Comparison of the efficacy of anti-diabetic medications as add-on to metformin in type 2 diabetes mellitus from a real-world database.

BACKGROUND: Metformin is recommended as a first-line drug in the guidelines of the treatment for type 2 diabetes mellitus. However, high-quality evidence from clinical trials directly comparing the degree of hypoglycemic effect of combination therapy of metformin and a hypoglycemic agent with a different mechanism of action with that of monotherapy of a hypoglycemic drug is lacking. We aimed to examine whether combination therapy of hypoglycemic agents with metformin showed antagonism, addition, or synergism compared to monotherapy with hypoglycemic agents other than metformin regarding hemoglobin A1c levels. METHODS: This retrospective cohort study used a medical information database in Japan. Non-insulin anti-hyperglycemic agents with different mechanisms of action were classified into eight drug classes. A monotherapy cohort and a combination therapy added to the metformin cohort were defined. The change in hemoglobin A1c levels was evaluated to compare the treatment effect between the cohorts. RESULTS: A total of 13,359 patients with type 2 diabetes mellitus in the monotherapy cohort and 1,064 in the metformin combination therapy cohort were identified. A comparison of the change from baseline HbA1c level by drug class between the two cohorts showed a similar trend. Among those treated with dipeptidyl peptidase-4 inhibitor and sodium-glucose co-transporter-2 inhibitor, no clinically significant difference was observed between the two cohorts (0.00% and -0.07% for unadjusted, 0.15% and -0.03% for propensity score matching-adjusted, and 0.09% and -0.01% for inverse probability treatment weighting-adjusted analysis). CONCLUSIONS: According to the results of this study, the effect of dipeptidyl peptidase-4 inhibitor or sodium-glucose co-transporter-2 inhibitor added to metformin seems to be additive with respect to the reduction in hemoglobin A1c.

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.

Development of a simple method for measuring tedizolid concentration in human serum using HPLC with a fluorescent detector.

ABSTRACT: The objective of the present study was to develop a method to measure tedizolid (TZD) concentration for studying target concentration intervention, pharmacokinetics, and pharmacodynamics of TZD. We established a high-performance liquid chromatography-fluorescence detector assay to measure the TZD concentration in serum for clinical application. Chromatographic separation was carried out on a 5 µm octadecyl silane hypersil column 150 mm × 4.6 mm. The mobile phase consisted of 0.1 M phosphoric acid and methanol (60:40, pH 7.0). Detection was performed at 300 nm and 340 nm for the excitation and emission wavelengths, respectively. The average retention times of TZD and the internal standard were 12.9 and 8.8 min, respectively. High linearity was exhibited over a concentration range of 0.025 to 10.0 µg/mL for TZD (R2 > 0.999). The intra- and inter-assay accuracies of TZD were 99.2% to 107.0% and 99.2% to 107.7%, respectively. The lower limit of quantitation and the lower limit of detection for TZD measurement were 0.025 and 0.01 µg/mL, respectively. The extraction recoveries of TZD were 100.4% to 114.1%.The high-performance liquid chromatography method developed in this study could separate the analytes with a single eluent (isocratic system), within a total run time of 15 min. Both TZD and IS were well separated, without interference from the peaks. Sharp peaks were observed in the chromatograms; problems such as double peaks, shoulder peaks, and broadened peaks were not observed. The proposed method showed acceptable analytical performance and could be used to evaluate serum TZD concentrations in patients.

An artificial neural network-pharmacokinetic model and its interpretation using Shapley additive explanations.

We developed a method to apply artificial neural networks (ANNs) for predicting time-series pharmacokinetics (PKs), and an interpretable the ANN-PK model, which can explain the evidence of prediction by applying Shapley additive explanations (SHAP). A previous population PK (PopPK) model of cyclosporin A was used as the comparison model. The patients' data were used for the ANN-PK model input, and the output by ANN was the clearance (CL). The estimated CL value from the ANN were substituted into the one-compartment with one-order absorption model, the concentrations were calculated, and the parameters of ANN were updated by the back-propagation method. Kernel SHAP was applied to the trained model and the SHAP value of each input was calculated. The root mean squared error for the PopPK model and the ANN-PK model were 41.1 and 31.0 ng/ml, respectively. The goodness of fit plots for the ANN-PK model represented more convergence to y = x compared with that for the PopPK model, with good model performance for the ANN-PK model. The most influential factors on CL output were age and body weight from the evaluation using Kernel SHAP, and these factors were incorporated into the PopPK model as the significant covariates of CL. The ANN-PK model could handle time-series data and showed higher prediction accuracy then the conventional PopPK model, and the scientific validity for the model could be evaluated by applying SHAP. Study Highlights WHAT IS THE CURRENT KNOWLEDGE ON THE TOPIC? A black-box property of an artificial neural network (ANN) decreases the scientific confidence of the model, and making it difficult to utilize the ANN in the medical field. Moreover, difficulty in handling the time-series data is a significant problem for applying the ANN for pharmacometrics study. WHAT QUESTION DID THIS STUDY ADDRESS? How can we apply the ANN for predicting the time-series pharmacokinetics (PKs) , and confirm the scientific validity of the ANN model? WHAT DOES THIS STUDY ADD TO OUR KNOWLEDGE? Using the ANN in combination with a conventional compartment (ANN-PK) model enabled to handle the time-series PK data, and the predicting performance of the model was higher than that of the population PK model. Furthermore, we could evaluate the scientific validity of the ANN model by applying the Shapley additive explanations. HOW MIGHT THIS CHANGE DRUG DISCOVERY, DEVELOPMENT, AND/OR THERAPEUTICS? We expect that our study will contribute to develop the interpretable ANN model, which can predict the time-series PKs, drug efficacies, and side effects with high prediction performance.

Initially Reduced Linezolid Dosing Regimen to Prevent Thrombocytopenia in Hemodialysis Patients.

This retrospective cohort study investigated the effects of an initially reduced linezolid dosing regimen in hemodialysis patients through therapeutic drug monitoring (TDM). Patients were divided into two groups depending on their initial dose of linezolid (standard dose of 600 mg every 12 h or initially reduced dose of 300 mg every 12 h/600 mg every 24 h). The cumulative incidence rates of thrombocytopenia and severe thrombocytopenia were compared between both groups using the Kaplan-Meier method and log-rank test. Eleven episodes of 8 chronic hemodialysis patients were included; 5 were in the initially reduced-dose group. Thrombocytopenia developed in 81.8% of patients. The cumulative incidence rates of thrombocytopenia and severe thrombocytopenia in the initially reduced-dose group were significantly lower than in the standard-dose group (p < 0.05). At the standard dose, the median linezolid trough concentration (Cmin) just before hemodialysis was 49.5 mg/L, and Cmin at the reduced doses of 300 mg every 12 h and 600 mg every 24 h were 20.6 mg/L and 6.0 mg/L, respectively. All five episodes underwent TDM in the standard-dose group required dose reduction to 600 mg per day. Our findings indicate that initial dose reduction should be implemented to reduce the risk of linezolid-induced thrombocytopenia among hemodialysis patients.

Proposal of initial and maintenance dosing regimens with linezolid for renal impairment patients.

BACKGROUND: Linezolid is administered as a fixed dose to all patients despite evidence of overexposure and thrombocytopenia in renal impairment. The aims of this study were to evaluate the risk of thrombocytopenia and the utility of therapeutic drug monitoring (TDM), and to propose alternate dosing regimens in patients with renal impairment. METHODS: We retrospectively reviewed patients ≥13 years old for whom serum linezolid trough concentration (Cmin) was measured during linezolid treatment. Patients with episodes of infection were divided into groups by presence of renal impairment (RI group) or absence of renal impairment (non-RI group), and by use of Cmin-based TDM (TDM group) or not (non-TDM group) during linezolid treatment. RESULTS: In the 108 patients examined by multivariable analyses, renal impairment was independently associated with increased risk of thrombocytopenia (OR 3.17, 95%CI 1.10-9.12) and higher Cmin. Analysis of the utility of TDM in the RI group showed that clinical failure rate was significantly lower in the TDM subgroup than in the non-TDM subgroup. Furthermore, in the RI group, dosage adjustments were needed in 90.5% of the TDM subgroup. All episodes administered a reduced dose of 300 mg every 12 h in the RI group showed Cmin ≥ 2.0 mg/L. Additional analysis of 53 episodes in which Cmin was measured within 48 h after starting administration showed that the initial standard dose for 2 days was sufficient to rapidly reach an effective therapeutic concentration in the RI group. CONCLUSIONS: Empirical dose reduction to 300 mg every 12 h after administration of the initial fixed dose for 2 days and Cmin-based TDM may improve safety outcomes while maintaining appropriate efficacy among patients with renal impairment.

A case of COVID-19 diagnosed with favipiravir-induced drug fever based on a positive drug-induced lymphocyte stimulation test.

As of October 2020, there is still no specific drug to treat COVID-19 as it rages worldwide. Favipiravir, indicated for the treatment of new and re-emerging influenza infections, has been suggested to be effective against SARS-CoV-2, although this is not yet fully validated. We administered favipiravir to a 64-year-old female patient with COVID-19. Her symptoms resolved quickly after the start of treatment, with reduction of SARS-CoV-2 viral load, but she developed a fever again on day 12. Since the fever was relieved by discontinuation of favipiravir, and based on positive results with a drug-induced lymphocyte stimulation test, we diagnosed her with favipiravir-induced drug fever. A decrease in the serum concentration of favipiravir was observed along with resolution of the fever. The present case suggests that drug fever should be considered in the differential diagnosis of relapsing fever episodes in COVID-19 patients receiving favipiravir.

Classification Tree Analysis Based On Machine Learning for Predicting Linezolid-Induced Thrombocytopenia.

Linezolid-induced thrombocytopenia is related to linezolid exposure, baseline platelet count and patient background. Although the relationship usually reflects the time of onset of thrombocytopenia, if the platelet maturation process is taken into account, the platelet decrease can be considered to have started at the beginning of treatment. To predict linezolid-induced thrombocytopenia, classification and regression tree (CART) analysis based on machine learning has been applied to identify predictive factors and cutoff values. We examined 74 patient data with or without linezolid-induced thrombocytopenia. Linezolid concentration and platelet count change, baseline platelet count, age, body weight and creatinine clearance estimate were evaluated as predictive factors for linezolid-induced thrombocytopenia. CART analysis selected the final tree containing two cutoff values: a platelet count reduction to less than 2.3% from baseline at 96 h after the initial dose and a linezolid concentration greater than or equal to 13.5 mg/L at 96 h after the initial dose. The targets for therapeutic intervention were concluded to be the linezolid concentration and the platelet change from baseline at 96 h after the initial dose. These cutoff values occur prior to the onset of thrombocytopenia and should be monitored to avoid linezolid-induced thrombocytopenia.

Evaluation of the relationship between linezolid exposure and hyponatremia.

INTRODUCTION: Aims of this study were (a) to assess the development ratio of hyponatremia during treatment with linezolid and (b) to evaluate the relationship between the risk of hyponatremia and linezolid exposure and patient background. METHOD: Clinical data including linezolid serum concentrations and serum sodium values were collected at Toyama University Hospital and Kyorin University Hospital. Data from 89 patients were used for the analysis, and a nadir serum sodium level ≤130 mmol/L during the treatment with linezolid was defined as hyponatremia. Mann-Whitney's U test was used to evaluate the effects of the area under the time-concentration curve (AUC) of linezolid at the nadir sodium level, clinical characteristics (e.g. laboratory data), and baseline serum sodium levels on the development of hyponatremia. RESULTS: The hyponatremia was occurred in 21 of 89 patients (23.6%). Data are compared for baseline and nadir serum sodium levels of patients with and without hyponatremia. In both groups, nadir serum sodium levels were significantly different from those of the baseline values (P < 0.05). The values of AUC0-12, accumulated AUC, baseline serum sodium levels and age were significantly different between patients with and without hyponatremia (P < 0.05). CONCLUSIONS: Linezolid exposure, age, and baseline sodium levels were detected as the risk factors for linezolid-related hyponatremia. Our findings suggest that regular monitoring of serum sodium levels is desirable during treatment with linezolid, especially for the elderly and patients with low serum sodium levels before the start of linezolid administration.

External Evaluation of Population Pharmacokinetics and Pharmacodynamics in Linezolid-Induced Thrombocytopenia: The Transferability of Published Models to Different Hospitalized Patients.

BACKGROUND: The objective of this study was to perform an external evaluation of published linezolid population pharmacokinetic and pharmacodynamic models, to evaluate the predictive performance using an independent data set. Another aim was to offer an elegant environment for display and simulation of both the concentration and platelet count after linezolid administration. METHODS: We performed a systematic literature search in PubMed for all studies evaluating the population pharmacokinetic and pharmacodynamic parameters of linezolid in patients and selected the models to be used for the external validation. The bias of predictions was visually evaluated by plotting prediction errors (PEs) and relative PEs. The precision of prediction was evaluated by calculating the mean absolute error (MAE), root mean squared error (RMSE), and mean relative error (MRE). RESULTS: Three articles (models A, B, and C) provided linezolid-induced platelet dynamic models using population pharmacokinetic and pharmacodynamic modeling approaches. The PE and relative PE of both linezolid concentrations and platelet counts for models A and C showed similar predictive distributions. With respect to the prediction accuracy of total linezolid concentration, the MAE, RMSE, and MRE of population prediction values for model C was the smallest. The comparison of the MAE, RMSE, and MRE of patient-individual prediction values for the 3 pharmacodynamic models revealed no large differences. CONCLUSIONS: We confirmed the transferability of published population pharmacokinetic and pharmacodynamic models and showed that they were suitable for extrapolation to other hospitals and/or patients. This study also introduced application software based on model C for the therapeutic drug monitoring of linezolid.

Population Pharmacokinetics and Pharmacodynamics of Teicoplanin and C-Reactive Protein in Hospitalized Patients With Gram-Positive Infections.

Teicoplanin is an antibiotic agent used for the treatment of Gram-positive infections. The clinical benefit of teicoplanin is associated with its blood concentrations, but the optimal dosing regimen is not yet known. To explore the optimal individual dosing regimen, we performed a population pharmacokinetic (PK) and pharmacodynamic (PD) analysis targeting a large-scale population, including patients with a wide range of ages, body weights, and renal functions. The PK of teicoplanin was described with a 2-compartment model, and the PD of C-reactive protein (CRP) concentrations was described with a turnover maximum inhibition model. The elimination half-life of teicoplanin calculated from the final estimated parameters was 169 hours, and renal function was a significant covariate of teicoplanin clearance. The teicoplanin concentration producing 50% of the maximum inhibition of CRP production was estimated to be 2.66 mg/L. The minimum concentration of teicoplanin in patients with higher loading doses (15 mg/kg) reached the target range (15-30 mg/L) with a probability of >50% in the dosing simulation. We described the influence of body size, body composition, and renal function on the PK of teicoplanin. The population PKPD model of teicoplanin and CRP in this study should provide useful information for development of a dosing strategy including the sequential clinical benefit of teicoplanin.

Pharmacokinetics and pharmacodynamics of daptomycin in a clinical setting.

We investigated achievement of a target 24-h area under the concentration-time curve to minimum inhibitory concentration ratio (AUC/MIC) ≥666 and the factors influencing this ratio in patients who received daptomycin (DAP) for infectious disease treatment in a clinical setting. The target AUC/MIC was obtained in 6 patients (35.3%) at a 4-6 mg/kg dose (Group_4-6 mg/kg) and in 4 (18.2%) at a >6 mg/kg dose (Group_>6 mg/kg). There was a significant difference in clearance of DAP (CL_DAP) between these groups, but no other difference in characteristics. Multiple linear regression analysis was performed for prediction of AUC ≥666 based on patient factors and the presence or absence of sepsis. In a stepwise analysis, serum creatinine (SCr) was a significant predictor of AUC, but this parameter explained only 13% of the variance in achievement of the target AUC. These results show that the target AUC/MIC may or may not be achieved at the doses used in Group_4-6 mg/kg and Group_>6 mg/kg. Receiver operating characteristic analysis suggested that a CL_DAP >0.450 L/hr may lead to failure to reach the target AUC/MIC. Therefore, regardless of dose, the efficacy of DAP should be monitored closely to prevent failure of infectious disease treatment, particularly because therapeutic drug monitoring of DAP is limited by difficulty measuring the DAP serum concentration at many medical facilities. Our findings are preliminary, and a further study is required to identify factors that increase CL_DAP and to enable dose adjustment of DAP.

Effects of a rifampicin pre-treatment on linezolid pharmacokinetics.

Linezolid is an oxazolidinone antibiotic that effectively treats methicillin-resistant Staphylococcus aureus (MRSA) and vancomycin-resistant Enterococci (VRE). Since rifampicin induces other antibiotic effects, it is combined with linezolid in therapeutic regimes. However, linezolid blood concentrations are reduced by this combination, which increases the risk of the emergence of antibiotic-resistant bacteria. We herein demonstrated that the combination of linezolid with rifampicin inhibited its absorption and promoted its elimination, but not through microsomal enzymes. Our results indicate that the combination of linezolid with rifampicin reduces linezolid blood concentrations via metabolic enzymes.

Pharmacokinetics, toxicity and clinical efficacy of linezolid in Japanese pediatric patients.

OBJECTIVES: The aims of the present study were (a) to evaluate the pharmacokinetics of linezolid, and (b) to assess the toxicity and clinical efficacy of linezolid in Japanese pediatric patients. PATIENTS AND METHODS: Routine clinical data including serum linezolid total and unbound concentrations were collected from 15 pediatric patients (0-13 years old). Pharmacokinetics of linezolid was assumed to follow one-compartment with the first-order absorption model. The relationship between risk for thrombocytopenia and linezolid concentrations, and the variations in C-reactive protein (CRP) concentrations and body temperatures were evaluated as clinical efficacy assessment. RESULTS: Body weight (WT) and maturation of body function were significant covariates for pharmacokinetics of linezolid in pediatric patients. The elimination half-life of linezolid in a pediatric patient with a WT of 9.9 kg and age of 24 months (median of this study) was 3.0 h. Thrombocytopenia was detected in three patients (21.4%), and the minimum concentrations (Cmin) in these patients were significantly higher than those in patients without thrombocytopenia (P < 0.05). The CRP concentrations decreased more than 50% in all pediatric patients after the treatment with linezolid, however body temperatures at the end of treatment were higher than 37.5 °C in 6 patients (42.9%). CONCLUSIONS: Although dose adjustment based on body size was performed for pediatric patients, thrombocytopenia was detected in 21.4% of pediatric patients, and higher Cmin was associated with the risk of thrombocytopenia. These results encourage the implementation of individual dose adjustment based on linezolid serum concentrations for safe and appropriate treatment with linezolid.

Population Pharmacokinetics and Exposure-Response of Lithium Carbonate in Patients Based on Tubular Reabsorption Mechanisms.

BACKGROUND AND OBJECTIVE: Lithium, which is used to treat bipolar disorder, has a narrow therapeutic blood concentration range and quickly reaches clinically toxic levels. We performed a population pharmacokinetic analysis with a lithium tubular reabsorption model including urinary pH and investigated the relationship between blood lithium concentration and tremor as a side effect. METHODS: Routine clinical data, including 389 serum concentrations, were collected from 214 patients orally administered an adjusted amount of lithium carbonate. Pharmacokinetics were described using a one-compartment distribution model with first-order absorption and elimination. The fractions of the MID (Li+ + LiCO3-) and ION (2Li+ + CO32-) forms were calculated using the Henderson-Hasselbalch equation, and the influences of these fractions on clearance (CL) were evaluated. The rate of tremor development was analyzed using a logit model. RESULTS: Oral apparent CL (CL/F) was explained by nonrenal CL and renal CL, and renal CL was varied by the fractions of lithium forms influenced by urinary pH. The contribution of MID to CL was slightly larger than that of ION. The rate of tremor development was estimated to be more than 30% when the trough lithium concentration was greater than 1.26 mEq L-1. CONCLUSION: Renal function and urinary pH are important indices in lithium treatment, so the serum concentration of lithium may be predicted based on the renal function and urinary pH.

Daptomycin-induced Eosinophilic Pneumonia and a Review of the Published Literature.

A 53-year-old man was admitted to the hospital with a diagnosis of cellulitis and osteomyelitis. Twenty-four days after the initiation of daptomycin and sulbactam/ampicillin, he developed a fever and pulmonary infiltration. Bronchoalveolar lavage revealed a high number of eosinophils, while an intracutaneous test revealed positivity for daptomycin. The patient improved after discontinuing antimicrobial therapy. The plasma daptomycin minimum concentration (Cmin) was elevated (27.4 µg/mL), but plasma protein binding of daptomycin was low (87.8%). Although the pathophysiology of eosinophilic pneumonia remains unclear, antigenic stimulation due to daptomycin accumulation in the alveoli may have caused continuous immune activation.

Population pharmacokinetics and pharmacodynamics of linezolid-induced thrombocytopenia in hospitalized patients.

AIMS: Thrombocytopenia is among the most important adverse effects of linezolid treatment. Linezolid-induced thrombocytopenia incidence varies considerably but has been associated with impaired renal function. We investigated the pharmacodynamic mechanism (myelosuppression or enhanced platelet destruction) and the role of impaired renal function (RF) in the development of thrombocytopenia. METHODS: The pharmacokinetics of linezolid were described with a two-compartment distribution model with first-order absorption and elimination. RF was calculated using the expected creatinine clearance. The decrease platelets by linezolid exposure was assumed to occur by one of two mechanisms: inhibition of the formation of platelets (PDI) or stimulation of the elimination (PDS) of platelets. RESULTS: About 50% of elimination was found to be explained by renal clearance (normal RF). The population mean estimated plasma protein binding of linezolid was 18% [95% confidence interval (CI) 16%, 20%] and was independent of the observed concentrations. The estimated mixture model fraction of patients with a platelet count decreased due to PDI was 0.97 (95% CI 0.87, 1.00), so the fraction due to PDS was 0.03. RF had no influence on linezolid pharmacodynamics. CONCLUSION: We have described the influence of weight, renal function, age and plasma protein binding on the pharmacokinetics of linezolid. This combined pharmacokinetic, pharmacodynamic and turnover model identified that the most common mechanism of thrombocytopenia associated with linezolid is PDI. Impaired RF increases thrombocytopenia by a pharmacokinetic mechanism. The linezolid dose should be reduced in RF.

Evaluation of pharmacokinetics and the stability of daptomycin in serum at various temperatures.

BACKGROUND: Daptomycin exhibits concentration-dependent antibacterial activity. By monitoring daptomycin serum concentrations, clinicians may be able to predict the effectiveness of treatments for infections more accurately. However, it has been reported that daptomycin concentrations in plasma samples stored at -20°C decrease approximately 25% after 4 weeks. The aim of this study was to evaluate the stability of daptomycin in serum at various temperatures. METHODS: Daptomycin serum samples were prepared and stored at different temperatures. The stability of daptomycin under various conditions was evaluated by sequential measurements of concentration. RESULTS: Although the loss of concentration of daptomycin in serum samples stored in freezers (-80°C and -20°C) was less than 10% after 168days (6 months), the concentrations in samples stored in a refrigerator (4°C) decreased by more than 70% over the same period. Furthermore, daptomycin concentrations in serum samples stored at close to body temperature (35°C, 37°C, and 39°C) decreased by more than 50% after only 24h. CONCLUSIONS: The results of the present study demonstrate that the measurement of serum concentrations of daptomycin needs to be performed rapidly. Furthermore, the degradation of daptomycin in serum may be involved in its elimination from the living body.