Therapeutic Drug Monitoring of Gentamicin Peak Concentrations in Critically Ill Patients

Appropriateness of gentamicin therapeutic drug monitoring at a Middle Eastern tertiary hospital setting: a retrospective evaluation and quality audit

Introduction

The use of gentamicin in the treatment of infectious diseases requires frequent monitoring to attain the best treatment outcomes.

Objective

This study aimed to evaluate the appropriateness of gentamicin therapeutic drug monitoring (TDM) at a tertiary care hospital in Qatar.

Methods

A one-year quantitative retrospective chart review of all gentamicin TDM records was conducted. Evidence-based criteria were applied to evaluate the appropriateness of gentamicin TDM in terms of indication, sampling times, and post-analytical actions.

Results

Out of 59 captured gentamicin TDM records, 58 gentamicin samples were eligible for evaluation. Overall, gentamicin TDM appropriateness was achieved in 50% (n = 29) of the evaluated records. However, 12% (n = 7) of gentamicin drug concentrations were below the assay quantification limits or were not sampled appropriately. Inappropriate post-analytical actions (22.4%, n = 13) and inappropriate sampling times (44.8%, n = 26) were recorded. Most of the gentamicin blood samples (n = 43; 74.2%) were taken appropriately at steady-state. Inappropriate sampling time relative to the last dose was captured in 31% (n = 18) of the cases. Although 27.6% (n = 16) of gentamicin concentrations were non-therapeutic, continuing gentamicin dosing without adjustment was the most frequent post-analytical action (69.8%, n = 37). Gentamicin dose regimen continuations, dose regimen decreases and dose regimen discontinuations were inappropriately applied in 27% (n = 10), 25% (n = 2) and 14% (n = 1) of the times, respectively.

Conclusion

Suboptimal gentamicin TDM practices exist in relation to sampling time and post-analytical actions. Studies exploring setting-specific reasons behind inappropriate TDM practices and methods of its optimisation are needed.

Nlmixr2 Versus NONMEM: An Evaluation of Maximum A Posteriori Bayesian Estimates Following External Evaluation of Gentamicin and Tobramycin Population Pharmacokinetic Models

The objective of this project is to compare the results of the same study carried out on NONMEM and nlmixr2. This analysis consists of evaluating previously published population pharmacokinetic models of gentamicin and tobramycin in our population of interest with sparse concentrations. A literature review was performed to determine the gentamicin and tobramycin models in critically ill adult patients. In parallel, gentamicin and tobramycin dosing data, information on the treatment, the patient, and the bacteria were collected retrospectively in 2 Quebec establishments. The external evaluations were previously performed using NONMEM Version 7.5. Model equations were rewritten with R, and external evaluations were performed using nlmixr2. Predictive performance was assessed based on the estimation of bias and imprecision of the prediction error for maximum a posteriori (MAP) Bayesian PK parameter and observed concentrations. Comparison between nlmixr2 and NONMEM was performed on 4 gentamicin and 3 tobramycin population pharmacokinetic models. Compared to NONMEM, for gentamicin and tobramycin clearance and central volume of distribution, nlmixr2 produced individual pharmacokinetic parameters with bias values ranging from -32.5% to 5.67% and imprecision values ranging from 6.33% to 32.5%. Despite these differences, population bias and imprecision for sparse concentrations were low and ranged from 0% to 5.3% and 0.2% to 6.5%, respectively. The external evaluations performed with both software packages resulted in the same interpretation in terms of population predictive performance for all 7 models. Nlmxir2 showed comparable predictive performance with NONMEM with sparse concentrations that are, at most, sampled twice within a single dose administration (peak and trough).

Hemoperfusion with Seraph 100 Microbind Affinity Blood Filter Unlikely to Require Increased Antibiotic Dosing: A Simulations Study Using a Pharmacokinetic/Pharmacodynamic Approach

INTRODUCTION

The Seraph® 100 Microbind® Affinity Blood Filter (Seraph 100) is a hemoperfusion device that can remove pathogens from central circulation. However, the effect of Seraph 100 on achieving pharmacodynamic (PD) targets is not well described. We sought to determine the impact of Seraph 100 on ability to achieve PD targets for commonly used antibiotics.

METHODS

Estimates of Seraph 100 antibiotic clearance were obtained via literature. For vancomycin and gentamicin, published pharmacokinetic models were used to explore the effect of Seraph 100 on ability to achieve probability of target attainment (PTA). For meropenem and imipenem, the reported effect of continuous kidney replacement therapy (CKRT) on achieving PTA was used to extrapolate decisions for Seraph 100.

RESULTS

Seraph 100 antibiotic clearance is likely less than 0.5 L/h for most antibiotics. Theoretical Seraph 100 clearance up to 0.5 L/h and 2 L/h had a negligible effect on vancomycin PTA in virtual patients with creatinine clearance (CrCl) = 14 mL/min and CrCl >14 mL/min, respectively. Theoretical Seraph 100 clearance up to 0.5 L/h and 2 L/h had a negligible effect on gentamicin PTA in virtual patients with CrCl = 120 mL/min and CrCl <60 mL/min, respectively. CKRT intensity resulting in antibiotic clearance up to 2 L/h generally does not require dose increases for meropenem or imipenem. As Seraph 100 is prescribed intermittently and likely contributes far less to antibiotic clearance, dose increases would also not be required.

CONCLUSION

Seraph 100 clearance of vancomycin, gentamicin, meropenem, and imipenem is likely clinically insignificant. There is insufficient evidence to recommend increased doses. For aminoglycosides, we recommend extended interval dosing and initiating Seraph 100 at least 30 min to 1 h after completion of infusion to avoid the possibility of interference with maximum concentrations.

Model Re-Estimation: An Alternative for Poor Predictive Performance during External Evaluations? Example of Gentamicin in Critically Ill Patients

Background: An external evaluation is crucial before clinical applications; however, only a few gentamicin population pharmacokinetic (PopPK) models for critically ill patients included it in the model development. In this study, we aimed to evaluate gentamicin PopPK models developed for critically ill patients. Methods: The evaluated models were selected following a literature review on aminoglycoside PopPK models for critically ill patients. The data of patients were retrospectively collected from two Quebec hospitals, the external evaluation and model re-estimation were performed with NONMEM^® (v7.5) and the population bias and imprecisions were estimated. Dosing regimens were simulated using the best performing model. Results: From the datasets of 39 and 48 patients from the two Quebec hospitals, none of the evaluated models presented acceptable values for bias and imprecision. Following model re-estimations, all models showed an acceptable predictive performance. An a priori dosing nomogram was developed with the best performing re-estimated model and was consistent based on recommended dosing regimens. Conclusion: Due to the poor predictive performance during the external evaluations, the latter must be prioritized during model development. Model re-estimation may be an alternative to developing a new model, especially when most known models display similar covariates.

Clinical Pharmacokinetics of Gentamicin in Various Patient Populations and Consequences for Optimal Dosing for Gram-Negative Infections: An Updated Review

Gentamicin is an aminoglycoside antibiotic with a small therapeutic window that is currently used primarily as part of short-term empirical combination therapy. Gentamicin dosing schemes still need refinement, especially for subpopulations where pharmacokinetics can differ from pharmacokinetics in the general adult population: obese patients, critically ill patients, paediatric patients, neonates, elderly patients and patients on dialysis. This review summarizes the clinical pharmacokinetics of gentamicin in these patient populations and the consequences for optimal dosing of gentamicin for infections caused by Gram-negative bacteria, highlighting new insights from the last 10 years. In this period, several new population pharmacokinetic studies have focused on these subpopulations, providing insights into the typical values of the most relevant pharmacokinetic parameters, the variability of these parameters and possible explanations for this variability, although unexplained variability often remains high. Both dosing schemes and pharmacokinetic/pharmacodynamic (PK/PD) targets varied widely between these studies. A gentamicin starting dose of 7 mg/kg based on total body weight (or on adjusted body weight in obese patients) appears to be the optimal strategy for increasing the probability of target attainment (PTA) after the first administration for the most commonly used PK/PD targets in adults and children older than 1 month, including critically ill patients. However, evidence that increasing the PTA results in higher efficacy is lacking; no studies were identified that show a correlation between estimated or predicted PK/PD target attainment and clinical success. Although it is unclear if performing therapeutic drug monitoring (TDM) for optimization of the PTA is of clinical value, it is recommended in patients with highly variable pharmacokinetics, including patients from all subpopulations that are critically ill (such as elderly, children and neonates) and patients on intermittent haemodialysis. In addition, TDM for optimization of the dosing interval, targeting a trough concentration of at least < 2 mg/L but preferably < 0.5–1 mg/L, has proven to reduce nephrotoxicity and is therefore recommended in all patients receiving more than one dose of gentamicin. The usefulness of the daily area under the plasma concentration–time curve for predicting nephrotoxicity should be further investigated. Additionally, more research is needed on the optimal PK/PD targets for efficacy in the clinical situations in which gentamicin is currently used, that is, as monotherapy for urinary tract infections or as part of short-term combination therapy.

Population Pharmacokinetics and Dosing Optimization of Gentamicin in Critically Ill Patients Undergoing Continuous Renal Replacement Therapy

Purpose

Appropriate gentamicin dosing in continuous renal replacement therapy (CRRT) patients remains undefined. This study aimed to develop a population pharmacokinetic (PK) model of gentamicin in CRRT patients and to infer the optimal dosing regimen for gentamicin.

Methods

Fourteen CRRT patients dosed with gentamicin were included to establish a population PK model to characterize the variabilities and influential covariates of gentamicin. The pharmacokinetic/pharmacodynamic (PK/PD) target attainment and risk of toxicity for different combinations of gentamicin regimens (3–7 mg/kg q24h) and CRRT effluent doses (30–50 mL/h/kg) were evaluated by Monte Carlo simulation. The probability of target attainment (PTA) was determined for the PK/PD indices of the ratio of drug peak concentration/minimum inhibitory concentration (C_max/MIC > 10) and the ratio of area under the drug concentration–time curve/MIC over 24 h (AUC_0-24h/MIC > 100), and the risk of toxicity was estimated by drug trough concentration thresholds (1 and 2 mg/L).

Results

A one-compartment model adequately described the PK characteristics of gentamicin. Covariates including body weight, age, gender, and CRRT modality did not influence the PK parameters of gentamicin based on our dataset. All studied gentamicin regimens failed to achieve satisfactory PTAs for pathogens with an MIC ≥2 mg/L. A good balance of PK/PD target attainment and risk of toxicity (>2 mg/L) was achieved under 7 mg/kg gentamicin q24h and 40 mL/kg/h CRRT dose for an MIC ≤1 mg/L. CRRT dose intensity had a significant impact on the target attainment of AUC_0-24h/MIC >100 and risk of toxicity.

Conclusion

A combination of 7 mg/kg gentamicin q24h and 40 mL/kg/h CRRT dose might be considered as a starting treatment option for CRRT patients, and drug monitoring is required to manage toxicity.

Therapeutic Drug Monitoring of Anti-infective Drugs: Implementation Strategies for 3 Different Scenarios

BACKGROUND

Therapeutic drug monitoring (TDM) supports personalized treatment. For successful implementation, TDM must have a turnaround time suited to the clinical needs of patients and their health care settings. Here, the authors share their views of how a TDM strategy can be tailored to specific settings and patient groups.

METHODS

The authors selected distinct scenarios for TDM: high-risk, complex, and/or critically ill patient population; outpatients; and settings with limited laboratory resources. In addition to the TDM scenario approach, they explored potential issues with the legal framework governing dose escalation.

RESULTS

The most important issues identified in the different scenarios are that critically ill patients require rapid turnaround time, outpatients require an easy sampling procedure for the sample matrix and sample collection times, settings with limited laboratory resources necessitate setting-specific analytic techniques, and all scenarios warrant a legal framework to capture the use of escalated dosages, ideally with the use of trackable dosing software.

CONCLUSIONS

To benefit patients, TDM strategies need to be tailored to the intended population. Strategies can be adapted for rapid turnaround time for critically ill patients, convenient sampling for outpatients, and feasibility for those in settings with limited laboratory resources.

PBPK Modeling and Simulation and Therapeutic Drug Monitoring: Possible Ways for Antibiotic Dose Adjustment

Pharmacokinetics (PK) is a branch of pharmacology present and of vital importance for the research and development (R&D) of new drugs, post-market monitoring, and continued optimizations in clinical contexts. Ultimately, pharmacokinetics can contribute to improving patients’ clinical outcomes, helping enhance the efficacy of treatments, and reducing possible adverse side effects while also contributing to precision medicine. This article discusses the methods used to predict and study human pharmacokinetics and their evolution to the current physiologically based pharmacokinetic (PBPK) modeling and simulation methods. The importance of therapeutic drug monitoring (TDM) and PBPK as valuable tools for Model-Informed Precision Dosing (MIPD) are highlighted, with particular emphasis on antibiotic therapy since dosage adjustment of antibiotics can be vital to ensure successful clinical outcomes and to prevent the spread of resistant bacterial strains.

PBPK Modeling and Simulation of Antibiotics Amikacin, Gentamicin, Tobramycin, and Vancomycin Used in Hospital Practice

The importance of closely observing patients receiving antibiotic therapy, performing therapeutic drug monitoring (TDM), and regularly adjusting dosing regimens has been extensively demonstrated. Additionally, antibiotic resistance is a contemporary concerningly dangerous issue. Optimizing the use of antibiotics is crucial to ensure treatment efficacy and prevent toxicity caused by overdosing, as well as to combat the prevalence and wide spread of resistant strains. Some antibiotics have been selected and reserved for the treatment of severe infections, including amikacin, gentamicin, tobramycin, and vancomycin. Critically ill patients often require long treatments, hospitalization, and require particular attention regarding TDM and dosing adjustments. As these antibiotics are eliminated by the kidneys, critical deterioration of renal function and toxic effects must be prevented. In this work, clinical data from a Portuguese cohort of 82 inpatients was analyzed and physiologically based pharmacokinetic (PBPK) modeling and simulation was used to study the influence of different therapeutic regimens and parameters as biological sex, body weight, and renal function on the biodistribution and pharmacokinetic (PK) profile of these four antibiotics. Renal function demonstrated the greatest impact on plasma concentration of these antibiotics, and vancomycin had the most considerable accumulation in plasma over time, particularly in patients with impaired renal function. Thus, through a PBPK study, it is possible to understand which pharmacokinetic parameters will have the greatest variation in a given population receiving antibiotic administrations in hospital context.

Generating Genotype-Specific Aminoglycoside Combinations with Ceftazidime/Avibactam for KPC-Producing Klebsiella pneumoniae

Antibiotic combinations, including ceftazidime/avibactam (CAZ/AVI), are frequently employed to combat KPC-producing Klebsiella pneumoniae (KPC-Kp), though such combinations have not been rationally optimized. Clinical KPC-Kp isolates with common genes encoding aminoglycoside-modifying enzymes (AMEs), aac(6')-Ib' or aac(6')-Ib, were used in static time-kill assays (n = 4 isolates) and the hollow-fiber infection model (HFIM; n = 2 isolates) to evaluate the activity of gentamicin, amikacin, and CAZ/AVI alone and in combinations. A short course, one-time aminoglycoside dose was also evaluated. Gentamicin plus CAZ/AVI was then tested in a mouse pneumonia model. Synergy with CAZ/AVI was more common with amikacin for aac(6')-Ib'-containing KPC-Kp but more common with gentamicin for aac(6')-Ib-containing isolates in time-kill assays. In the HFIM, although the isolates were aminoglycoside-susceptible at baseline, aminoglycoside monotherapies displayed variable initial killing, followed by regrowth and resistance emergence. CAZ/AVI combined with amikacin or gentamicin resulted in undetectable counts 50 h sooner than CAZ/AVI monotherapy against KPC-Kp with aac(6')-Ib'. CAZ/AVI monotherapy failed to eradicate KPC-Kp with aac(6')-Ib and a combination with gentamicin led to undetectable counts 70 h sooner than with amikacin. A one-time aminoglycoside dose with CAZ/AVI provided similar killing to aminoglycosides dosed for 7 days. In the mouse pneumonia model (n = 1 isolate), gentamicin and CAZ/AVI achieved a 6.0-log₁₀ CFU/lung reduction at 24 h, which was significantly greater than either monotherapy (P < 0.005). Aminoglycosides in combination with CAZ/AVI were promising for KPC-Kp infections; this was true even for a one-time aminoglycoside dose. Selecting aminoglycosides based on AME genes or susceptibilities can improve the pharmacodynamic activity of the combination.

Dose Optimization of Gentamicin in Critically Ill Neonates

BACKGROUND

Appropriate dosing of gentamicin in critically ill neonates is still debated.

OBJECTIVE

To assess the peak concentration (Cmax) and area-under-the-time-concentration curve (AUC0-24) of gentamicin and to simulate the recommended doses using the Monte Carlo method.

METHODS

This was a retrospective study on critically ill neonates carried over a one-year period. The demographic characteristics, dosage regimen and gentamicin concentrations were recorded for each neonate. Using Bayesian pharmacokinetic modeling, Cmax and AUC0-24 were predicted. Dose recommendations for the target Cmax (μg/ml) of 12 were obtained, and Monte Carlo simulation (100,000 iterations) was used for predicting the pharmacokinetic parameters and recommended doses for various birth weight categories.

RESULTS

Eighty-two critically ill neonates (with an average gestational age of 33.7 weeks; and birth weight of 2.1 kg) were recruited. Higher Cmax and AUC0-24 values were predicted in premature neonates, with greater cumulative AUCs in extremely preterm neonates. The average administered dose was 4 mg/kg/day and 75% of the participants had Cmax greater than 12 μg/ml following a single dose, and 85% were found to be at steady state. On the contrary, only 25% of the study population had the recommended AUC0-24 (above 125 μg-hr/ml). Simulation tests indicate that 90% of the critically ill neonates would achieve recommended Cmax with doses ranging between 5 and 6 mg/kg/day.

CONCLUSION

Currently used dose of 4 mg/kg/day is adequate to maintain Cmax in a large majority of the study population, with one-fourth population reporting the recommended AUC0-24. Increasing the dose to 5-6 mg/kg/day will more likely help to achieve both the recommended Cmax and AUC0-24 values.

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.

Pinacho D. Personalized Medicine for Antibiotics: The Role of Nanobiosensors in Therapeutic Drug Monitoring

Due to the high bacterial resistance to antibiotics (AB), it has become necessary to adjust the dose aimed at personalized medicine by means of therapeutic drug monitoring (TDM). TDM is a fundamental tool for measuring the concentration of drugs that have a limited or highly toxic dose in different body fluids, such as blood, plasma, serum, and urine, among others. Using different techniques that allow for the pharmacokinetic (PK) and pharmacodynamic (PD) analysis of the drug, TDM can reduce the risks inherent in treatment. Among these techniques, nanotechnology focused on biosensors, which are relevant due to their versatility, sensitivity, specificity, and low cost. They provide results in real time, using an element for biological recognition coupled to a signal transducer. This review describes recent advances in the quantification of AB using biosensors with a focus on TDM as a fundamental aspect of personalized medicine.

Safety of drug use in patients with a primary mitochondrial disease: An international Delphi-based consensus

Clinical guidance is often sought when prescribing drugs for patients with primary mitochondrial disease. Theoretical considerations concerning drug safety in patients with mitochondrial disease may lead to unnecessary withholding of a drug in a situation of clinical need. The aim of this study was to develop consensus on safe medication use in patients with a primary mitochondrial disease. A panel of 16 experts in mitochondrial medicine, pharmacology, and basic science from six different countries was established. A modified Delphi technique was used to allow the panellists to consider draft recommendations anonymously in two Delphi rounds with predetermined levels of agreement. This process was supported by a review of the available literature and a consensus conference that included the panellists and representatives of patient advocacy groups. A high level of consensus was reached regarding the safety of all 46 reviewed drugs, with the knowledge that the risk of adverse events is influenced both by individual patient risk factors and choice of drug or drug class. This paper details the consensus guidelines of an expert panel and provides an important update of previously established guidelines in safe medication use in patients with primary mitochondrial disease. Specific drugs, drug groups, and clinical or genetic conditions are described separately as they require special attention. It is important to emphasise that consensus-based information is useful to provide guidance, but that decisions related to drug prescribing should always be tailored to the specific needs and risks of each individual patient. We aim to present what is current knowledge and plan to update this regularly both to include new drugs and to review those currently included.

A coup d'état by NDM-producing Klebsiella pneumoniae overthrows the major bacterial population during KPC-directed therapy

The objective of this study was to utilize a co-culture hollow-fiber infection model (HFIM) to characterize the interplay between a small, difficult-to-detect, New Delhi metallo-β-lactamase-producing Klebsiella pneumoniae (NDM-Kp) minor population and a larger K. pneumoniae carbapenemase (KPC)-producing K. pneumoniae population in the presence of KPC-directed antibacterial therapy. Selective plating onto agar with ceftazidime-avibactam was used to track the density of the NDM-Kp population. Susceptibility testing and the Verigene System failed to identify the small initial NDM-Kp population. However, a ceftazidime-avibactam Etest detected resistant colonies that were confirmed to be NDM-Kp. In the HFIM, all of the investigated drug regimens caused regrowth within 24 h and resulted in >10⁹ CFU/mL of NDM-Kp. Our study demonstrates that the HFIM is a powerful tool for studying the population dynamics of multiple pathogens during antimicrobial exposure and also highlights that difficult-to-detect minor populations of drug-resistant bacteria may cause treatment failure without appropriate antibacterial therapy.