Comparison of daptomycin and glycopeptide efficacy and safety for the treatment of Gram-positive infections: a systematic review and meta-analysis.

BACKGROUND: The indications of daptomycin have been extended to off-label indications including prosthesis-related infection, and bone and joint infection (BJI). However, efficacy and safety have not been thoroughly demonstrated compared with the standard of care. This systematic review and meta-analysis aimed to compare the treatment effect of daptomycin and glycopeptides for complicated infections. MATERIALS AND METHODS: MEDLINE, Embase and Web of Science were searched for randomized controlled trials (RCTs) comparing daptomycin and standard of care for Gram-positive infections, published until 30 June 2021. The primary outcome was defined as all-cause mortality. Secondary outcomes were clinical and microbiological success. The main safety outcome was any severe adverse event (SAE) (grade  ≥3). RESULTS: Overall, eight RCTs were included in the meta-analysis, totalling 1095 patients. Six (75%) were in complicated skin and soft-structure infections, one (12.5%) in bacteraemia and one (12.5%) in a BJI setting. Six RCTs used vancomycin as a comparator and two used either vancomycin or teicoplanin. All-cause mortality and clinical cure were not different between groups. The microbiological cure rate was superior in patients who received daptomycin [risk ratio (RR) = 1.17 (95% CI: 1.01-1.35)]. The risk of SAEs [RR = 0.57 (95% CI: 0.36-0.90)] was lower in the daptomycin arm. CONCLUSIONS: While daptomycin is associated with a significantly lower risk of SAEs and a better microbiological eradication, substantial uncertainty remains about the best treatment strategy in the absence of good-quality evidence, especially in bacteraemia and endocarditis where further RCTs should be conducted.

Daptomycin Exposure as a Risk Factor for Daptomycin-Induced Eosinophilic Pneumonia and Muscular Toxicity.

BACKGROUND: High-dose daptomycin is increasingly used in patients with bone and joint infection (BJI). This raises concerns about a higher risk of adverse events (AEs), including daptomycin-induced eosinophilic pneumonia (DIEP) and myotoxicity. We aimed to examine pharmacokinetic and other potential determinants of DIEP and myotoxicity in patients with BJI receiving daptomycin. METHODS: All patients receiving daptomycin for BJI were identified in a prospective cohort study. Cases were matched at a 1:3 ratio, with controls randomly selected from the same cohort. Bayesian estimation of the daptomycin daily area under the concentration-time curve over 24 hours (AUC24h) was performed with the Monolix software based on therapeutic drug monitoring (TDM) data. Demographic and biological data were also collected. Risk factors of AEs were analyzed using Cox proportional hazards model. RESULTS: From 1130 patients followed over 7 years, 9 with DIEP, 26 with myotoxicity, and 106 controls were included in the final analysis. Daptomycin AUC24h, C-reactive protein, and serum protein levels were associated with the risk of AEs. The adjusted hazard ratio of DIEP or myotoxicity was 3.1 (95% confidence interval [CI], 1.48-6.5; P < .001) for daptomycin AUC24h > 939 mg/h/L, 9.8 (95% CI, 3.94-24.5; P < .001) for C-reactive protein > 21.6 mg/L, and 2.4 (95% CI, 1.02-5.65; P = .04) for serum protein <72 g/L. CONCLUSIONS: We identified common determinants of DIEP and myotoxicity in patients with BJI. Because the risk of AEs was associated with daptomycin exposure, daptomycin TDM and model-informed precision dosing may help optimize the efficacy and safety of daptomycin treatment in this setting. A target AUC24h range of 666 to 939 mg/h/L is suggested.

Evaluation of Renal Impairment Influence on Metabolic Drug Clearance using a Modelling Approach.

BACKGROUND AND OBJECTIVE: Chronic kidney disease (CKD) may alter drug renal elimination but is also known for interacting with hepatic metabolism via multiple uremic components. However, few global models, considering the five major cytochromes, have been published, and none specifically address the decrease in cytochrome P450 (CYP450) activity. The aim of our study was to estimate the possibility of quantifying residual cytochrome activity as a function of filtration rate, according to the data available in the literature. METHODS: For each drug in the DDI-predictor database, we collected available pharmacokinetic data comparing drug exposition in the healthy patient and in various stages of CKD, before building a model capable of predicting the variation of exposure according to the degree of renal damage. We followed an In vivo Mechanistic Static Model (IMSM) approach, previously validated for predicting change in liver clearance. We estimated the remaining fraction parameters at glomerular filtration rate (GFR) = 0 and the alpha value of GFR to 50% impairment for the 5 major cytochromes using a non-linear constrained regression using Matlab software. RESULTS: Thirty-one compounds had usable pharmacokinetic data, with 51 AUC ratios between healthy and renal impaired patients. The remaining CYP3A4 activity was estimated to be 0.4 when CYP2D6, 2C9, 2C19 and 1A2 activity was estimated to be 0.43; 1; 0.73 and 0.7, respectively. The alpha value was estimated to be at 6.62; 25; 9.8; 1.38 and 11.04 for each cytochrome. In comparison with published data, all estimates but one were correctly predicted in the range of 0.5-2. CONCLUSION: Our approach was able to describe the impact of CKD on metabolic elimination. Modelling this process makes it possible to anticipate changes in clearance and drug exposure in CKD patients, with the advantage of greater simplicity than approaches based on physiologically-based pharmacokinetic modelling. However, a precise estimation of the impact of renal failure is not possible with an IMSM approach due to the large variability of the published data, and thus should rely on specific pharmacokinetic modelling for narrow therapeutic margin drugs.

Machine-Learning Exploration of Exposure-Effect Relationships of Cisplatin in Head and Neck Cancer Patients.

BACKGROUND: Cisplatin is a pivotal drug in the treatment of head and neck cancer, and personalized dosage should help the preservation of an optimal toxicity-efficacy ratio. METHODS: We analyzed the exposure-effect relationships of 80 adult patients with head and neck cancers and treated with standard Cisplatin-based regimen administered as three-hour infusion. Individual pharmacokinetics (PK) parameters of Cisplatin were identified using a Bayesian approach. Nephrotoxicity and ototoxicity were considered as typical Cisplatin-related toxicities according to Common Terminology Criteria for Adverse Events (CTCAE) standards. Efficacy was evaluated based upon Response Evaluation Criteria in Solid Tumors (RECIST) criteria. Up to nine different machine-learning algorithms were tested to decipher the exposure-effect relationships with Cisplatin. RESULTS: The generalized linear model was the best algorithm with an accuracy of 0.71, a recall of 0.55 and a precision of 0.75. Among the various metrics for exposure (i.e., maximal concentration (Cmax), area-under-the-curve (AUC), trough levels), Cmax, comprising a range between 2.4 and 4.1 µg/mL, was the best one to be considered. When comparing a consequent, model-informed dosage with the standard dosage in 20 new patients, our strategy would have led to a reduced dosage in patients who would eventually prove to have severe toxicities while increasing dosage in patients with progressive disease. CONCLUSION: Determining a target Cmax could pave the way for PK-guided precision dosage with Cisplatin given as three-hour infusion.

An Investigation of O-Demethyl Tramadol/Tramadol Ratio for Cytochrome P450 2D6 Phenotyping: The CYTRAM Study.

Cytochrome P450 2D6 (CYP2D6) gene polymorphisms influence the exposure to tramadol (T) and its pharmacologically active metabolite, O-demethyl tramadol (O-dT). Tramadol has been considered as a candidate probe drug for CYP2D6 phenotyping. The objective of the CYTRAM study was to investigate the value of plasma O-dT/T ratio for CYP2D6 phenotyping. European adult patients who received IV tramadol after surgery were included. CYP2D6 genotyping was performed and subjects were classified as extensive (EM), intermediate (IM), poor (PM), or ultra-rapid (UM) CYP2D6 metabolizers. Plasma concentrations of tramadol and O-dT were determined at 24 h and 48 h. The relationship between O-dT/T ratio and CYP2D6 phenotype was examined in both a learning and a validation group. Genotype data were obtained in 301 patients, including 23 PM (8%), 117 IM (39%), 154 EM (51%), and 7 UM (2%). Tramadol trough concentrations at 24 h were available in 297 patients. Mean value of O-dT/T ratio was significantly lower in PM than in non-PM individuals (0.061 ± 0.031 versus 0.178 ± 0.09, p < 0.01). However, large overlap was observed in the distributions of O-dT/T ratio between groups. Statistical models based on O-dT/T ratio failed to identify CYP2D6 phenotype with acceptable sensitivity and specificity. Those results suggest that tramadol is not an adequate probe drug for CYP2D6 phenotyping.

Implementation of Model-Based Dose Adjustment of Tobramycin in Adult Patients with Cystic Fibrosis.

Therapeutic drug monitoring (TDM) of tobramycin is widely performed in patients with cystic fibrosis (CF), but little is known about the value of model-informed precision dosing (MIPD) in this setting. We aim at reporting our experience with tobramycin MIPD in adult patients with CF. We analyzed data from adult patients with CF who received IV tobramycin and had model-guided TDM during the first year of implementation of MIPD. The predictive performance of a pharmacokinetic (PK) model was assessed. Observed maximal (Cmax) and minimal (Cmin) concentrations after initial dosing were compared with target values. We compared the initial doses and adjusted doses after model-based TDM, as well as renal function at the beginning and end of therapy. A total of 78 tobramycin courses were administered in 61 patients. After initial dosing set by physicians (mean, 9.2 ± 1.4 mg/kg), 68.8% of patients did not achieve the target Cmax ≥ 30 mg/L. The PK model fit the data very well, with a median absolute percentage error of 4.9%. MIPD was associated with a significant increase in tobramycin doses (p < 0.001) without significant change in renal function. Model-based dose suggestions were wellaccepted by the physicians and the expected target attainment for Cmax was 83%. To conclude, the implementation of MIPD was effective in changing prescribing practice and was not associated with nephrotoxic events in adult patients with CF.

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.

Pharmacokinetic/Pharmacodynamic Simulations of Cost-Effective Dosage Regimens of Ceftolozane-Tazobactam and Ceftazidime-Avibactam in Patients with Renal Impairment.

The pharmacokinetics of ceftolozane-tazobactam (TOL-TAZ) and ceftazidime-avibactam (CEF-AVI) is influenced by renal function. Application of recommended dosages in patients with renal impairment requires the use of fractions of the full dose, as only one dosage is available for both antibiotics. The objective of this study was to evaluate the adequacy of alternative dosage regimens based on the full dose. We performed pharmacokinetic/pharmacodynamic (PK/PD) simulations of recommended and alternative dosage regimens in patients with various degrees of renal impairment by using the Pmetrics program. Alternative regimens included longer dosage interval and prolonged infusions of the full dose for both drugs. Probabilities of target attainment (PTA) were assessed considering PK/PD targets defined for cephalosporins and beta-lactamase inhibitors as well as MIC breakpoints. The risk of overexposure was also assessed. Results showed that alternative dosage regimens based on a full dose of TOL-TAZ and CEF-AVI administered every 12 or 24 h were associated with PTA similar to that of recommended dosages, especially when administered as prolonged infusion. The alternative dosage regimens were not associated with overexposure in most cases. In addition, those regimens could reduce dosing errors, drug cost, and nurse labor. Clinical investigation ovf those alternative dosage regimens would be required before implementation.

Nonparametric Methods in Population Pharmacokinetics.

Population pharmacokinetic (PK) modeling is a widely used approach to analyze PK data obtained from groups of individuals, in both industry and academic research. The approach can also be used to analyze pharmacodynamic (PD) data and pooled PK/PD data. There are 2 main families of population PK methods: parametric and nonparametric. The objectives of this article are to present an overview of nonparametric methods used in population pharmacokinetic modeling and to explain their specific characteristics to inform scientists and clinicians about their potential value for data analysis, simulation, dosage design, and therapeutic drug monitoring (TDM). Nonparametric methods have several interesting characteristics for population PK analysis, including computation of exact likelihoods, the ability to accommodate parameter probability distributions of any shape (eg, non-Gaussian), and to detect subpopulations and outliers. Nonparametric population methods are also highly relevant for model-based TDM and design of individualized drug dosage regimens. Several algorithms have been developed to estimate model parameter values within an individual and compute that individual's dosage to achieve target drug exposure with maximum precision and accuracy. Nonparametric modeling methods for both population and individual PK analysis are available under user-friendly packages.

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

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

Population Pharmacokinetics and Dosing Simulation of Vancomycin Administered by Continuous Injection in Critically Ill Patient.

Background: Vancomycin is widely used for empirical antimicrobial therapy in critically ill patients with sepsis. Continuous infusion (CI) may provide more stable exposure than intermittent infusion, but optimal dosing remains challenging. The aims of this study were to perform population pharmacokinetic (PK) analysis of vancomycin administered by CI in intensive care unit (ICU) patients to identify optimal dosages. Methods: Patients who received vancomycin by CI with at least one measured concentration in our center over 16 months were included, including those under continuous renal replacement therapy (CRRT). Population PK was conducted and external validation of the final model was performed in a dataset from another center. Simulations were conducted with the final model to identify the optimal loading and maintenance doses for various stages of estimated creatinine clearance (CRCL) and in patients on CRRT. Target exposure was defined as daily AUC of 400-600 mg·h/L on the second day of therapy (AUC24-48 h). Results: A two-compartment model best described the data. Central volume of distribution was allometrically scaled to ideal body weight (IBW), whereas vancomycin clearance was influenced by CRRT and CRCL. Simulations performed with the final model suggested a loading dose of 27.5 mg/kg of IBW. The maintenance dose ranged from 17.5 to 30 mg/kg of IBW, depending on renal function. Overall, simulation showed that 55.8% (95% CI; 47-64%) of patients would achieve the target AUC with suggested dosages. Discussion: A PK model has been validated for vancomycin administered by CI in ICU patients, including patients under CRRT. Our model-informed precision dosing approach may help for early optimization of vancomycin exposure in such patients.

How a Patient Personalised Clinical Pharmacy Programme Can Secure Therapeutic Care in an Orthogeriatric Care Pathway (5P Project)?

BACKGROUND: A new model was developed for integrating a personalised clinical pharmacy programme (5P project) into the orthogeriatric care pathway. OBJECTIVE: To secure the therapeutic care of orthogeriatric patients. DESIGN AND SETTING: Prospective descriptive study in a multisite teaching hospital from June 2019 to January 2020. SUBJECTS: Patients aged ≥75 years admitted for hip fracture. METHODS: A prescription review was performed for all patients at inclusion. Other clinical pharmacy activities (additional prescription review, pharmaceutical interviews, medication reconciliation) were dedicated to "high-risk" patients. Potential medication errors (ME), either pharmaceutical interventions (PI) or unintentional discrepancies (UID), were recorded. The potential clinical impact of PI was evaluated by a pluriprofessional expert panel using a validated tool. RESULTS: In the 455 patients included, 955 potential ME were detected, that is ≥1 potential ME for 324/455 (71%) patients. In acute care, 561 PI were formulated during prescription review for 440/455 (97%) patients and 348/561 (62%) were accepted by physicians. Medication reconciliation was performed for 213 patients, 316 UID were identified. In rehabilitation units, a second prescription review was performed for 112/122 (92%) "high-risk" patients, leading to 61 PI. The clinical impact was evaluated for 519/622 (83%) PI. A consensus was obtained for 310/519 (60%) PI: 147/310 (47%) were rated as having minor clinical impact, 138/310 (45%) moderate, 22/310 (7%) major, 2/310 (0.6%) vital, and 1/310 (0.3%) null. CONCLUSION: The 5P project secured the orthogeriatric care pathway by detecting a great number of potential ME, including PI mostly considered as having a significant clinical impact.

Population Pharmacokinetic Modeling and Dosing Simulations of Tobramycin in Pediatric Patients with Cystic Fibrosis.

Initial dosing and dose adjustment of intravenous tobramycin in children with cystic fibrosis (CF) is challenging. The objectives of this study were to develop nonparametric population pharmacokinetic (PK) models of tobramycin in children with CF to be used for dosage design and model-guided therapeutic drug monitoring. We performed a retrospective analysis of tobramycin PK data in our children's CF center. The Pmetrics package was used for nonparametric population PK analysis and dosing simulations. Both the ratios of maximal concentration to the MIC (Cmax/MIC) and daily area under the concentration-time curve to the MIC (AUC24/MIC) were considered efficacy targets. Trough concentration (Cmin) was considered the safety target. A total of 2,884 tobramycin concentrations collected in 195 patients over 9 years were analyzed. A two-compartment model including total body weight, body surface area, and creatinine clearance as covariates best described the data. A simpler model was also derived for implementation in the BestDose software to perform Bayesian dose adjustment. Both models were externally validated. PK/pharmacodynamics (PD) simulations with the final model suggest that an initial dose of tobramycin of 15 to 17.5 mg/kg/day was necessary to achieve Cmax/MICs of ≥10 for MICs up to 2 mg/liter in most patients. The AUC24/MIC target was associated with higher dosage requirements and higher Cmin. A daily dose of 12.5 mg/kg would optimize both efficacy and safety target attainment. We recommend performing tobramycin therapeutic drug monitoring (TDM), model-based dose adjustment, and MIC determination to individualize intravenous tobramycin therapy in children with CF.

Model-Based Comparative Analysis of Rifampicin and Rifabutin Drug-Drug Interaction Profile.

Rifamycins are widely used for treating mycobacterial and staphylococcal infections. Drug-drug interactions (DDI) caused by rifampicin (RIF) are a major issue. We used a model-based approach to predict the magnitude of DDI with RIF and rifabutin (RBT) for 217 cytochrome P450 (CYP) substrates. On average, DDI caused by low-dose RIF were twice as potent as those caused by RBT. Contrary to RIF, RBT appears unlikely to cause severe DDI, even with sensitive CYP substrates.

To Estimate or to Forecast? Lessons From a Comparative Analysis of Four Bayesian Fitting Methods Based on Nonparametric Models.

ABSTRACT: Using pharmacokinetic (PK) models and Bayesian methods in dosing software facilitates the analysis of individual PK data and precision dosing. Several Bayesian methods are available for computing Bayesian posterior distributions using nonparametric population models. The objective of this study was to compare the performance of the maximum a posteriori (MAP) model, multiple model (MM), interacting MM (IMM), and novel hybrid MM(HMM) in estimating past concentrations and predicting future concentrations during therapy. Amikacin and vancomycin PK data were analyzed in older hospitalized patients using 2 strategies. First, the entire data set of each patient was fitted using each of the 4 methods implemented in BestDose software. Then, the 4 methods were used in each therapeutic drug monitoring occasion to estimate the past concentrations available at this time and to predict the subsequent concentrations to be observed on the next occasion. The bias and precision of the model predictions were compared among the methods. A total of 406 amikacin concentrations from 96 patients and 718 vancomycin concentrations from 133 patients were available for analysis. Overall, significant differences were observed in the predictive performance of the 4 Bayesian methods. The IMM method showed the best fit to past concentration data of amikacin and vancomycin, whereas the MM method was the least precise. However, MM best predicted the future concentrations of amikacin. The MAP and HMM methods showed a similar predictive performance and seemed to be more appropriate for the prediction of future vancomycin concentrations than the other models were. The richness of the prior distribution may explain the discrepancies between the results of the 2 drugs. Although further research with other drugs and models is necessary to confirm our findings, these results challenge the widely accepted assumption in PK modeling that a better data fit indicates better forecasting of future observations.

Pharmacokinetic/Pharmacodynamic Dosage Individualization of Cefepime in Critically Ill Patients: A Case Study.

OBJECTIVE: The authors report on a case of a 59-year-old man hospitalized in the intensive care unit because of severe SARS-COV-2 infection (COVID-19). BACKGROUND: The patient had several comorbidities, including liver cirrhosis. He developed ventilation-associated bacterial pneumonia for which he was administered cefepime at an initial dose of 2 g/8 hours. Therapeutic drug monitoring was performed, showing overexposure with an initial trough concentration of >60 mg/L. METHODS: Analysis of pharmacokinetic data and model-based dose adjustment was performed using BestDose software. RESULTS: The patient had unexpected pharmacokinetic parameter values. Serum creatinine was only moderately increased, whereas measured creatinine clearance based on urine collection showed impaired renal function. Bacterial minimum inhibitory concentration was also considered in the dosing decisions. After dose reduction to 0.5 g/8 hours, the cefepime trough concentration progressively declined and reached the target values by the end of the therapy. A post-hoc analysis provided a different interpretation of drug overexposure. CONCLUSION: This case report illustrates how physiological, microbiological, and drug concentration data can be used for model-based dosage individualization of cefepime in intensive care unit patients.

Pharmacogenetic-guided glimepiride therapy in type-2 diabetes mellitus: a cost-effectiveness study.

The demonstration of the link between certain genetic variations and drug response has allowed the emergence of pharmacogenetics, which offers many opportunities to improve patient care. Type-2 diabetes mellitus is a disease for which several gene polymorphisms have been reported to be associated with drug response. Sulfonylureas are commonly used for the management of this disease. Genetic polymorphisms of CYP2C9, the main enzyme involved in the metabolism of sulfonylureas, have been associated with the risk of severe hypoglycaemia, particularly in poor metabolizers carrying CYP2C9 *3/*3 genotype, and especially in the case of patients treated with glimepiride. The objectives of the present study were to evaluate the potential clinical and economic outcomes of using CYP2C9 genotype data to guide the management of SU regimen in patients initiating glimepiride therapy, and to identify factors affecting the cost-effectiveness of this treatment scheme. The analysis was conducted using a decision tree, considering a 1-year time horizon, and taking as perspective that of the French national health insurance system. With pharmacogenetic-guided therapy, the cost to avoid an episode of severe hypoglycaemia event per 100 000 patients treated was €421 834. Genotyping cost was the most influential factor on the incremental cost-effectiveness ratio. In conclusion, the potential cost of CYP2C9 genotype-guided dosing for glimepiride therapy is relatively high, and associated with modest improvements with respect to the number of hypoglycaemia avoided, as compared with standard dosing. Additional economic studies are required to better specify the usefulness of CYP2C9 genotyping prior to glimepiride regimen initiation.

Population pharmacokinetics of daptomycin in patients with bone and joint infection: minimal effect of rifampicin co-administration and confirmation of a sex difference.

BACKGROUND: Daptomycin is increasingly used in the treatment of bone and joint infection (BJI), but its pharmacokinetics (PK) and dosage requirements have not been thoroughly investigated in this indication. Daptomycin may be co-administered with rifampicin, which raises questions about a potential drug interaction. OBJECTIVES: To investigate the population PK and dosage requirements of daptomycin in patients with BJI, and examine the influence of rifampicin co-administration. METHODS: A population approach was used to analyse PK data from patients who received daptomycin in our regional reference for BJI. We examined the influence of available covariates, including rifampicin co-administration on daptomycin PK. Simulations performed with the final model investigated the influence of dosages and covariates on PTA for both efficacy and safety. RESULTS: A total of 1303 daptomycin concentrations from 183 patients were analysed. A two-compartment model best described the data. Significant intra-individual variability was observed. Daptomycin clearance was influenced by renal function and sex, with females having a 26% lower typical clearance than males. Central volume of distribution (V1) was influenced by body weight, age, sex and rifampicin co-administration. Typical V1 was 11% lower in patients who were co-administered rifampicin. In PK/PD simulations, sex influenced the probability of AUC24/MIC target attainment, while rifampicin had a marginal effect. CONCLUSIONS: A daptomycin dosage of 8 mg/kg/24 h in women and 10 mg/kg/24 h in men should optimize efficacy but may lead to excessive trough concentrations in many patients, especially in women. Therapeutic drug monitoring appears necessary for precision dosing of daptomycin.