Population Pharmacokinetic Analysis and Dosing Optimization Based on Unbound Daptomycin Concentration and Cystatin C in Nonobese Elderly Patients with Hypoalbuminemia and Chronic Kidney Disease

Daptomycin Exposure Prediction With a Limited Sampling Strategy

BACKGROUND

Daptomycin is a cyclic lipopeptide antibiotic used to treat serious infectious endocarditis caused by Staphylococcus aureus . The pharmacodynamic parameter correlating best with efficacy is the ratio of the estimated area under the concentration (AUC 0-24 )-time curve to the minimum inhibitory concentration. The aim of the study is to develop a limited sampling strategy to estimate AUC 0-24 using a reduced number of samples.

METHODS

Sixty-eight daptomycin AUC 0-24 values were calculated for 50 White patients who underwent treatment for at least 5 consecutive days. Plasma concentrations were detected using a validated high-performance liquid chromatography-tandem mass spectrometry analytical method, with daptomycin-d5 as an internal standard. Multiple regression was used to evaluate the ability of 2 concentration-time points to predict the AUC 0-24 calculated from the entire pharmacokinetic profile. Prediction bias was calculated as the mean prediction error, whereas prediction precision was estimated as the mean absolute prediction error. The development and validation datasets comprised 40 and 10 randomly selected patients, respectively.

RESULTS

The AUC 0-24 (mg*h/L) was best estimated using the daptomycin trough concentration and plasma concentrations detected 2 hours after dosing. We calculated a mean prediction error of 1.6 (95% confidence interval, -10.7 to 10.9) and a mean absolute prediction error of 11.8 (95% confidence interval, 5.3-18.3), with 73% of prediction errors within ±15%.

CONCLUSIONS

An equation was developed to estimate daptomycin exposure (AUC 0-24 ), offering clinical applicability and utility in generating personalized dosing regimens, especially for individuals at high risk of treatment failure or delayed response.

Population pharmacokinetics of antibacterial agents in the older population: a literature review

INTRODUCTION

Older individuals face an elevated risk of developing bacterial infections. The optimal use of antibacterial agents in this population is challenging because of age-related physiological alterations, changes in pharmacokinetics (PK) and pharmacodynamics (PD), and the presence of multiple underlying diseases. Therefore, population pharmacokinetics (PPK) studies are of great importance for optimizing individual treatments and prompt identification of potential risk factors.

AREA COVERED

Our search involved keywords such as 'elderly,' 'old people,' and 'geriatric,' combined with 'population pharmacokinetics' and 'antibacterial agents.' This comprehensive search yielded 11 categories encompassing 28 antibacterial drugs, including vancomycin, ceftriaxone, meropenem, and linezolid. Out of 127 studies identified, 26 (20.5%) were associated with vancomycin, 14 (11%) with meropenem, and 14 (11%) with piperacillin. Other antibacterial agents were administered less frequently.

EXPERT OPINION

PPK studies are invaluable for elucidating the characteristics and relevant factors affecting the PK of antibacterial agents in the older population. Further research is warranted to develop and validate PPK models for antibacterial agents in this vulnerable population.

Pharmacokinetics of Antibacterial Agents in the Elderly: The Body of Evidence

Infections are important factors contributing to the morbidity and mortality among elderly patients. High rates of consumption of antimicrobial agents by the elderly may result in increased risk of toxic reactions, deteriorating functions of various organs and systems and leading to the prolongation of hospital stay, admission to the intensive care unit, disability, and lethal outcome. Both safety and efficacy of antibiotics are determined by the values of their plasma concentrations, widely affected by physiologic and pathologic age-related changes specific for the elderly population. Drug absorption, distribution, metabolism, and excretion are altered in different extents depending on functional and morphological changes in the cardiovascular system, gastrointestinal tract, liver, and kidneys. Water and fat content, skeletal muscle mass, nutritional status, use of concomitant drugs are other determinants of pharmacokinetics changes observed in the elderly. The choice of a proper dosing regimen is essential to provide effective and safe antibiotic therapy in terms of attainment of certain pharmacodynamic targets. The objective of this review is to perform a structure of evidence on the age-related changes contributing to the alteration of pharmacokinetic parameters in the elderly.

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.

Hypoalbuminemia and Pharmacokinetics: When the Misunderstanding of a Fundamental Concept Leads to Repeated Errors over Decades

Surprisingly, misinterpretation of the influence of hypoalbuminemia on pharmacokinetics and the clinical effects of drugs seems to be a current problem, even though hypoalbuminemia has no impact on the pharmacologically active exposure. Exceptions to this fact are highly protein-bound anaesthetics with high elimination capacity (i.e., <5 drugs on the market). To assess the frequency of misinterpretation of the influence of hypoalbuminemia on pharmacokinetics and the clinical effects of drugs between 1975 and 2021, a PubMed literature review was conducted. Each paragraph on albumin binding was classified as correct, ambiguous or incorrect, creating two acceptable categories: (1) content without any errors, and (2) content containing some incorrect and/or ambiguous statements. The analyses of these articles showed that fewer than 11% of articles contained no interpretation errors. In order to contain this misinterpretation, several measures are proposed: (1) Make the message accessible to a wide audience by offering a simplified and didactic video representation of the lack of impact of albumin binding to drugs. (2) Precise terminology (unbound/free form/concentration) should be used for highly bound drugs. (3) Unbound/free forms should be systematically quantified for highly plasma protein bound drugs for clinical trials as well as for therapeutic drug monitoring.

Population Pharmacokinetic Model for Unbound Concentrations of Daptomycin in Patients with MRSA Including Patients Undergoing Hemodialysis

BACKGROUND AND OBJECTIVE

Unbound daptomycin concentrations are responsible for pharmacologically beneficial and adverse effects, although most previous reports have been limited to the use of total concentrations. We developed a population pharmacokinetic model to predict both total and unbound daptomycin concentrations.

METHODS

Clinical data were collected from 58 patients with methicillin-resistant Staphylococcus aureus including patients undergoing hemodialysis. A total of 339 serum total and 329 unbound daptomycin concentrations were used for model construction.

RESULTS

Total and unbound daptomycin concentration was explained by a model that assumed first-order distribution with two compartments, and first-order elimination. Normal fat body mass was identified as covariates. Renal function was incorporated as a linear function of renal clearance and independent non-renal clearance. The unbound fraction was estimated to be 0.066 with a standard albumin of 45 g/L and standard creatinine clearance of 100 mL/min. Simulated unbound daptomycin concentration was compared with minimum inhibitory concentration as a measure of clinical effectiveness and exposure-level-related induction of creatine phosphokinase elevation. The recommended doses were 4 mg/kg for patients with severe renal function [creatinine clearance (CLcr) ≤ 30 mL/min] and 6 mg/kg for patients with mild to moderate renal function (CLcr > 30 and ≤ 60 mL/min). A simulation indicated that dose adjusted by body weight and renal function improved target attainment.

CONCLUSIONS

This population pharmacokinetics model for unbound daptomycin could help clinicians to select the appropriate dose regimen for patients undergoing daptomycin treatment and reduce associated adverse effects.

Characterization of plasma daptomycin in patients with serum highly glycated albumin and obesity

PURPOSE

Plasma daptomycin has not been fully characterized in diabetic and obese patients. This study aimed to evaluate the associations of plasma daptomycin with glycation of serum albumin and obesity.

METHODS

Infectious patients (n = 70) receiving intravenous daptomycin were enrolled. The plasma concentration of total and free daptomycin were determined using liquid chromatograph-tandem mass spectrometer. The associations of the plasma concentrations of daptomycin with clinical factors including serum albumin fractionations and physical status (obese including overweight, body mass index ≥ 25.0) were investigated. Daptomycin doses were adjusted using total body-weight.

RESULTS

The serum albumin level was positively and negatively correlated with the plasma concentration of total daptomycin and its free fraction proportion, respectively. The serum non-glycated albumin was negatively correlated with the free fraction proportion. The dose-normalized plasma concentration of total daptomycin was higher in the obese patients than in non-obese patients when the body-weight was corrected with total and adjusted values. For the dose adjustment with lean body-weight, no difference was observed in the dose-normalized plasma concentration of total daptomycin between the physical statuses. For each body-weight correction method, physical status did not affect the dose-normalized plasma concentration of free daptomycin.

CONCLUSION

The glycation of serum albumin and obesity did not associate with dose-normalized plasma free daptomycin. In obese patients, daptomycin dosage adjustment with total body-weight and adjusted body-weight may lead to an apparent excessive exposure resulting in overdosage compared to lean body-weight.

Daptomycin Physiology-Based Pharmacokinetic Modeling to Predict Drug Exposure and Pharmacodynamics in Skin and Bone Tissues

BACKGROUND AND OBJECTIVE

Daptomycin has been recommended in the treatment of bone and joint infection. Previous work showed that the approved dosage of daptomycin may be insufficient to achieve optimal exposure in patients with bone and joint infection. However, those studies assumed that bone exposure was similar to steady-state daptomycin-free plasma concentrations. We sought to establish a physiologically based pharmacokinetic (PBPK) model of daptomycin to describe the dynamics of daptomycin disposition in bone and skin tissue.

METHODS

A PBPK model of daptomycin was built using PK-Sim^®. Daptomycin concentrations in plasma and bone were obtained from three previously published studies. Physicochemical drug characteristics, mass balance, anthropometrics, and experimental data were used to build and refine the PBPK model. Internal validation of the PBPK model was performed using the usual diagnostic plots. The final PBPK model was then used to run simulations with doses of 6, 8, 10, and 12 mg/kg/24 h. Pharmacokinetic profiles were simulated in 1000 subjects and the probabilities of target attainment for the area under the concentration-time curve over the bacterial minimum inhibitory concentration were computed in blood, skin, and bone compartments.

RESULTS

The final model showed a good fit of all datasets with an absolute average fold error between 0.5 and 2 for all pharmacokinetic quantities in blood, skin and bone tissues. Results of dosing simulations showed that doses ≥10 mg/kg should be used in the case of bacteremia caused by Staphylococcus aureus with a minimum inhibitory concentration >0.5 mg/L or Enterococcus faecalis with a minimum inhibitory concentration >1 mg/L, while doses ≥12 mg/kg should be used in the case of bone and joint infection or complicated skin infection. When considering a lower minimum inhibitory concentration, doses of 6-8 mg/kg would likely achieve a sufficient success rate. However, in the case of infections caused by E. faecalis with a minimum inhibitory concentration >2 mg/L, a higher dosage and combination therapy would be necessary to maximize efficacy.

CONCLUSIONS

We developed the first daptomycin PBPK/pharmacodynamic model for bone and joint infection, which confirmed that a higher daptomycin dosage is needed to optimize exposure in bone tissue. However, such higher dosages raise safety concerns. In this setting, therapeutic drug monitoring and model-informed precision dosing appear necessary to ensure the right exposure on an individual basis.

Target Therapeutic Ranges of Anti-MRSA Drugs, Linezolid, Tedizolid and Daptomycin, and the Necessity of TDM

The target therapeutic ranges of vancomycin, teicoplanin, and arbekacin have been determined, and therapeutic drug monitoring (TDM) is performed in clinical practice. However, TDM is not obligatory for daptomycin, linezolid, or tedizolid. In this study, we examined whether TDM will be necessary for these 3 drugs in the future. There was no significant difference in therapeutic effects on acute bacterial skin and skin structure infection between linezolid and tedizolid by meta-analysis. Concerning the therapeutic effects on pneumonia, the rate of effectiveness after treatment with tedizolid was significantly lower than with linezolid. With respect to safety, the incidences of gastrointestinal adverse events and blood/lymphatic system disorders related to tedizolid were significantly lower than those related to linezolid. Linezolid exhibits potent therapeutic effects on pneumonia, but the appearance of adverse reactions is indicated as a problem. There was a dose-dependent decrease in the platelet count, and the target trough concentration (C_trough) was estimated to be 4-6 or 2-7 µg/mL in accordance with the patient's condition. The efficacy of linezolid may be obtained while minimizing the appearance of adverse reactions by performing TDM. The target therapeutic range of tedizolid cannot be achieved in immunocompromised or severe patients. Therefore, we concluded that TDM was unnecessary, considering step-down therapy with oral drugs, use in non-severe patients, and high-level safety. Concerning daptomycin, high-dose administration is necessary to achieve an area under the curve (AUC) of ≥666 as an index of efficacy. To secure its safety, C_trough (<20 µg/mL) monitoring is important. Therefore, TDM is necessary.

Efficacy and Safety of Daptomycin versus Vancomycin for Bacteremia Caused by Methicillin-Resistant Staphylococcus aureus with Vancomycin Minimum Inhibitory Concentration > 1 µg/mL: A Systematic Review and Meta-Analysis

This systematic review and meta-analysis compares the efficacy of daptomycin and vancomycin in adult patients with bacteremia by methicillin-resistant Staphylococcus aureus (MRSA) with vancomycin minimum inhibitory concentration (MIC) > 1 µg/mL. We searched the PubMed, Web of Science, Cochrane Library, and ClinicalTrials.gov databases on 12 May 2020. All-cause mortality (primary outcome) and treatment success rates were compared and subgroups stratified by infection source risk level and method of vancomycin susceptibility testing were also analyzed. Seven studies (n = 907 patients) were included in this efficacy analysis. Compared with vancomycin, daptomycin treatment was associated with significantly lower mortality (six studies, odds ratio (OR) 0.53, 95% confidence interval (CI) 0.29−0.98) and higher treatment success (six studies, OR 2.20, 95% CI 1.63−2.96), which was consistent regardless of the vancomycin MIC test method used. For intermediate-risk sources, daptomycin was a factor increasing treatment success compared with vancomycin (OR 4.40, 95% CI 2.06−9.40), and it exhibited a trend toward a higher treatment success rate for high-risk sources. In conclusion, daptomycin should be considered for the treatment of bacteremia caused by MRSA with vancomycin MIC > 1 µg/mL, especially in patients with intermediate- and high-risk bacteremia sources.

Identification of Risk Factors for Daptomycin-Associated Creatine Phosphokinase Elevation and Development of a Risk Prediction Model for Incidence Probability

BACKGROUND

In this study, we investigated the risk factors for daptomycin-associated creatine phosphokinase (CPK) elevation and established a risk score for CPK elevation.

METHODS

Patients who received daptomycin at our hospital were classified into the non-elevated or elevated CPK group based on their peak CPK levels during daptomycin therapy. Univariable and multivariable analyses were performed, and a risk score and prediction model for the incidence probability of CPK elevation were calculated based on logistic regression analysis.

RESULTS

The non-elevated and elevated CPK groups included 181 and 17 patients, respectively. Logistic regression analysis revealed that concomitant statin use (odds ratio [OR], 4.45 [95% confidence interval {CI}, 1.40-14.47]; risk score 4), concomitant antihistamine use (OR, 5.66 [95% CI, 1.58-20.75]; risk score 4), and trough concentration (Cmin) between 20 and <30 µg/mL (OR, 14.48 [95% CI, 2.90-87.13]; risk score 5) and ≥30.0 µg/mL (OR, 24.64 [95% CI, 3.21-204.53]; risk score 5) were risk factors for daptomycin-associated CPK elevation. The predicted incidence probabilities of CPK elevation were <10% (low risk), 10%-<25% (moderate risk), and ≥25% (high risk) with total risk scores of ≤4, 5-6, and ≥8, respectively. The risk prediction model exhibited a good fit (area under the receiver operating characteristic curve, 0.85 [95% CI, .74-.95]).

CONCLUSIONS

These results suggested that concomitant use of statins with antihistamines and Cmin ≥20 µg/mL were risk factors for daptomycin-associated CPK elevation. Our prediction model might aid in reducing the incidence of daptomycin-associated CPK elevation.