Aminoglycoside dosing in patients by kidney function and area under the curve: the Sawchuk-Zaske dosing method revisited in the era of obesity

Improved characterization of aminoglycoside penetration into human lung epithelial lining fluid via population pharmacokinetics

Aminoglycosides are important treatment options for serious lung infections, but modeling analyses to quantify their human lung epithelial lining fluid (ELF) penetration are lacking. We estimated the extent and rate of penetration for five aminoglycosides via population pharmacokinetics from eight published studies. The area under the curve in ELF vs plasma ranged from 50% to 100% and equilibration half-lives from 0.61 to 5.80 h, indicating extensive system hysteresis. Aminoglycoside ELF peak concentrations were blunted, but overall exposures were moderately high.

Antimicrobials in patients with hematologic malignancies and recipients of hematopoietic cell transplantation and other cellular therapies

BACKGROUND

Appropriate use of antimicrobials for hematologic malignancy, hematopoietic stem cell transplant recipients, and other cellular therapies is vital, with infection causing significant morbidity and mortality in this unique population of immunocompromised hosts. However, often in this population the choice and management of antimicrobial therapy is complex. When selecting an antimicrobial agent, key considerations include the need for dose adjustments due to renal or hepatic impairment, managing drug interactions, the potential for additive drug toxicity among those receiving polypharmacy and therapeutic drug monitoring. Other factors include leveraging pharmacodynamic principles to enable optimization of directed therapy against challenging pathogens, as well as judicious use of antimicrobials to limit drug resistance and adverse drug reactions.

SUMMARY

This review summarizes the clinical considerations for commonly used antimicrobials in this setting, including antibacterial, antiviral, and antifungal agents.

Pharmacokinetics and therapeutic target attainment of vancomycin in pediatric post-liver transplant patients

INTRODUCTION

Vancomycin is widely prescribed to treat or prevent Gram-positive infections in pediatric liver transplant recipients. The objective of this prospective cohort study is to describe vancomycin pharmacokinetics and to evaluate the therapeutic target attainment after initial dose regimen.

MATERIALS AND METHODS

Patients with previous renal injury were excluded. Vancomycin therapy started with 40‒60 mg/kg/day. The pharmacokinetic parameters were assessed using two steady-state blood samples and the first-order kinetic equations. Therapeutic target was defined as vancomycin 24-hour Area Under the Curve/Minimum Inhibitory Concentration (AUC/MIC) ≥ 400 and < 600.

RESULTS

Sixteen patients were included. The found vancomycin clearance, half-life, and volume of distribution were, respectively: 2.1 (1.3‒2.8) mL/kg/min, 3.3 (2.7‒4.4) hours, and 0.7 (0.5‒0.9) L/kg. With the initial dose, only 6 (37 %) patients reached the therapeutic target against Gram-positive pathogens with MIC 1 mg/L. After individual dose adjustments, all patients reached the target. The correlation between trough levels and AUC was low (R2 = 0.5).

CONCLUSIONS

Pediatric patients with preserved renal function after liver transplantation have an increased volume of distribution for vancomycin, and most patients present subtherapeutic levels after the standard initial dosing regimen. With the vancomycin AUC-guided monitoring and dosing, it is possible to improve therapeutic target attainment.

Predicting the Area under the Plasma Concentration-Time Curve (AUC) for First Dose Vancomycin Using First-Order Pharmacokinetic Equations

To treat critically ill patients, early achievement of the target area under the plasma concentration-time curve/minimum inhibitory concentration (AUC/MIC) in the first 24 h is recommended. However, accurately calculating the AUC before steady state is an obstacle to this goal. A first-order pharmacokinetic equation to calculate vancomycin AUC after a first dose of vancomycin has never been studied. We sought to estimate AUC using two first-order pharmacokinetic equations, with different paired concentration time points, and to compare these to the actual first dose vancomycin AUC calculated by the linear-log trapezoid rule as a reference. The equations were validated using two independent intensive first dose vancomycin concentration time data sets, one from 10 adults and another from 14 children with severe infection. The equation with compensation for the alpha distribution phase using a first vancomycin serum concentration from 60 to 90 min and the second concentration from 240 to 300 min after the completed infusion showed good agreement and low bias of calculated AUC, with mean differences <5% and Lin's correlation coefficient >0.96. Moreover, it gave an excellent correlation with Pearson's r > 0.96. Estimating the first dose vancomycin AUC calculated using this first-order pharmacokinetic equation is both reliable and reproducible in clinical practice settings.

Comprehensive guidance for antibiotic dosing in obese adults: 2022 update

Drug dosing in obese patients continues to be challenging due to a lack of high-quality evidence to guide dosing recommendations. We first published guidance for antibiotic dosing in obese adults in 2017, in which we critically reviewed articles identified from a broad search strategy to develop dosing recommendations for 35 antimicrobials. In this updated narrative review, we searched Pubmed, Web of Science, and the Cochrane Library using Medical Subject Headings including anti-infectives, specific generic antimicrobial names, obese, pharmacokinetics, and others. We reviewed 393 articles, cross-referenced select cited references, and when applicable, referenced drug databases, package inserts, and clinical trial data to update dosing recommendations for 41 antimicrobials. Most included articles were pharmacokinetic studies, other less frequently included articles were clinical studies (mostly small, retrospective), case reports, and very rarely, guidelines. Pharmacokinetic changes are frequently reported, can be variable, and sometimes conflicting in this population, and do not always translate to a documented difference in clinical outcomes, yet are used to inform dosing strategies. Extended infusions, high doses, and therapeutic drug monitoring remain important strategies to optimize dosing in this population. Additional studies are needed to clinically validate proposed dosing strategies, clarify optimal body size descriptors, dosing weight scalars, and estimation method of renal function in obese patients.

Trough-Guided Versus AUC/MIC-Guided Vancomycin Monitoring: A Cost Analysis

PURPOSE

Recent vancomycin dosing and monitoring guidelines recommend monitoring vancomycin area under the 24-hour time-concentration curve instead of traditional trough-only monitoring. This study aimed to compare the total costs of vancomycin dosing and monitoring between trough-guided and AUC-guided approaches in a quaternary hospital from Brazil.

METHODS

In this retrospective cohort study, patients were divided into 2 groups according to the monitoring method. Patients with previous renal impairment were excluded. Vancomycin AUC was estimated by using 2 steady-state serum concentrations and first-order kinetics equations. The primary outcome was total cost of vancomycin therapy and monitoring from the hospital perspective, which included costs of cumulative doses, laboratory fees, materials used in blood collection, nursing time for collection, and pharmacist time for result interpretation.

FINDINGS

A total of 68 patients were included in the AUC/MIC-guided monitoring group, and 76 patients were included in the trough-guided monitoring group. There were no significant differences between groups regarding baseline serum creatinine level, duration of vancomycin therapy, and cumulative vancomycin dose. The median (interquartile range) total vancomycin drug and monitoring cost was $298.32 ($153.81-$429.85) for the AUC/MIC-guided group compared with $285.59 ($198.81-$435.57) for the trough-guided group (P = 0.9658).

IMPLICATIONS

Vancomycin AUC estimation using 2 steady-state serum concentrations and first-order kinetics equations is a feasible alternative for limited-resource institutions that intend to transition from a trough approach to AUC/MIC-guided monitoring. (Clin Ther. 2022;44:XXX-XXX) © 2022 Elsevier HS Journals, Inc.

Augmented Renal Clearance in Severe Infections-An Important Consideration in Vancomycin Dosing: A Narrative Review

Vancomycin is a hydrophilic antibiotic widely used in severe infections, including bacteremia and central nervous system (CNS) infections caused by Gram-positive bacteria such as methicillin-resistant Staphylococcus aureus (MRSA), coagulase-negative staphylococci and enterococci. Appropriate antimicrobial dosage regimens can help achieve the target exposure and improve clinical outcomes. However, vancomycin exposure in serum and cerebrospinal fluid (CSF) is challenging to predict due to rapidly changing pathophysiological processes and patient-specific factors. Vancomycin concentrations may be decreased for peripheral infections due to augmented renal clearance (ARC) and increased distribution caused by systemic inflammatory response syndrome (SIRS), increased capillary permeability, and aggressive fluid resuscitation. Additionally, few studies on vancomycin’s pharmacokinetics (PK) in CSF for CNS infections. The relationship between exposure and clinical response is unclear, challenging for adequate antimicrobial therapy. Accurate prediction of vancomycin pharmacokinetics/pharmacodynamics (PK/PD) in patients with high interindividual variation is critical to increase the likelihood of achieving therapeutic targets. In this review, we describe the interaction between ARC and vancomycin PK/PD, patient-specific factors that influence the achievement of target exposure, and recent advances in optimizing vancomycin dosing schedules for severe infective patients with ARC.

Antimicrobial Dosing in Specific Populations and Novel Clinical Methodologies: Obesity

Obesity and its related comorbidities can negatively influence the outcomes of certain infectious diseases. Specific dosing recommendations are often lacking in the product label for patients with obesity that leads to unclear guidance in practice. Higher rates of therapeutic failure have been reported with some fixed dose antibiotics and pragmatic approaches to dose modification are limited for orally administered agents. For i.v. antimicrobials dosed on weight, alternate body size descriptors (ABSDs) have been used to reduce the risk of overdosing. These ABSDs are mathematical transformations of height and weight that represent fat-free weight and follow the same principles as body surface area (BSA)-based dosing of cancer chemotherapy. However, ABSDs are rarely studied in pivotal phase III studies and so can risk the underdosing of antimicrobials in patients with obesity when incorrectly applied in the real-world setting. Specific case examples are presented to highlight these risks. Although general principles may be considered by clinicians, a universal approach to dose modification in obesity is unlikely. Studies that can better distinguish human body phenotypes may help reduce our reliance on height and weight to define dosing. Simple and complex technologies exist to quantify individual body composition that could improve upon our current approach. Early evidence suggests that body composition parameters repurposed from medical imaging data may improve upon height and weight as covariates of drug clearance and distribution. Clinical trials that can integrate human body phenotyping may help us identify new approaches to optimal dose selection of antimicrobials in patients with obesity.

A Prospective Clinical Study Characterizing the Influence of Morbid Obesity on the Pharmacokinetics of Gentamicin: Towards Individualized Dosing in Obese Patients

Background and Objective

Gentamicin is an aminoglycoside antibiotic predominantly used in bloodstream infections. Although the prevalence of obesity is increasing dramatically, there is no consensus on how to adjust the dose in obese individuals. In this prospective clinical study, we study the pharmacokinetics of gentamicin in morbidly obese and non-obese individuals to develop a dosing algorithm that results in adequate drug exposure across body weights.

Methods

Morbidly obese subjects undergoing bariatric surgery and non-obese healthy volunteers received one intravenous dose of gentamicin (obese: 5 mg/kg based on lean body weight, non-obese: 5 mg/kg based on total body weight [TBW]) with subsequent 24-h sampling. All individuals had a normal renal function. Statistical analysis, modelling and Monte Carlo simulations were performed using R version 3.4.4 and NONMEM^® version 7.3.

Results

A two-compartment model best described the data. TBW was the best predictor for both clearance [CL = 0.089 × (TBW/70)^0.73] and central volume of distribution [V_c = 11.9 × (TBW/70)^1.25] (both p < 0.001). Simulations showed how gentamicin exposure changes across the weight range with currently used dosing algorithms and illustrated that using a nomogram based on a ‘dose weight’ [70 × (TBW/70)^0.73] will lead to similar exposure across the entire population.

Conclusions

In this study in morbidly obese and non-obese individuals ranging from 53 to 221 kg we identified body weight as an important determinant for both gentamicin CL and V_c. Using a body weight-based dosing algorithm, optimized exposure across the entire population can be achieved, thereby potentially improving efficacy and safety of gentamicin in the obese and morbidly obese population.

Trial Registration

Registered in the Dutch Trial Registry (NTR6058).

Electronic supplementary material

The online version of this article (10.1007/s40262-019-00762-4) contains supplementary material, which is available to authorized users.

Monitoring of Tobramycin Exposure: What is the Best Estimation Method and Sampling Time for Clinical Practice?

OBJECTIVES

The objective of this article is to investigate the influence of blood sampling times on tobramycin exposure estimation and clinical decisions and to determine the best sampling times for two estimation methods used for therapeutic drug monitoring.

METHODS

Adult patients with cystic fibrosis, treated with once-daily intravenous tobramycin, were intensively sampled over one 24-h dosing interval to determine true exposure (AUC_0-24). The AUC_0-24s were then estimated using both log-linear regression and Bayesian forecasting methods for 21 different sampling time combinations. These were compared to true exposure using relative prediction errors. The differences in subsequent dose recommendations were calculated.

RESULTS

Twelve patients, with a median (range) age of 25 years (18-36) and weight of 66.5 kg (50.6-76.4) contributed 96 tobramycin concentrations. Five hundred and eighty-eight estimated AUC_0-24s were compared to 12 measured true AUC_0-24 values. Median relative prediction errors ranged from - 34.7 to 45.5% for the log-linear regression method and from - 14.46 to 11.23% for the Bayesian forecasting method across the 21 sampling combinations. The most unbiased exposure estimation was provided from concentrations sampled at 100/640 min after the start of the infusion using log-linear regression and at 70/160 min using Bayesian forecasting. Subsequent dosing recommendations varied greatly depending on the estimation method and the sampling times used.

CONCLUSION

Sampling times markedly influence bias in AUC_0-24 estimation, leading to greatly varied dose adjustments. The impact of blood sampling times on dosing decisions is reduced when using Bayesian forecasting.

AUC- vs. Trough-Guided Monitoring of Vancomycin in Infants

OBJECTIVE

Improving vancomycin therapy with therapeutic drug monitoring is recommended. Over the past few years, a few studies have demonstrated that trough concentrations may not be the optimal parameter for monitoring vancomycin concentration and Area under the curve (AUC) should be used instead. In this study authors evaluate two methods to estimate the AUC. The first method is based on linear regression using only a trough concentration. The second method uses a simplified two-sample equation-based strategy to estimate the AUC.

METHODS

Data from 70 infant patients were collected retrospectively from their medical records at King Saud University Medical City. The prediction accuracy for vancomycin therapy monitoring was optimized by comparing the two methods for the AUC calculation, the simple linear regression and simplified two-sample equation-based strategy.

RESULTS

The target AUC > 400 μg × h/ml was achieved in 10%, 71%, and 100% of patients with trough concentration ranges of 5-10, 10-15, and > 15 μg/ml, respectively. There was a strong correlation between the predicted and observed AUC calculated using the simplified two-sample equation-based strategy (R² = 0.91, bias = -3.9%, precision =12%).

CONCLUSIONS

The target AUC > 400 μg × h/ml can be achieved at trough concentrations <15 μg/ml in most patients. Targeting trough concentrations >15 can lead to overdoing and increase risk of nephrotoxicity. The authors recommend estimating the AUC using the simplified two-sample equation strategy for more precise dosing of vancomycin. Using AUC-guided dosing instead of the trough-guided approach can prevent over dosing and reduce the risk of nephrotoxicity.

Tobramycin Clearance Is Best Described by Renal Function Estimates in Obese and Non-obese Individuals: Results of a Prospective Rich Sampling Pharmacokinetic Study

Purpose

Tobramycin is an aminoglycoside antibiotic of which the 24 h exposure correlates with efficacy. Recently, we found that clearance of the aminoglycoside gentamicin correlates with total body weight (TBW). In this study, we investigate the full pharmacokinetic profile of tobramycin in obese and non-obese individuals with normal renal function.

Methods

Morbidly obese individuals (n = 20) undergoing bariatric surgery and non-obese healthy volunteers (n = 8), with TBW ranging 57–194 kg, received an IV dose of tobramycin with plasma concentrations measured over 24 h (n = 10 per individual). Statistical analysis, modelling and simulations were performed using NONMEM.

Results

In a two-compartment model, TBW was the best predictor for central volume of distribution (p < 0.001). For clearance, MDRD (de-indexed for body surface area) was identified as best covariate (p < 0.001), and was superior over TBW ((p < 0.05). Other renal function estimates (24 h urine GFR and de-indexed CKD-EPI) led to similar results as MDRD (all p < 0.001)).

Conclusions

In obese and non-obese individuals with normal renal function, renal function estimates such as MDRD were identified as best predictors for tobramycin clearance, which may imply that other processes are involved in clearance of tobramycin versus gentamicin. To ensure similar exposure across body weights, we propose a MDRD-based dosing nomogram for obese patients.

Electronic supplementary material

The online version of this article (10.1007/s11095-019-2651-2) contains supplementary material, which is available to authorized users.

Optimizing Vancomycin Monitoring in Pediatric Patients

BACKGROUND

Several studies have reported that trough levels may not be optimal for monitoring vancomycin therapy, because of overexposure and nephrotoxicity risks. Therefore, we developed a population pharmacokinetic model to optimize vancomycin dosing and monitoring in pediatrics.

METHODS

Data were retrospectively collected on 76 pediatric patients 1-12 years of age, admitted to general pediatric wards or intensive care units at King Saud University Medical City, Riyadh, Saudi Arabia. The predictability of 3 methods for calculating the area under the curve (AUC) at steady state was assessed for optimum vancomycin therapy monitoring. The 3 methods were simple linear regression, Bayesian approach and the 2-sample pharmacokinetic equation method. We also used Monet Carlo simulations to evaluate the dosing of vancomycin.

RESULTS

A 1-compartment model adequately described the data. A strong correlation occurred between the observed and predicted AUC from 0 to 24 hours (AUC0-24h) calculated using the Bayesian approach with a trough sample only or pharmacokinetic equations based on 2 measured samples (R = 0.93 and 0.92, respectively). For the simple linear regression method with a trough sample only, the predicted AUC0-24h at steady state with vancomycin trough levels of 10, 15 and 20 µg/mL were 413, 548 and 714 µg·hour/mL, respectively. The target AUC0-24h above 400 was achieved in 46% and 95% of individuals with trough values of 7-11 and 11-15 µg/mL, respectively. Monte Carlo simulations showed that 60-80 mg/kg/d doses are needed to optimize vancomycin therapy.

CONCLUSIONS

In conclusion, targeting vancomycin trough levels above 15 µg/mL in pediatrics would overshoot the target AUC0-24h above 400 and expose them to unnecessary adverse events.

Measurement of Skeletal Muscle Area Improves Estimation of Aminoglycoside Clearance across Body Size

A consistent approach to the dosing of aminoglycosides across the modern body size distribution has been elusive. We evaluated whether radiologically derived measures of body composition could explain more of the interpatient variability in aminoglycoside pharmacokinetics (PK) than standard body size metrics. This retrospective study included adult patients treated with gentamicin or tobramycin with at least three drug concentrations and computed tomography (CT) imaging available. Aminoglycoside volume and clearance (CL) estimates were computed using a two-compartment model by Bayesian analysis. Morphomic data were extracted from CT images using a custom algorithm. Bivariable and multivariable linear regression were used to assess relationships between PK parameters and covariates. A total of 335 patients were included with a median (minimum, maximum) of 4 (3, 16) aminoglycoside concentrations per patient. The median (minimum, maximum) age, height, and weight of included patients were 57 (21, 93) years, 170 (145, 203) centimeters, and 81 (42, 187) kilograms. Both standard and morphomic measures poorly explained variability in volume (R² < 0.06). Skeletal muscle area and volume explained more of the interpatient variability in CL than weight or sex. Higher precision was observed using a modified Cockcroft-Gault equation with skeletal muscle area at L3 (R²= 0.38) or L4 (R²= 0.37) than the standard Cockcroft-Gault equation using lean (R²= 0.23), adjusted (R²= 0.23), or total (R²= 0.22) body weights. These results highlight that skeletal muscle measurements from CT images obtained in the course of care can improve the precision of aminoglycoside CL estimation over current body size scalars.

The performance of contemporary cystatin C-based GFR equations in predicting gentamicin clearance

AIMS

We aimed to compare the performances of contemporary cystatin C (Cys)-based GFR equations, and the creatinine only Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation for predicting gentamicin clearance.

METHODS

The bias and imprecision of the CKD-EPI, CKD-EPI_Cys and creatinine-cystatin C CKD-EPI (CKD-EPI_CrCys) equations for predicting gentamicin clearances, were assessed in 260 patients treated with gentamicin during 2012-2013. The creatinine-cystatin C Berlin Initiative Study equation (BIS_CrCys) was examined in the ≥70 year subgroup. The reference gentamicin clearance was calculated using post-dose plasma concentrations.

RESULTS

The CKD-EPI_CrCys equation had the highest percentage of estimates within 30% of the reference gentamicin clearance (70%, P = 0.003) and lowest root mean square error (95% CI) of 29 (25, 23) ml min(-1) of the three equations for the entire cohort. There was no significant improvement in the performances of the equations with the exclusion of 41 patients with abnormal thyroid function tests or steroid co-prescription at the time of the index gentamicin dose. Of the remaining 219 patients, adjustment for individual BSA improved the performances of all GFR equations (P ≤ 0.003) in those with body mass indices (BMI) <18.5 or ≥30 kg m(-2) , but not those with BMI 18.5-29.9 kg m(-2) . There was no advantage of the BIS_CrCys over the CKD-EPI_CrCys equation in the ≥70 year subgroup.

CONCLUSIONS

The CKD-EPI_CrCys equation provided the best estimate of gentamicin clearance. If used for guiding gentamicin dosing, the results from GFR equations should be adjusted for individual BSA at the extremes of body size.

Innovative approaches to optimizing the delivery of vancomycin in individual patients

The delivery of personalized antimicrobial therapy is a critical component in the treatment of patients with invasive infections. Vancomycin, the drug of choice for infections due to methicillin-resistant Staphylococcus aureus, requires the use of therapeutic drug monitoring (TDM) for delivery of optimal therapy. Current guidance on vancomycin TDM includes the measurement of a trough concentration as a surrogate for achieving an AUC to minimum inhibitory concentration (MIC) by broth microdilution (AUC/MICBMD) ratio≥400. Although trough-only monitoring has been widely integrated into clinical practice, there is a high degree of inter-individual variability between a measured trough concentration and the actual AUC value. The therapeutic discordance between AUC and trough may lead to suboptimal outcomes among patients with infections due to less susceptible pathogens or unnecessarily increase the probability of acute kidney injury (AKI) in others. Given the potentially narrow vancomycin AUC range for optimal effect and minimal AKI, clinicians need a "real-time" system to predict accurately the AUC with limited pharmacokinetic (PK) sampling. This article reviews two innovative approaches for calculating the vancomycin AUC in clinical practice based on one or two drug concentrations. One such approach involves the use of Bayesian computer software programs to estimate the "true" vancomycin AUC value with minimal PK sampling and provide AUC-guided dosing recommendations at the bedside. An alternative involves use of two concentrations (peak and trough) and simple analytic equations to estimate AUC values. Both approaches provide considerable improvements over the current trough-only concentration monitoring method.

Pharmacokinetic changes and dosing modification of aminoglycosides in critically ill obese patients: a literature review

The objective of the paper is to review the literature and provide recommendations for use of aminoglycoside antibiotics in critically ill obese patients. Literature search in PubMed for all articles on the use of aminoglycosides in critically ill obese patients was conducted, and all articles related to pharmacokinetics in obesity were reviewed. Bibliographies of all searched manuscripts were also reviewed in an attempt to find additional references. Although aminoglycoside pharmacokinetics have been described in detail, data on aminoglycoside use and appropriate dose modification in critically ill obese patients are very limited. Knowledge on aminoglycoside pharmacokinetics and use in critically ill obese patients is incomplete. Pathophysiologic changes in obesity can result in sub- or supra-therapeutic aminoglycoside plasma concentrations, especially in the presence of sepsis. Rigorous clinical studies are needed to establish aminoglycoside dosing guidelines in critically ill obese patients with sepsis.

Simplified equations using two concentrations to calculate area under the curve for antimicrobials with concentration-dependent pharmacodynamics: daptomycin as a motivating example

The effects of several antimicrobial agents are predicted by the ratio of the area under the concentration-time curve (AUC) to the MIC (AUC/MIC). Peak (Cp) and trough (Ct) concentrations are often measured clinically as surrogates of AUC because actual computation of AUC from 1 or 2 samples requires sophisticated mathematical methods. Given that the effects of daptomycin are predicted by AUC/MIC, our objective was to compare simple equation calculated AUC based on Cp and Ct to model integrated AUC. A standard population pharmacokinetic model was used to simulate 5,000 daptomycin concentration-time profiles after 5 doses of 6 mg/kg of body weight/day (0.5-h infusions). The AUC for the 24-h period was computed by integration and by equations with 110 Cp-Ct combination pairs. The Cp time points were in 15-min increments between 0.5 h and 3 h and Ct in 15-min increments within an hour of the end of the dosing interval for each dose. The precision and bias of the calculated AUC relative to the integrated AUC were determined to identify Cp-Ct pairs associated with the lowest bias and highest precision. The equations were further validated using two daptomycin concentration-time data sets from healthy volunteers and critically ill patients. The precision and bias of calculated AUC were based primarily on Cp, and use of a daptomycin Cp 1.5 h to 3 h from the start of infusion was associated with a bias of <10% and an R(2) of >0.95. Data from the healthy volunteers and critically ill patients also demonstrated declining bias with use of Cp ≥ 1.5 h from the start of infusion with relatively good precision. Simplified equations using a daptomycin Cp approximately 2 h from the start of infusion and a Ct within an hour of the end of the dosing interval should yield precise and unbiased estimates of daptomycin AUC.