Amikacin Initial Dose in Critically Ill Patients: a Nonparametric Approach To Optimize A Priori Pharmacokinetic/Pharmacodynamic Target Attainments in Individual Patients

Comparative assessment of trough and peak levels and AUC24 for amikacin in nontuberculous mycobacterial infection

BACKGROUND

Amikacin, an aminoglycoside antibiotic, is widely used for the treatment of nontuberculous mycobacterial (NTM) infections. To date, therapeutic drug monitoring (TDM) of amikacin has primarily relied on the measurement of peak and trough levels as indicators rather than the 24-hr area under the concentration-time curve (AUC24).

METHODS

NTM patients referred for amikacin TDM from March 2021 to May 2023 were assessed for the AUC24 values based on administered dose. We investigated re-admission rates, all-cause mortality and AFB smear results to evaluate clinical outcome based on the actual AUC24 values. Ototoxicity and nephrotoxicity were also investigated as adverse effects in correlation with TDM parameters.

RESULTS

Among 65 patients, the mean and median values of AUC24 were 234 and 249 mg·hr/L, respectively. In a group of patients with AUC24 values less than 250 mg·hr/L, 42.4 % of patients were re-admitted for pulmonary symptoms. On the contrary, another group with AUC24 values equal to or more than 250 mg·hr/L, had lower re-admission rates (25.0 %). They also showed lower all-cause mortality rates and more improvement on acid-fast bacilli smear results. Moderate to poor correlation between AUC24 values and peak/trough levels were observed. Ototoxicity and nephrotoxicity were revealed to be associated with drug exposure duration rather than AUC24 values.

CONCLUSION

In this study, we performed comparative assessment of trough/peak level, traditional clinical marker for amikacin TDM, and AUC24 value. Although AUC24 values showed poor to moderate correlation to trough/peak levels, higher AUC24 correlated with favorable clinical outcomes without additional risk of toxicity.

Amikacin therapeutic drug monitoring: Evaluation of therapy performance and analytical techniques in a developing country setting

INTRODUCTION

Healthcare systems face several challenges, with microbial infections being one of the main concerns. Therapeutic drug monitoring (TDM) is a strategy that has been encouraged to optimize antimicrobial regimens, particularly those with significant toxicity and narrow therapeutic indices, such as amikacin (AMK). We aimed to evaluate AMK concentrations of patients in a non-routine TDM setting and compare the performance of immunoassay and chromatography methods for routine clinical use.

MATERIAL AND METHODS

In this prospective study, peak (Cmax) and trough (Cmin) plasma samples were collected from 39 adult patients and quantified by ultra-performance liquid chromatography coupled with mass spectrometry (UPLC-MS/MS). Relevant clinical information was collected from medical records. AMK concentrations and clinical data were analyzed to evaluate therapy performance and influencing factors. In addition, fluorescence polarized immunoassay (FPIA) and UPLC-MS/MS were compared with Passing-Bablok regression and Bland-Altman plot analysis.

RESULTS

AMK concentrations varied widely, with a median Cmax of 41.40 µg/mL (interquartile range [IQR] 27.60 - 56.75 µg/mL) and a median Cmin of 1.87 µg/mL (IQR 0.7 - 6.19 µg/mL). A high proportion of patients (83.1 %) failed to achieve the Cmax therapeutic target, while 31.7 % failed to achieve the Cmin therapeutic target. Overall, elderly patients and those with reduced renal function had higher Cmax target attainment, while the same groups had lower Cmin target attainment. The method comparison showed a mean difference of 1.54 % (limits of agreement -42.46 % to 45.54 %) in measured concentrations, with good correlation and no constant or proportional differences.

CONCLUSION

Many patients failed to reach the Cmax target and were at risk of treatment failure, although adequate Cmin was achieved more often. TDM with dose adjustments could improve AMK therapy, but further research is needed.

Monte Carlo simulation for dosage optimization of the best available therapy for bloodstream infections secondary to carbapenemase-producing Klebsiella pneumoniae in critically ill patients

OBJECTIVE

We aimed to use Monte Carlo simulation, based on pharmacokinetic/pharmacodynamic targets, to investigate and determine the optimal dosage of the available combination therapies for carbapenem-resistant Klebsiella pneumoniae (CRKP) in critically ill patients.

METHODS

We collected CRKP clinical isolates from Phramongkutklao Hospital between October 2020 and June 2022. A molecular study of resistant genes was performed using polymerase chain reaction. Broth microdilution checkerboards were used to evaluate the mono- and synergistic antibiotic activities. Monte Carlo simulation was used to determine the optimal antibiotic regimens, based on the probability of target attainment (PTA) and cumulative fraction of response.

RESULTS

The 54 CRKP isolates were resistant to tigecycline (100%), colistin (75.9%), amikacin (70.4%), and gentamicin (63.0%). The most common carbapenemase genotype was blaoxacillinases (OXA)-48-like (42.6%), followed by blaNew Delhi metallo beta-lactamase (NDM) (29.6%) and coexistence of blaOXA-48-like and blaNDM (22.2%). Based on the PTA, synergistic and additive activities against CRKP isolates were observed with appropriate dosages of tigecycline-colistin (67.9%), tigecycline-gentamicin (62.2%), and tigecycline-amikacin (51.4%).

CONCLUSIONS

Tigecycline-colistin was the best available combination therapy for critically ill patients with CRKP, especially NDM. When used in combination with tigecycline, a colistin creatinine clearance of <90 mL/min can raise the cumulative fraction of response target and less nephrotoxicity.

Therapeutic Drug Monitoring of Amikacin in Neutropenic Oncology Patients

Amikacin is the antibiotic of choice for the treatment of Gram-negative infections, namely, those in neutropenic oncology patients. No populational pharmacokinetic studies are currently available reporting amikacin pharmacokinetics in neutropenic oncology patients despite their specific pathophysiological features and treatments. A large-scale retrospective study was herein conducted to specifically investigate the effects that tumor diseases have on the pharmacokinetic parameters of amikacin and identify whether chemotherapy, the lag time between administration of chemotherapy and amikacin, age and renal function contribute to amikacin pharmacokinetics in neutropenic cancer patients. A total of 1180 pharmacokinetic analysis from 629 neutropenic patients were enrolled. The daily dose administered to oncology patients was higher than that administered to non-oncology patients (p < 0.0001). No statistical differences were found in amikacin concentrations, probably because drug clearance was increased in cancer patients (p < 0.0001). Chemotherapy influenced amikacin pharmacokinetics and drug clearance decreased as the lag time enhanced. The elderly group revealed no statistical differences between the doses administered to both the oncology groups, suggesting that the impact of ageing is stronger than chemotherapy. Our research suggests that cancer patients require higher initial doses of amikacin, as well as when chemotherapy is received less than 30 days before amikacin treatment has started.

Amikacin pharmacokinetics in elderly patients with severe infections

OBJECTIVE

The aim of this study was to characterize the population pharmacokinetics of amikacin in elderly patients by means of nonlinear mixed effects modelling and to propose initial dosing schemes to optimize therapy based on PK/PD targets.

METHOD

A total of 137 elderly patients from 65 to 94 years receiving intravenous amikacin and routine therapeutic drug monitoring at Hospital Universitario Severo Ochoa were included. Concentration-time data and clinical information were retrospectively collected; initial doses of amikacin ranged from 5.7 to 22.5 mg/kg/day and each patient provided between 1 and 10 samples.

RESULTS

Amikacin pharmacokinetics were best described by a two-compartment open model; creatinine clearance (CrCL) was related to drug clearance (2.75 L/h/80 mL/min) and it was augmented 28% when non-steroidal anti-inflammatory drugs were concomitantly administered. Body mass index (BMI) influenced the central volume of distribution (17.4 L/25 kg/m²). Relative absolute prediction error was reduced from 33.2% (base model) to 17.9% (final model) when predictive performance was evaluated with a different group of elderly patients. A nomogram for initial amikacin dosage was developed and evaluated based on stochastic simulations considering final model to achieve PK/PD targets (Cmax/MIC>10 and AUC/MIC>75) and to avoid toxic threshold (Cmin<2.5 mg/L).

CONCLUSION

Initial dosing approach for amikacin was designed for elderly patients based on nonlinear mixed effects modeling to maximize the probability to attain efficacy and safety targets considering individual BMI and CrCL.

Evaluation of amikacin dosing schedule in critically ill elderly patients with different stages of renal dysfunction

OBJECTIVES

Amikacin is still a widely used aminoglycoside for the treatment of life-threatening infections. The pharmacokinetic parameters of this antibiotic may be altered in critically ill conditions. Moreover, in the elderly population, pathophysiological changes affect these pharmacokinetic variables, making it difficult to predict the appropriate dose and dosing schedule for amikacin. This study aimed to characterise the pharmacokinetics of amikacin in critically ill elderly patients with renal dysfunction, and to evaluate if the available dose adjustment schedules dependent on renal function would be appropriate for empirical dosing.

METHODS

Critically ill patients aged >60 years with a creatinine clearance of >20 mL/min in need of treatment with amikacin were randomly enrolled. All the patients received approximately 25 mg/kg amikacin. The patients were then divided into three groups according to the stages of their renal dysfunction based on creatinine clearance, and the optimum time to re-dosing was calculated for each group. The pharmacokinetic parameters of the patients were calculated and estimated as population pharmacokinetic data.

RESULTS

Of 30 patients, only 20% attained the target peak levels of amikacin of >64 mg/L. In addition, the mean volume of distribution was 0.47 L/kg. There was a poor correlation between amikacin clearance and creatinine clearance. The difference in amikacin half-life was not statistically significant among any of the stages of renal impairment.

CONCLUSIONS

The initial dosing of amikacin in critically ill elderly patients should not be reduced, even in the context of renal impairment. Regarding the dose adjustment in renal impairment, dosing intervals estimation, no decision can be made based on the creatinine clearance and the first dose individualisation method in terms of the two-sample measurements may be considered as an appropriate strategy.

Population Pharmacokinetics of Amikacin in Patients on Veno-Arterial Extracorporeal Membrane Oxygenation

Veno-arterial extracorporeal membrane oxygenation (V-A ECMO) support leads to complex pharmacokinetic alterations, whereas adequate drug dosing is paramount for efficacy and absence of toxicity in critically ill patients. Amikacin is a major antibiotic used in nosocomial sepsis, especially for these patients. We aimed to describe amikacin pharmacokinetics on V-A ECMO support and to determine relevant variables to improve its dosing. All critically ill patients requiring empirical antimicrobial therapy, including amikacin for nosocomial sepsis supported or not by V-A ECMO, were included in a prospective population pharmacokinetic study. This population pharmacokinetic analysis was built with a dedicated software, and Monte Carlo simulations were performed to identify doses achieving therapeutic plasma concentrations. Thirty-nine patients were included (control n = 15, V-A ECMO n = 24); 215 plasma assays were performed and used for the modeling process. Patients received 29 (24–33) and 32 (30–35) mg/kg of amikacin in control and ECMO groups, respectively. Data were best described by a two-compartment model with first-order elimination. Inter-individual variabilities were observed on clearance, central compartment volume (V₁)_, and peripherical compartment volume (V₂). Three significant covariates explained these variabilities: Kidney Disease Improving Global Outcomes (KDIGO) stage on amikacin clearance, total body weight on V_1, and ECMO support on V₂. Our simulations showed that the adequate dosage of amikacin was 40 mg/kg in KDIGO stage 0 patients, while 25 mg/kg in KDIGO stage 3 patients was relevant. V-A ECMO support had only a secondary impact on amikacin pharmacokinetics, as compared to acute kidney injury.

Cefepime precision dosing tool: From Standard to Precise Dose Using Nonparametric Population Pharmacokinetics

Cefepime is the second most common cephalosporin used in U.S. hospitals. We aim to develop and validate cefepime population pharmacokinetic (PK) model and integrate into precision dosing tool for implementation. Two datasets (680 patients) were used to build cefepime PK model in Pmetrics, and three datasets (34 patients) were used for the validation. A separate application dataset (115 patients) was used for the implementation and validation of a precision dosing tool. The model support points and covariates were used to generate the optimal initial dose (OID). Cefepime PK was described by a two-compartment model including weight and creatinine clearance (CrCl) as covariates. The median rate of elimination was 0.30 hr^-1 (adults) and 0.96 hr^-1 (pediatrics), central volume of distribution 13.85 L, and rate of transfer from the central to the peripheral compartments 1.22 hr^-1 and from the peripheral to the central compartments 1.38 hr^-1. After integration in BestDose, the observed vs. predicted cefepime concentration fit using the application dataset was excellent (R²>0.98) and the median difference between observed and what BestDose predicted in a second occasion was 4%. For OID, cefepime 0.5-1g 4-hour infusion q8-24hr with CrCl<70 mL/min was needed to achieve a target range of free trough:MIC 1-4 at MIC 8 mg/L, while continuous infusion was needed for higher CrCl and weight values. In conclusion, we developed and validated a cefepime model for clinical application. The model was integrated in a precision dosing tool for implementation and the median concentration prediction bias was 4%. OID algorithm was provided.

Amikacin in emergency surgery: How to dose it optimally?

Amikacin is still a recommended option in emergency surgery. Current guidelines have suggested an amikacin dose of 15-20 mg/kg/24 h for intra-abdominal infections (IAI). Our objectives were to analyse amikacin pharmacokinetics (PK) and dosage requirements in patients who underwent emergency surgery, and to identify an optimal dosing approach. We performed a retrospective data analysis of patients who received amikacin for emergency surgery over 2.5 years, with measurement of both peak (C_max) and trough (C_min) concentration after the first dose. The BestDose software was used to analyse amikacin concentrations and simulate various alternative dosage regimens in each patient. We compared concentration estimates with target values: C_max > 64 mg/L and C_min < 2.5 mg/L at 24 h. Classification and regression tree analysis was used to identify determinants of C_max target attainment (TA) and optimal dose. Data from 84 patients, including 62 with IAI, were analysed. Despite a median initial dose of 25 mg/kg, 32% of patients did not achieve the C_max target. An amikacin dose ≤ 21.5 mg/kg was the primary predictor of failure to achieve the target. A dose of 30 mg kg of total or corrected body weight, as well as a fixed dose of 2500 mg would result in the highest TA. The primary determinants of the optimal dose were ideal body weight, age, and renal function. To conclude, recommended dosages of amikacin in emergency surgery are not optimal. A fixed initial dose of 2500 mg could simplify and optimise dosing in this setting.

Parametric and Nonparametric Methods in Population Pharmacokinetics: Experts' Discussion on Use, Strengths, and Limitations

Population pharmacokinetics consists of analyzing pharmacokinetic (PK) data collected in groups of individuals. Population PK is widely used to guide drug development and to inform dose adjustment via therapeutic drug monitoring and model-informed precision dosing. There are 2 main types of population PK methods: parametric (P) and nonparametric (NP). The characteristics of P and NP population methods have been previously reviewed. The aim of this article is to answer some frequently asked questions that are often raised by scholars, clinicians, and researchers about P and NP population PK methods. The strengths and limitations of both approaches are explained, and the characteristics of the main software programs are presented. We also review the results of studies that compared the results of both approaches in the analysis of real data. This opinion article may be informative for potential users of population methods in PK and guide them in the selection and use of those tools. It also provides insights on future research in this area.

Quantification and Explanation of the Variability of First-Dose Amikacin Concentrations in Critically Ill Patients Admitted to the Emergency Department: A Population Pharmacokinetic Analysis

BACKGROUND

There may be a difference between the determinants of amikacin exposure in emergency department (ED) versus intensive care (ICU) patients, and the peak amikacin concentration varies widely between patients. Moreover, when the first dose of antimicrobials is administered to septic patients admitted to the ED, fluid resuscitation and vasopressors have just been initiated. Nevertheless, population pharmacokinetic modelling data for amikacin in ED patients are unavailable.

OBJECTIVE

The aim of this study was to quantify the interindividual variability (IIV) in the pharmacokinetics of amikacin in patients admitted to the ED and to identify the patient characteristics that explain this IIV.

METHODS

Patients presenting at the ED with severe sepsis or septic shock were randomly assigned to receive amikacin 25 mg/kg or 15 mg/kg intravenously. Blood samples were collected at 1, 6 and 24 h after the onset of the first amikacin infusion. Data were analysed using nonlinear mixed-effects modelling.

RESULTS

A two-compartment population pharmacokinetic model was developed based on 279 amikacin concentrations from 97 patients. The IIV in clearance (CL) and central distribution volume (V₁) were 71% and 26%, respectively. Body mass index (BMI), serum total protein level, serum sodium level, and fluid balance 24 h after amikacin administration explained 30% of the IIV in V₁, leaving 18% of the IIV unexplained. BMI and creatinine clearance according to the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation 24 h after amikacin administration explained 46% of the IIV in CL, and 39% remained unexplained.

CONCLUSION

The IIV of amikacin pharmacokinetics in ED patients is large. Higher doses may be considered in patients with low serum sodium levels, low total protein levels, or a high fluid balance.

TRIAL REGISTRATION

ClinicalTrials.gov ID: NCT02365272.

Population pharmacokinetic modeling and dosing simulations of tobramycin in pediatric patients with cystic fibrosis

Initial dosing and dose adjustment of intravenous tobramycin in cystic fibrosis children is challenging. The objectives of this study were to develop nonparametric population pharmacokinetic (PK) models of tobramycin in children with CF to be used for dosage design and model-guided therapeutic drug monitoring. We performed a retrospective analysis of tobramycin PK data in our CF children center. The Pmetrics package was used for nonparametric population PK analysis and dosing simulations. Both the maximal concentration over the MIC (Cmax/MIC) and daily area under the concentration-time curve to the MIC (AUC₂₄/MIC) ratios were considered as efficacy target. Trough concentration (Cmin) was considered as the safety target. A total of 2884 tobramycin concentrations collected in 195 patients over 9 years were analyzed. A two-compartment model including total body weight, body surface area and creatinine clearance as covariates best described the data. A simpler model was also derived for implementation into the BestDose software to perform Bayesian dose adjustment. Both models were externally validated. PK/PD simulations with the final model suggest that an initial dose of tobramycin of 15 to 17.5 mg/kg/day was necessary to achieve Cmax/MIC ≥ 10 values for MIC values up to 2 mg/L in most patients. The AUC₂₄/MIC target was associated with larger dosage requirements and higher Cmin. A daily dose of 12.5 mg/kg would optimize both efficacy and safety target attainment. We recommend to perform tobramycin TDM, model-based dose adjustment, and MIC determination to individualize intravenous tobramycin therapy in children with CF.

Aminoglycosides in the Intensive Care Unit: What Is New in Population PK Modeling?

Background: Although aminoglycosides are often used as treatment for Gram-negative infections, optimal dosing regimens remain unclear, especially in ICU patients. This is due to a large between- and within-subject variability in the aminoglycoside pharmacokinetics in this population. Objective: This review provides comprehensive data on the pharmacokinetics of aminoglycosides in patients hospitalized in the ICU by summarizing all published PopPK models in ICU patients for amikacin, gentamicin, and tobramycin. The objective was to determine the presence of a consensus on the structural model used, significant covariates included, and therapeutic targets considered during dosing regimen simulations. Method: A literature search was conducted in the Medline/PubMed database, using the terms: ‘amikacin’, ‘gentamicin’, ‘tobramycin’, ‘pharmacokinetic(s)’, ‘nonlinear mixed effect’, ‘population’, ‘intensive care’, and ‘critically ill’. Results: Nineteen articles were retained where amikacin, gentamicin, and tobramycin pharmacokinetics were described in six, 11, and five models, respectively. A two-compartment model was used to describe amikacin and tobramycin pharmacokinetics, whereas a one-compartment model majorly described gentamicin pharmacokinetics. The most recurrent significant covariates were renal clearance and bodyweight. Across all aminoglycosides, mean interindividual variability in clearance and volume of distribution were 41.6% and 22.0%, respectively. A common consensus for an optimal dosing regimen for each aminoglycoside was not reached. Conclusions: This review showed models developed for amikacin, from 2015 until now, and for gentamicin and tobramycin from the past decades. Despite the growing challenges of external evaluation, the latter should be more considered during model development. Further research including new covariates, additional simulated dosing regimens, and external validation should be considered to better understand aminoglycoside pharmacokinetics in ICU patients.

Population Pharmacokinetics Analysis of Amikacin Initial Dosing Regimen in Elderly Patients

There are limited data of amikacin pharmacokinetics (PK) in the elderly population. Hence, we aimed to describe the population PK of amikacin in elderly patients (>70 years old) and to establish optimized initial dosing regimens. We simulated individual maximum concentrations in plasma (Cmax) and minimal concentrations (Cmin) for several dosing regimens (200–2000 mg every 24, 48, and 72 h) for patients with creatinine clearance (CCr) of 10–90 mL/min and analyzed efficacy (Cmax/minimal inhibitory concentration (MIC) ≥ 8) for MICs of 4, 8, and 16 mg/L and safety (Cmin < 4 mg/L). A one-compartment model best described the data. CCr was the only covariate associated with amikacin clearance. The population PK parameter estimates were 2.25 L/h for clearance and 18.0 L for volume of distribution. Dosing simulations recommended the dosing regimens (1800 mg) with dosing intervals ranging 48–72 h for patients with CCr of 40–90 mL/min based on achievement of both efficacy for the MIC of 8 mg/L and safety. None of the dosing regimens achieved the targets for an MIC of 16 mg/L. We recommend the initial dosing regimen using a nomogram based on CCr for an MIC of ≤8 mg/L in elderly patients with CCr of 40–90 mL/min.

Aminoglycosides in critically ill patients: which dosing regimens for which pathogens?

Modifications of antibiotic pharmacokinetic parameters have been reported in critically ill patients, resulting in a risk of treatment failure. We aimed to determine optimised amikacin (AMK), gentamicin (GEN) and tobramycin (TOB) intravenous dosing regimens in this patient population. Patients admitted to the medical ICU and treated with AMK, GEN or TOB were included. Analyses were performed using a parametric population approach. Monte Carlo simulations were performed and the probability of target attainment (PTA) was calculated using C_max/MIC ≥ 8 and trough concentrations as targets. A total of 117 critically ill hospitalised patients were studied. Median values (interindividual variability, ɷ²) of clearance were 3.51 (0.539), 3.53 (0.297), 2.70 (0.339) and 5.07 (0.339) L/h for AMK, GEN, TOB, and TOB in cystic fibrosis (CF), respectively. Median values (ɷ²) of central volume of distribution were 30.2 (0.215), 20.0 (0.109) and 25.6 (0.177) L for AMK, GEN and TOB, respectively. Simulations showed that doses should be adjusted to actual body weight and creatinine clearance (CLCR) for AMK and GEN, and according to CLCR and presence of CF for TOB. In conclusion, our recommendations for treating Pseudomonas aeruginosa infections in this population include using initial doses of 35 mg/kg for AMK or 10 mg/kg for TOB (CF and non-CF patients). GEN demonstrated the best rates of target attainment against Staphylococcus aureus infections with a dose of 5 mg/kg. As high aminoglycoside doses are required in this population, efficacy and safety targets are conflicting and therapeutic drug monitoring remains an important tool to manage this issue.

Population Pharmacokinetics of Amikacin Administered Once Daily in Patients with Different Renal Functions

The aim of this work was to evaluate the pharmacokinetics of amikacin in Mexican patients with different renal functions receiving once-daily dosing regimens and the influence of clinical and demographical covariates that may influence the optimization of this antibiotic. A prospective study was performed in a total of 63 patients with at least one determination of amikacin plasma concentration. Population pharmacokinetic (PK) parameters were estimated by nonlinear mixed-effects modeling; validations were performed for dosing recommendation purposes based on PK/pharmacodynamic simulations. The concentration-versus-time data were best described by a one-compartment open model with proportional interindividual variability associated with amikacin clearance (CL) and volume of distribution (V); residual error followed a homoscedastic trend. Creatinine clearance (CL_CR) and ideal body weight (IBW) demonstrated significant influence on amikacin CL and V, respectively. The final model [CL (liters/h) = 7.1 × (CL_CR/130)^0.84 and V (liters) = 20.3 × (IBW/68)^2.9] showed a mean prediction error of 0.11 mg/liter (95% confidence interval, -3.34, 3.55) in the validation performed in a different group of patients with similar characteristics. There is a wide variability in amikacin PK parameters in Mexican patients. This leads to inadequate dosing regimens, especially in patients with augmented renal clearance (CL_CR of >130 ml/min). Optimization based on the final population PK model in Mexican patients may be useful, since reliability and clinical applicability have been demonstrated in this study.

Population Pharmacokinetic Study of the Suitability of Standard Dosing Regimens of Amikacin in Critically Ill Patients with Open-Abdomen and Negative-Pressure Wound Therapy

The aim was to assess the appropriateness of recommended regimens for empirical MIC coverage in critically ill patients with open-abdomen and negative-pressure therapy (OA/NPT). Over a 5-year period, every critically ill patient who received amikacin and who underwent therapeutic drug monitoring (TDM) while being treated by OA/NPT was retrospectively included. A population pharmacokinetic (PK) modeling was performed considering the effect of 10 covariates (age, sex, total body weight [TBW], adapted body weight [ABW], body surface area [BSA], modified sepsis-related organ failure assessment [SOFA] score, vasopressor use, creatinine clearance [CL_CR], fluid balance, and amount of fluids collected by the NPT over the sampling day) in patients who underwent continuous renal replacement therapy (CRRT) or did not receive CRRT. Monte Carlo simulations were employed to determine the fractional target attainment (FTA) for the PK/pharmacodynamic [PD] targets (maximum concentration of drug [C _max]/MIC ratio of ≥8 and a ratio of the area under the concentration-time curve from 0 to 24 h [AUC_0-24]/MIC of ≥75). Seventy critically ill patients treated by OA/NPT (contributing 179 concentration values) were included. Amikacin PK concentrations were best described by a two-compartment model with linear elimination and proportional residual error, with CL_CR and ABW as significant covariates for volume of distribution (V) and CL_CR for CL. The reported V) in non-CRRT and CRRT patients was 35.8 and 40.2 liters, respectively. In Monte Carlo simulations, ABW-adjusted doses between 25 and 35 mg/kg were needed to reach an FTA of >85% for various renal functions. Despite an increased V and a wide interindividual variability, desirable PK/PD targets may be achieved using an ABW-based loading dose of 25 to 30 mg/kg. When less susceptible pathogens are targeted, higher dosing regimens are probably needed in patients with augmented renal clearance (ARC). Further studies are needed to assess the effect of OA/NPT on the PK parameters of antimicrobial agents.