of malignancy as covariates. We examined the validity of the final PopPK model using bootstrapping, goodness-of-fit plots, and prediction-corrected visual predictive checks. RESULTS: Six hundred and eight blood samples were obtained from 325 patients. In the final PopPK model, the CLCr and qSOFA scores were selected as covariates of systemic vancomycin clearance (p < 0.05): the population mean value was 2.8 (L/h). Regardless of the CLCr, a qSOFA score of greater than 1 was associated with an approximately 10% reduction in vancomycin clearance. CONCLUSIONS: qSOFA scores might be an additional covariate to CLCr for estimating vancomycin concentrations with a PopPK model in patients with malignancy.

Antimicrobial pharmacokinetics and dosing in critically ill adults receiving prolonged intermittent renal replacement therapy: A systematic review.

Prolonged intermittent renal replacement therapy (PIRRT) is gaining popularity as a renal replacement modality in intensive care units, but there is a relative lack of guidance regarding antimicrobial clearance and dosing when compared with other modalities. The objectives of this systematic review were to: (1) identify and describe the pharmacokinetics (PK) of relevant antimicrobials used in critically ill adults receiving PIRRT, (2) evaluate the quality of evidence supporting these data, and (3) propose dosing recommendations based on the synthesis of these data. A search strategy for multiple databases was designed and executed to identify relevant published evidence describing the PK of antimicrobials used in critically ill adults receiving PIRRT. Quality assessment, evaluation of reporting, and relevant data extraction were conducted in duplicate. Synthesis of PK/pharmacodynamic (PD) outcomes, dosing recommendations from study authors, and physicochemical properties of included antibiotics were assessed by investigators in addition to the quality of evidence to develop dosing recommendations. Thirty-nine studies enrolling 452 patients met criteria for inclusion and provided PK and/or PD data for 20 antimicrobials in critically ill adults receiving PIRRT. Nineteen studies describe both PK and PD outcomes. Vancomycin (12 studies, 171 patients), meropenem (7 studies, 84 patients), and piperacillin/tazobactam (5 studies, 56 patients) were the most frequent antimicrobials encountered. The quality of evidence was deemed strong for 7/20 antimicrobials, and strong dosing recommendations were determined for 9/20 antimicrobials. This systematic review updates and addresses issues of quality in previous systematic reviews on this topic. Despite an overall low quality of evidence, strong recommendations were able to be made for almost half of the identified antimicrobials. Knowledge gaps persist for many antimicrobials, and higher quality studies (i.e., population PK studies with assessment of PD target attainment) are needed to address these gaps.

Use of a common spreadsheet program to demonstrate the ability of Bayesian forecasting to estimate the pharmacokinetic parameters of antibiotics.

OBJECTIVES: Recent guidelines for vancomycin have incorporated the use of Bayesian forecasting, reinforcing the need to inform students in pharmacy and clinical pharmacology of its use in therapeutic drug monitoring. The goal was to devise a PharmD research project that could demonstrate to students through simulation and data generation the utility of the Bayesian approach in estimating the pharmacokinetics of gentamicin and vancomycin. METHODS: A series of steps were devised using Microsoft Excel to simulate patient data based on study-derived means and variances, pharmacokinetic modelling, random selection of sparse blood samples, introduce random error into the selected concentrations based on assay variability measure, and finally, inputting of the information into an add-in computer program to find the pharmacokinetic estimates using Bayesian forecasting. KEY FINDINGS: Excellent correlations were seen between Bayesian estimates and true clearances. Lower assay variability tended to provide better estimates than larger assay variability for gentamicin, and for vancomycin, selecting a sample during the distribution phase and near the trough values tended to provide estimates with less bias and greater precision. CONCLUSIONS: The approach used was able to demonstrate all aspects involved in Bayesian forecasting, and the results supported its use for these antibiotics.

External validation of population pharmacokinetic models of vancomycin in postoperative neurosurgical patients.

OBJECTIVE: Vancomycin is commonly used in the prevention and treatment of intracranial infections in postoperative neurosurgical patients with narrow therapeutic window and large pharmacokinetic variations. Several population pharmacokinetic (PPK) models of vancomycin have been established for neurosurgical patients. But comprehensive external evaluation has not been performed for almost all models. The objective of this study was to evaluate the predictive ability of published vancomycin PPK models in adult postoperative neurosurgical patients using an independent dataset. METHOD: PubMed, Embase and China National Knowledge Internet databases were searched to identify published vancomycin PPK models in adult postoperative neurosurgical patients. Prediction-based and simulation-based diagnostics were used to evaluate model predictability. Bayesian forecasting was used to assess the influence of prior concentration on model prediction performance. RESULT: A total of 763 vancomycin plasma concentrations from 493 postoperative neurosurgical patients were included in the external dataset. Eight population pharmacokinetic models of vancomycin in postoperative neurosurgical patients were included and evaluated. The model by Zhang et al. exhibited the best predictive performance in prediction-based diagnostics and prediction-corrected visual predictive checks, followed by the model by Shen et al. The predictive performance of other models was not satisfactory. The normalized predictive distribution error test shows that none of the models is suitable to describe our data. The predictive performance of vancomycin models was obviously improved by maximum a posteriori Bayesian forecasting. CONCLUSION: The published PPK models for adult postoperative neurosurgical patients show extensive variation in predictive performance in our patients. Although it is challenging to recommend initial doses of vancomycin from these predictive models, the combination of model-based prediction and therapeutic drug monitoring can be used for dose optimization.

Use of Machine Learning for Dosage Individualization of Vancomycin in Neonates.

BACKGROUND AND OBJECTIVE: High variability in vancomycin exposure in neonates requires advanced individualized dosing regimens. Achieving steady-state trough concentration (C0) and steady-state area-under-curve (AUC0-24) targets is important to optimize treatment. The objective was to evaluate whether machine learning (ML) can be used to predict these treatment targets to calculate optimal individual dosing regimens under intermittent administration conditions. METHODS: C0 were retrieved from a large neonatal vancomycin dataset. Individual estimates of AUC0-24 were obtained from Bayesian post hoc estimation. Various ML algorithms were used for model building to C0 and AUC0-24. An external dataset was used for predictive performance evaluation. RESULTS: Before starting treatment, C0 can be predicted a priori using the Catboost-based C0-ML model combined with dosing regimen and nine covariates. External validation results showed a 42.5% improvement in prediction accuracy by using the ML model compared with the population pharmacokinetic model. The virtual trial showed that using the ML optimized dose; 80.3% of the virtual neonates achieved the pharmacodynamic target (C0 in the range of 10-20 mg/L), much higher than the international standard dose (37.7-61.5%). Once therapeutic drug monitoring (TDM) measurements (C0) in patients have been obtained, AUC0-24 can be further predicted using the Catboost-based AUC-ML model combined with C0 and nine covariates. External validation results showed that the AUC-ML model can achieve an prediction accuracy of 80.3%. CONCLUSION: C0-based and AUC0-24-based ML models were developed accurately and precisely. These can be used for individual dose recommendations of vancomycin in neonates before treatment and dose revision after the first TDM result is obtained, respectively.

Comparison of the in vivo efficacy of ceftaroline fosamil, vancomycin and daptomycin in a murine model of methicillin-resistant Staphylococcus aureus bacteraemia.

The need for alternative drugs to treat methicillin-resistant Staphylococcus aureus (MRSA) bacteraemia has led to a focus on ceftaroline, for which clinical data remain scarce. Herein, the efficacy of ceftaroline fosamil for the treatment of experimental MRSA bacteraemia was compared with that of approved therapies. Five MRSA strains were tested in an immunocompetent BALB/c bacteraemia model. Serum pharmacokinetics of ceftaroline fosamil were determined using HPLC/MS Q-TOF. Two hours after infection with the MRSA strains, mice were administered 50 mg/kg of ceftaroline fosamil every 6 h, for 24 h. This regimen yielded a T>MIC of 61.5% for an MIC of 1 mg/L and proved efficacious against all strains, including an hVISA strain with non-susceptibility to daptomycin, as indicated by the reduction (mean ± s.d.) in log10 CFU/mL in blood of 2.34 ± 0.33 and log10 CFU/g in kidney of 2.08 ± 0.22. Similarly, treatment with daptomycin yielded a log reduction of 2.30 ± 0.60 in blood and 2.14 ± 0.31 in kidney. The decrease in bacterial density was less accentuated after treatment with vancomycin, which yielded 1.84 ± 0.73 and 1.95 ± 0.32 log reductions in blood and kidney, respectively. The results of the study showed that the efficacy of ceftaroline fosamil against MRSA bacteraemia in mice is not inferior to that of vancomycin and daptomycin, and indicated the potential use of ceftaroline fosamil against difficult-to-treat S. aureus bacteraemia. Considering these promising data, clinical trials should be conducted to ascertain the efficacy of the drug for treating bloodstream infections in humans.

Bayesian prediction-based individualized dosing of anti-methicillin-resistant Staphylococcus aureus treatment: Recent advancements and prospects in therapeutic drug monitoring.

As one of the efficient techniques for TDM, the population pharmacokinetic (popPK) model approach for dose individualization has been developed due to the rapidly growing innovative progress in computer technology and has recently been considered as a part of model-informed precision dosing (MIPD). Initial dose individualization and measurement followed by maximum a posteriori (MAP)-Bayesian prediction using a popPK model are the most classical and widely used approach among a class of MIPD strategies. MAP-Bayesian prediction offers the possibility of dose optimization based on measurement even before reaching a pharmacokinetically steady state, such as in an emergency, especially for infectious diseases requiring urgent antimicrobial treatment. As the pharmacokinetic processes in critically ill patients are affected and highly variable due to pathophysiological disturbances, the advantages offered by the popPK model approach make it highly recommended and required for effective and appropriate antimicrobial treatment. In this review, we focus on novel insights and beneficial aspects of the popPK model approach, especially in the treatment of infectious diseases with anti-methicillin-resistant Staphylococcus aureus agents represented by vancomycin, and discuss the recent advancements and prospects in TDM practice.

Plasma and Cerebrospinal Fluid Population Pharmacokinetics of Vancomycin in Patients with External Ventricular Drain.

Vancomycin is a commonly used antibacterial agent in patients with primary central nervous system (CNS) infection. This study aims to examine predictors of vancomycin penetration into cerebrospinal fluid (CSF) in patients with external ventricular drainage and the feasibility of CSF sampling from the distal drainage port for therapeutic drug monitoring. Fourteen adult patients (9 with primary CNS infection) were treated with vancomycin intravenously. The vancomycin concentrations in blood and CSF (from proximal [CSF_P] and distal [CSF_D] drainage ports) were evaluated by population pharmacokinetics. Model-based simulations were conducted to compare various infusion modes. A three-compartment model with first-order elimination best described the vancomycin data. Estimated parameters included clearance (CL, 4.53 L/h), central compartment volume (Vc, 24.0 L), apparent CSF compartment volume (VCSF, 0.445 L), and clearance between central and CSF compartments (QCSF, 0.00322 L/h and 0.00135 L/h for patients with and without primary CNS infection, respectively). Creatinine clearance was a significant covariate on vancomycin CL. CSF protein was the primary covariate to explain the variability of QCSF. There was no detectable difference between the data for sampling from the proximal and the distal port. Intermittent infusion and continuous infusion with a loading dose reached the CSF target concentration faster than continuous infusion only. All infusion schedules reached similar CSF trough concentrations. Beyond adjusting doses according to renal function, starting treatment with a loading dose in patients with primary CSF infection is recommended. Occasionally, very high and possibly toxic doses would be required to achieve adequate CSF concentrations, which calls for more investigation of direct intraventricular administration of vancomycin. (This study has been registered at ClinicalTrials.gov under registration no. NCT04426383).

Model-Informed Precision Dosing of Vancomycin in Adult Patients Undergoing Hemodialysis.

Model-informed precision dosing (MIPD) maximizes the probability of successful dosing in patients undergoing hemodialysis. In these patients, area under the concentration-time curve (AUC)-guided dosing is recommended for vancomycin. However, this model is yet to be developed. The purpose of this study was to address this issue. The overall mass transfer-area coefficient (KoA) was used for the estimation of vancomycin hemodialysis clearance. A population pharmacokinetic (popPK) model was developed, resulting in a fixed-effect parameter for nonhemodialysis clearance of 0.316 liters/h. This popPK model was externally evaluated, with a resulting mean absolute error of 13.4% and mean prediction error of -0.17%. KoA-predicted hemodialysis clearance was prospectively evaluated for vancomycin (n = 10) and meropenem (n = 10), with a correlation equation being obtained (slope of 1.099, intercept of 1.642; r = 0.927, P < 0.001). An experimental evaluation using an in vitro hemodialysis circuit validated the developed model of KoA-predicted hemodialysis clearance using vancomycin, meropenem, vitamin B6, and inulin in 12 hemodialysis settings. This popPK model indicated a maximum a priori dosing for vancomycin-a loading dose of 30 mg/kg, which achieves the target AUC for 24 h after first dose with a probability of 93.0%, ensured by a predialysis concentration of >15 µg/mL. Maintenance doses of 12 mg/kg after every hemodialysis session could achieve the required exposure, with a probability of 80.6%. In conclusion, this study demonstrated that KoA-predicted hemodialysis clearance may lead to an upgrade from conventional dosing to MIPD for vancomycin in patients undergoing hemodialysis.

In silico Evaluation of a Vancomycin Dosing Guideline Among Adults with Serious Infections.

BACKGROUND: This study aimed to compare the achievement of pharmacokinetic-pharmacodynamic (PK-PD) exposure targets for vancomycin using a newly developed dosing guideline with product-information-based dosing in the treatment of adult patients with serious infections. METHODS: In silico product-information- and guideline-based dosing simulations for vancomycin were performed across a range of doses and patient characteristics, including body weight, age, and renal function at 36-48 and 96 hours, using a pharmacokinetic model derived from a seriously ill patient population. The median simulated concentration and area under the 24-hour concentration-time curve (AUC 0-24 ) were used to measure predefined therapeutic, subtherapeutic, and toxicity PK-PD targets. RESULTS: Ninety-six dosing simulations were performed. The pooled median trough concentration target with guideline-based dosing at 36 and 96 hours was achieved in 27.1% (13/48) and 8.3% (7/48) of simulations, respectively. The pooled median AUC 0-24 /minimum inhibitory concentration ratio with guideline-based dosing at 48 and 96 hours was attained in 39.6% (19/48) and 27.1% (13/48) of simulations, respectively. Guideline-based dosing simulations yielded improved trough target attainment compared with product-information-based dosing at 36 hours and significantly less subtherapeutic drug exposure. The toxicity threshold was exceeded in 52.1% (25/48) and 0% (0/48) for guideline- and product-information-information-based dosing, respectively ( P < 0.001). CONCLUSIONS: A Critical care vancomycin dosing guideline appeared slightly more effective than standard dosing, as per product information, in achieving PK-PD exposure associated with an increased likelihood of effectiveness. In addition, this guideline significantly reduced the risk of subtherapeutic exposure. The risk of exceeding toxicity thresholds, however, was greater with the guideline, and further investigation is suggested to improve dosing accuracy and sensitivity.

Analytical and Non-Analytical Variation May Lead to Inappropriate Antimicrobial Dosing in Neonates: An In Silico Study.

BACKGROUND: Therapeutic drug monitoring (TDM) of aminoglycosides and vancomycin is used to prevent oto- and nephrotoxicity in neonates. Analytical and nonanalytical factors potentially influence dosing recommendations. This study aimed to determine the impact of analytical variation (imprecision and bias) and nonanalytical factors (accuracy of drug administration time, use of non-trough concentrations, biological variation, and dosing errors) on neonatal antimicrobial dosing recommendations. METHODS: Published population pharmacokinetic models and the Australasian Neonatal Medicines Formulary were used to simulate antimicrobial concentration-time profiles in a virtual neonate population. Laboratory quality assurance data were used to quantify analytical variation in antimicrobial measurement methods used in clinical practice. Guideline-informed dosing recommendations based on drug concentrations were applied to compare the impact of analytical variation and nonanalytical factors on antimicrobial dosing. RESULTS: Analytical variation caused differences in subsequent guideline-informed dosing recommendations in 9.3-12.1% (amikacin), 16.2-19.0% (tobramycin), 12.2-45.8% (gentamicin), and 9.6-19.5% (vancomycin) of neonates. For vancomycin, inaccuracies in drug administration time (45.6%), use of non-trough concentrations (44.7%), within-subject biological variation (38.2%), and dosing errors (27.5%) were predicted to result in more dosing discrepancies than analytical variation (12.5%). Using current analytical performance specifications, tolerated dosing discrepancies would be up to 14.8% (aminoglycosides) and 23.7% (vancomycin). CONCLUSIONS: Although analytical variation can influence neonatal antimicrobial dosing recommendations, nonanalytical factors are more influential. These result in substantial variation in subsequent dosing of antimicrobials, risking inadvertent under- or overexposure. Harmonization of measurement methods and improved patient management systems may reduce the impact of analytical and nonanalytical factors on neonatal antimicrobial dosing.

Correlation of Calculated Vancomycin Trough Concentrations and Exposure: A Monte Carlo Simulation.

BACKGROUND: Current recommendations are to dose vancomycin to target 24-hour area under the curve (AUC) of 400-600 mg·h/L to optimize efficacy and safety. Limited data support AUC monitoring, and some centers continue to use trough concentrations. A target of 10-20 mg/L has been proposed to reduce nephrotoxicity risk. OBJECTIVE: To use previously published pharmacokinetic equations in a Monte Carlo simulation relating AUC exposure to trough concentrations when targeting an AUC between 400 and 600 mg·h/L. METHODS: Previously published pharmacokinetic data were used as input parameters for a Monte Carlo simulation using previously published formulae to correlate AUC to simulated trough concentrations. Pharmacokinetic parameters were assumed to occur in a normal distribution pattern. We excluded irrelevant simulated cases. Maintenance doses of 15 mg/kg were rounded to the nearest 250 mg. Calculated trough concentrations for AUCs of both 400 and 600 mg·h/L were evaluated in each simulation. RESULTS: A total of 10 000 Monte Carlo simulations were performed. Targeting an AUC of 400 mg·h/L resulted in a mean trough concentration of 10.3 ± 0.8 mg/L. Targeting an AUC of 600 mg·h/L resulted in a mean trough concentration of 15.4 ± 1.2 mg/L. CONCLUSION AND RELEVANCE: We demonstrate that a lower trough concentration range may be supported by an AUC of 400-600 mg·h/L, which may reduce risk and rates of nephrotoxicity without compromising previously established efficacious target trough concentrations.

Population Pharmacokinetics of Vancomycin in Patients Receiving Hemodialysis in a Malian and a French Center and Simulation of the Optimal Loading Dose.

PURPOSE: Vancomycin dosing remains challenging in patients receiving intermittent hemodialysis, especially in developing countries, where access to therapeutic drug monitoring and model-based dose adjustment services is limited. The objectives of this study were to describe vancomycin population PK in patients receiving hemodialysis in a Malian and French center and examine the optimal loading dose of vancomycin in this setting. METHODS: Population pharmacokinetic analysis was conducted using Pmetrics in 31 Malian and 27 French hemodialysis patients, having a total of 309 vancomycin plasma concentrations. Structural and covariate analyses were based on goodness-of-fit criteria. The final model was used to perform simulations of the vancomycin loading dose, targeting a daily area under the concentration-time curve (AUC) of 400-600 mg.h/L or trough concentration of 15-20 mg/L at 48 hours. RESULTS: After 48 hours of therapy, 68% of Malian and 63% of French patients exhibited a daily AUC of <400. The final model was a 2-compartment model, with hemodialysis influencing vancomycin elimination and age influencing the vancomycin volume distribution. Younger Malian patients exhibited a lower distribution volume than French patients. Dosing simulation suggested that loading doses of 1500, 2000, and 2500 mg would be required to minimize underexposure in patients aged 30, 50, and 70 years, respectively. CONCLUSIONS: In this study, a low AUC was frequently observed in hemodialysis patients in Mali and France after a standard vancomycin loading dose. A larger dose is necessary to achieve the currently recommended AUC target. However, the proposed dosing algorithm requires further clinical evaluation.