A physiological approach to renal clearance: From premature neonates to adults.

AIMS: We propose using glomerular filtration rate (GFR) as the physiological basis for distinguishing components of renal clearance. METHODS: Gentamicin, amikacin and vancomycin are thought to be predominantly excreted by the kidneys. A mixed-effects joint model of the pharmacokinetics of these drugs was developed, with a wide dispersion of weight, age and serum creatinine. A dataset created from 18 sources resulted in 27,338 drug concentrations from 9,901 patients. Body size and composition, maturation and renal function were used to describe differences in drug clearance and volume of distribution. RESULTS: This study demonstrates that GFR is a predictor of two distinct components of renal elimination clearance: (1) GFR clearance associated with normal GFR and (2) non-GFR clearance not associated with normal GFR. All three drugs had GFR clearance estimated as a drug-specific percentage of normal GFR (gentamicin 39%, amikacin 90% and vancomycin 57%). The total clearance (sum of GFR and non-GFR clearance), standardized to 70 kg total body mass, 176 cm, male, renal function 1, was 5.58 L/h (95% confidence interval [CI] 5.50-5.69) (gentamicin), 7.77 L/h (95% CI 7.26-8.19) (amikacin) and 4.70 L/h (95% CI 4.61-4.80) (vancomycin). CONCLUSIONS: GFR provides a physiological basis for renal drug elimination. It has been used to distinguish two elimination components. This physiological approach has been applied to describe clearance and volume of distribution from premature neonates to elderly adults with a wide dispersion of size, body composition and renal function. Dose individualization has been implemented using target concentration intervention.

Use of Machine Learning for Dosage Individualization of Vancomycin in Neonates.

BACKGROUND AND OBJECTIVE: High variability in vancomycin exposure in neonates requires advanced individualized dosing regimens. Achieving steady-state trough concentration (C0) and steady-state area-under-curve (AUC0-24) targets is important to optimize treatment. The objective was to evaluate whether machine learning (ML) can be used to predict these treatment targets to calculate optimal individual dosing regimens under intermittent administration conditions. METHODS: C0 were retrieved from a large neonatal vancomycin dataset. Individual estimates of AUC0-24 were obtained from Bayesian post hoc estimation. Various ML algorithms were used for model building to C0 and AUC0-24. An external dataset was used for predictive performance evaluation. RESULTS: Before starting treatment, C0 can be predicted a priori using the Catboost-based C0-ML model combined with dosing regimen and nine covariates. External validation results showed a 42.5% improvement in prediction accuracy by using the ML model compared with the population pharmacokinetic model. The virtual trial showed that using the ML optimized dose; 80.3% of the virtual neonates achieved the pharmacodynamic target (C0 in the range of 10-20 mg/L), much higher than the international standard dose (37.7-61.5%). Once therapeutic drug monitoring (TDM) measurements (C0) in patients have been obtained, AUC0-24 can be further predicted using the Catboost-based AUC-ML model combined with C0 and nine covariates. External validation results showed that the AUC-ML model can achieve an prediction accuracy of 80.3%. CONCLUSION: C0-based and AUC0-24-based ML models were developed accurately and precisely. These can be used for individual dose recommendations of vancomycin in neonates before treatment and dose revision after the first TDM result is obtained, respectively.

Drug Clearance in Neonates: A Combination of Population Pharmacokinetic Modelling and Machine Learning Approaches to Improve Individual Prediction.

BACKGROUND: Population pharmacokinetic evaluations have been widely used in neonatal pharmacokinetic studies, while machine learning has become a popular approach to solving complex problems in the current era of big data. OBJECTIVE: The aim of this proof-of-concept study was to evaluate whether combining population pharmacokinetic and machine learning approaches could provide a more accurate prediction of the clearance of renally eliminated drugs in individual neonates. METHODS: Six drugs that are primarily eliminated by the kidneys were selected (vancomycin, latamoxef, cefepime, azlocillin, ceftazidime, and amoxicillin) as 'proof of concept' compounds. Individual estimates of clearance obtained from population pharmacokinetic models were used as reference clearances, and diverse machine learning methods and nested cross-validation were adopted and evaluated against these reference clearances. The predictive performance of these combined methods was compared with the performance of two other predictive methods: a covariate-based maturation model and a postmenstrual age and body weight scaling model. Relative error was used to evaluate the different methods. RESULTS: The extra tree regressor was selected as the best-fit machine learning method. Using the combined method, more than 95% of predictions for all six drugs had a relative error of < 50% and the mean relative error was reduced by an average of 44.3% and 71.3% compared with the other two predictive methods. CONCLUSION: A combined population pharmacokinetic and machine learning approach provided improved predictions of individual clearances of renally cleared drugs in neonates. For a new patient treated in clinical practice, individual clearance can be predicted a priori using our model code combined with demographic data.

Do Vancomycin Pharmacokinetics Differ Between Obese and Non-obese Patients? Comparison of a General-Purpose and Four Obesity-Specific Pharmacokinetic Models.

BACKGROUND: Over the past decade, numerous obesity-specific pharmacokinetic (PK) models and dosage regimens have been developed. However, it is unclear whether vancomycin PKs differ between obese and other patients after accounting for weight, age, and kidney function. In this study, the authors investigated whether using obesity-specific population PK models for vancomycin offers any advantage in accuracy and precision over using a recently developed general-purpose model. METHODS: Vancomycin plasma concentrations in a cohort of 49 obese patients (body mass index [BMI] >30 kg/m2), not previously used in the development of any of the evaluated models, were used to validate the performance of 4 obesity-specific models and a general model. Bias and imprecision were calculated for the a priori and a posteriori predictive performance. RESULTS: The bias of the a priori prediction was lowest for one of the obesity-specific models (-1.40%) and that of the general model was a close second (-7.0%). The imprecision was lowest for the general model (4.34 mg/L). The predictive performance for the a posteriori predictions was best for the general model, both for bias (1.96%) and imprecision (2.75 mg/L). CONCLUSIONS: The results of the external validation of vancomycin PK in obese patients showed that currently available obesity-specific models do not necessarily outperform a broadly supported general-purpose model. Based on these results, the authors conclude that there is no advantage in using vancomycin PK models specifically tailored to obese patients over the general-purpose model reported by Colin et al.

Population pharmacokinetic evaluation and optimization of amikacin dosage regimens for the management of mycobacterial infections.

BACKGROUND: There is limited information on amikacin pharmacokinetics (PK) and dose requirements in patients with mycobacterial infections. OBJECTIVES: To conduct a population PK analysis of amikacin data from patients with mycobacterial infections and compare predicted concentrations from standard and modified dosage guidelines with recommended target ranges. METHODS: A population PK model was developed using NONMEM. Cmax, Cmin, concentration 1 h post-infusion (C1h) and AUC0-24 using 15 mg/kg daily (once daily), the WHO table, 25 mg/kg three times weekly (TTW) and modified guidelines were compared using Monte Carlo simulations of 1000 patients. RESULTS: Data were available from 124 patients (684 concentrations) aged 16-92 years. CL was 4.64 L/h per 100 mL/min CLCR; V was 0.344 L/kg. With once-daily regimens, Cmax was 35-45 mg/L in 30%-35% of patients and 35-50 mg/L in 46%-48%; C1h was 25-40 mg/L in 53%-59%. The WHO table produced high Cmax values in patients <60 kg and low in patients >75 kg. With TTW dosing, around 30% of Cmax values were 65-80 mg/L, 40% were 60-80 mg/L, and 48% of C1h were 45-65 mg/L. Increasing the dosage interval for patients with CLCR <50 mL/min reduced Cmin values >2 mg/L from 34% to 25% for once-daily dosing and from 18% to 13% for TTW. In patients whose Cmin was <2 mg/L, 82% of AUC0-24 values were 100-300 mg.h/L. CONCLUSIONS: Standard amikacin dosing guidelines achieve low percentages of target concentrations for mycobacterial infections. Extending the dosing interval in renal impairment and widening target ranges would reduce the need for dose adjustment.

Genetic Algorithms as a Tool for Dosing Guideline Optimization: Application to Intermittent Infusion Dosing for Vancomycin in Adults.

This paper demonstrates the use of a genetic algorithm (GA) for the optimization of a dosing guideline. GAs are well-suited to derive combinations of doses and dosing intervals that go into a dosing guideline when the number of possible combinations rule out the calculation of all possible outcomes. GAs also allow for different constraints to be imposed on the optimization process to safeguard the clinical feasibility of the dosing guideline. In this work, we demonstrate the use of a GA for the optimization of intermittent vancomycin administration in adult patients. Constraints were placed on the dose strengths, the length of the dosing intervals, and the maximum infusion rate. In addition, flexibility with respect to the timing of the first maintenance dose was included in the optimization process. The GA-based optimal solution is compared with the Scottish Antimicrobial Prescribing Group vancomycin guideline.

Development and evaluation of a national gentamicin and vancomycin quality improvement programme.

BACKGROUND: Scottish Antimicrobial Prescribing Group (SAPG) recommendations to reduce broad-spectrum antimicrobial use led to an increase in gentamicin and vancomycin prescribing. In 2009, SAPG introduced national guidance to standardize dosage regimens, reduce calculation errors and improve the monitoring of these antibiotics. Studies conducted in 2010 and 2011 identified limitations in guideline implementation. OBJECTIVES: To develop, implement and assess the long-term impact of quality improvement (QI) resources to support gentamicin and vancomycin prescribing, administration and monitoring. METHODS: New resources, comprising revised guidelines, online and mobile app dose calculators, educational material and specialized prescribing and monitoring charts were developed in collaboration with antimicrobial specialists and implemented throughout Scotland during 2013-16. An online survey in 2017 evaluated the use of these resources and a before (2011) and after (2018) point prevalence study assessed their impact. RESULTS: All 12 boards who responded to the survey (80%) were using the guidance, electronic calculators and gentamicin prescription chart; 8 used a vancomycin chart. The percentage of patients who received the recommended gentamicin dose increased from 44% to 89% (OR 10.99, 95% CI = 6.37-18.95) between 2011 and 2018. For vancomycin, the correct loading dose increased from 50% to 85% (OR = 5.69, CI = 2.76-11.71) and the correct maintenance dose from 55% to 90% (OR = 7.17, CI = 3.01-17.07). CONCLUSIONS: This study demonstrated improvements in the national prescribing of gentamicin and vancomycin through the development and coordinated implementation of a range of QI resources and engagement with local and national multidisciplinary teams.

Professional development beyond foundation training: a study of pharmacists working in Scotland.

OBJECTIVES: In Scotland, post-registration hospital pharmacists typically undertake a vocational foundation training programme. Beyond this, there are no mandatory structures for ongoing professional training. To support progression to a more advanced level, competency frameworks are increasingly being used. This study aimed to measure the self-reported competence of pharmacists against a relevant framework and to determine what support was required to enable further professional development. METHODS: An online survey was completed by pharmacists working across six acute hospital sites within NHS Greater Glasgow and Clyde who had completed foundation training between Jan 2013 and Jan 2018. Participants self-reported competency against the Royal Pharmaceutical Society's Advanced Practice Framework Advanced Stage 1 competencies and gave qualitative feedback through free-text questions. KEY FINDINGS: Twenty out of twenty-eight eligible pharmacists (71.4%) responded to the survey and three core areas requiring further support were identified: leadership, management and research. Participants reported that a strategic plan for professional development, more opportunities and managerial support were needed to help them develop these areas. Mentorship programmes and postgraduate qualifications were suggested as formats to support development. CONCLUSION: Pharmacists working towards advanced practice reported high levels of competence in expert professional practice, collaborative working relationships and education, training and development. While these results are promising, additional support is likely to be needed to cultivate leadership, management and research skills. Future training strategies need to consider this imbalance if we are to achieve national and international workforce goals for the professional development of pharmacists.

Population pharmacokinetic meta-analysis of individual data to design the first randomized efficacy trial of vancomycin in neonates and young infants.

OBJECTIVES: In the absence of consensus, the present meta-analysis was performed to determine an optimal dosing regimen of vancomycin for neonates. METHODS: A 'meta-model' with 4894 concentrations from 1631 neonates was built using NONMEM, and Monte Carlo simulations were performed to design an optimal intermittent infusion, aiming to reach a target AUC0-24 of 400 mg·h/L at steady-state in at least 80% of neonates. RESULTS: A two-compartment model best fitted the data. Current weight, postmenstrual age (PMA) and serum creatinine were the significant covariates for CL. After model validation, simulations showed that a loading dose (25 mg/kg) and a maintenance dose (15 mg/kg q12h if <35 weeks PMA and 15 mg/kg q8h if ≥35 weeks PMA) achieved the AUC0-24 target earlier than a standard 'Blue Book' dosage regimen in >89% of the treated patients. CONCLUSIONS: The results of a population meta-analysis of vancomycin data have been used to develop a new dosing regimen for neonatal use and to assist in the design of the model-based, multinational European trial, NeoVanc.

Vancomycin Pharmacokinetics Throughout Life: Results from a Pooled Population Analysis and Evaluation of Current Dosing Recommendations.

BACKGROUND AND OBJECTIVES: Uncertainty exists regarding the optimal dosing regimen for vancomycin in different patient populations, leading to a plethora of subgroup-specific pharmacokinetic models and derived dosing regimens. We aimed to investigate whether a single model for vancomycin could be developed based on a broad dataset covering the extremes of patient characteristics. Furthermore, as a benchmark for current dosing recommendations, we evaluated and optimised the expected vancomycin exposure throughout life and for specific patient subgroups. METHODS: A pooled population-pharmacokinetic model was built in NONMEM based on data from 14 different studies in different patient populations. Steady-state exposure was simulated and compared across patient subgroups for two US Food and Drug Administration/European Medicines Agency-approved drug labels and optimised doses were derived. RESULTS: The final model uses postmenstrual age, weight and serum creatinine as covariates. A 35-year-old, 70-kg patient with a serum creatinine level of 0.83 mg dL-1 (73.4 µmol L-1) has a V1, V2, CL and Q2 of 42.9 L, 41.7 L, 4.10 L h-1 and 3.22 L h-1. Clearance matures with age, reaching 50% of the maximal value (5.31 L h-1 70 kg-1) at 46.4 weeks postmenstrual age then declines with age to 50% at 61.6 years. Current dosing guidelines failed to achieve satisfactory steady-state exposure across patient subgroups. After optimisation, increased doses for the Food and Drug Administration label achieve consistent target attainment with minimal (± 20%) risk of under- and over-dosing across patient subgroups. CONCLUSIONS: A population model was developed that is useful for further development of age and kidney function-stratified dosing regimens of vancomycin and for individualisation of treatment through therapeutic drug monitoring and Bayesian forecasting.

Development of a LC-MS method for simultaneous determination of amoxicillin and metronidazole in human serum using hydrophilic interaction chromatography (HILIC).

A method was developed for the determination of amoxicillin and metronidazole in human serum. The procedure used was hydrophilic interaction chromatography (HILIC) followed by mass spectrometric (MS) detection. Chromatographic separation was achieved on a ZIC-HILIC column and the mobile phase consisted of a mixture of 0.1% (v/v) formic acid in water and 0.1% (v/v) formic acid in acetonitrile. The method was validated with regard to selectivity, accuracy, precision, calibration, lower limit of quantification (LOQ), extraction recovery and matrix effect. The LOQs were 0.0138 and 0.008 µg/ml for amoxicillin and metronidazole respectively, while for quantification purposes linearity was achieved in the range of 0.1 µg/ml to 6.4 µg/ml for both drugs with correlation coefficients >0.9990. The intraday precision (expressed as %RSD) and the accuracy (expressed as the % deviation from the nominal value) was <15% for both antibiotics at all QC levels. Extraction recoveries for both drugs and internal standards were >80%, while a considerable matrix effect (<60%) was observed for amoxicillin. Finally, the method was applied to the determination of amoxicillin and metronidazole concentrations in serum for 20 patients.

Influence of Genotype on Warfarin Maintenance Dose Predictions Produced Using a Bayesian Dose Individualization Tool.

BACKGROUND: A previously established Bayesian dosing tool for warfarin was found to produce biased maintenance dose predictions. In this study, we aimed (1) to determine whether the biased warfarin dose predictions previously observed could be replicated in a new cohort of patients from 2 different clinical settings, (2) to explore the influence of CYP2C9 and VKORC1 genotype on predictive performance of the Bayesian dosing tool, and (3) to determine whether the previous population used to develop the kinetic-pharmacodynamic model underpinning the Bayesian dosing tool was sufficiently different from the test (posterior) population to account for the biased dose predictions. METHODS: The warfarin maintenance doses for 140 patients were predicted using the dosing tool and compared with the observed maintenance dose. The impact of genotype was assessed by predicting maintenance doses with prior parameter values known to be altered by genetic variability (eg, EC50 for VKORC1 genotype). The prior population was evaluated by fitting the published kinetic-pharmacodynamic model, which underpins the Bayesian tool, to the observed data using NONMEM and comparing the model parameter estimates with published values. RESULTS: The Bayesian tool produced positively biased dose predictions in the new cohort of patients (mean prediction error [95% confidence interval]; 0.32 mg/d [0.14-0.5]). The bias was only observed in patients requiring ≥7 mg/d. The direction and magnitude of the observed bias was not influenced by genotype. The prior model provided a good fit to our data, which suggests that the bias was not caused by different prior and posterior populations. CONCLUSIONS: Maintenance doses for patients requiring ≥7 mg/d were overpredicted. The bias was not due to the influence of genotype nor was it related to differences between the prior and posterior populations. There is a need for a more mechanistic model that captures warfarin dose-response relationship at higher warfarin doses.

Amikacin use and therapeutic drug monitoring in adults: do dose regimens and drug exposures affect either outcome or adverse events? A systematic review.

OBJECTIVES: The objectives of this study were to identify the amikacin dosage regimens and drug concentrations consistent with good outcomes and to determine the drug exposures related to nephrotoxicity and ototoxicity. METHODS: A literature review was conducted in Medline, EMBASE and the Cochrane Central Register of Controlled Trials. Full journal articles reporting randomized controlled trials, controlled clinical trials, interrupted time series trials, and controlled before and after studies involving amikacin therapeutic drug monitoring (TDM) and dose adjustment were considered for inclusion. RESULTS: Seventeen studies for inclusion were identified, comprising 1677 participants. Amikacin doses ranged from 11 to 15 mg/kg/day with 13 studies using 15 mg/kg/day. Studies were generally designed to compare different aminoglycosides rather than to assess concentration-effect relationships. Only 11 papers presented data on target concentrations, rate of clinical cure and toxicity. Target peak concentrations ranged from 15 to 40 mg/L and target troughs were typically <10 or <5 mg/L. It was not clear whether these targets were achieved. Measured peaks averaged 28 mg/L for twice-daily dosing and 40-45 mg/L for once-daily dosing; troughs averaged 5 and 1-2 mg/L, respectively. Fifteen of the included studies reported rates of nephrotoxicity; auditory and vestibular toxicities were reported in 12 and 8 studies. CONCLUSIONS: This systematic review found little published evidence to support an optimal dosage regimen or TDM targets for amikacin therapy. The use of alternative approaches, such as consensus opinion and a review of current practice, will be required to develop guidelines to maximize therapeutic outcomes and minimize toxicity with amikacin.

Dosing regimen of meropenem for adults with severe burns: a population pharmacokinetic study with Monte Carlo simulations.

OBJECTIVES: To develop a population model to describe the pharmacokinetics (PK) of intravenous meropenem in adult patients with severe burns and investigate potential relationships between dosage regimens and antimicrobial efficacy. PATIENTS AND METHODS: A dose of 1 g every 8 h was administered to adult patients with total body surface area burns of ≥15%. Doses for subsequent courses were determined using results from the initial course and the patient's clinical condition. Five plasma meropenem concentrations were typically measured over the dosage interval on one to four occasions. An open, two-compartment PK model was fitted to the meropenem concentrations using NONMEM and the effect of covariates on meropenem PK was investigated. Monte Carlo simulations investigated dosage regimens to achieve a target T>MIC for ≥40%, ≥60% or ≥80% of the dose interval. RESULTS: Data comprised 113 meropenem concentration measurements from 20 dosage intervals in 12 patients. The parameters were CL (L/h) = 0.196 L/h/kg × [1 - 0.023 × (age - 46)] × [1 - 0.049 × (albumin - 15)], V1 = 0.273 L/kg × [1 - 0.049 × (albumin - 15)], Q = 0.199 L/h/kg and V2 = 0.309 L/kg × [1 - 0.049 × (albumin - 15)]. For a target of ≥80% T>MIC, the breakpoint was 8 mg/L for doses of 1 g every 4 h and 2 g every 8 h given over 3 h, but only 4 mg/L if given over 5 min. CONCLUSIONS: Although 1 g 8 hourly should be effective against Escherichia coli and CoNS, higher doses, ideally with a longer infusion time, would be more appropriate for empirical therapy, mixed infections and bacteria with MIC values ≥4 mg/L.

Population pharmacokinetics of tobramycin in patients with and without cystic fibrosis.

BACKGROUND AND OBJECTIVES: While several studies have examined the pharmacokinetics of tobramycin in patients with cystic fibrosis (CF), there is no consensus on whether they differ in patients with and without CF. The objectives of this study were to identify covariates which explain pharmacokinetic variability and to examine whether having the disease CF in itself alters these relationships and drug dose requirements. METHODS: To investigate this issue, a population pharmacokinetic meta-analysis of data from eight centres was undertaken. NONMEM(®) 7.2 was used to analyse the data, which comprised 4,514 concentration-time measurements from 465 adults and children with CF and 1,095 concentration-time measurements from 267 adults and children without CF. RESULTS: Tobramycin disposition was well described by a two-compartment model with first-order elimination. Patient age, fat-free mass, serum creatinine concentration and sex were identified as significant covariates in the final model. Fat-free mass was superior to total bodyweight as a descriptor of clearance, volume of distribution of the central and peripheral compartments and inter-compartmental clearance. CF as an independent disease-specific factor had no significant influence on the pharmacokinetics of tobramycin at any stage during covariate model building. An optimal dose of 11 mg/kg every 24 h was defined for CF patients using a utility function approach. CONCLUSION: The pharmacokinetics of tobramycin do not differ significantly in CF patients compared with patients without CF when subject age, fat-free mass, sex and renal function are taken into consideration. Variations in tobramycin dosing between CF and non-CF patients should therefore reflect target concentrations or exposures based on differences in expected pathogen sensitivity and not the presence of CF.

Influence of multiple courses of therapy on aminoglycoside clearance in adult patients with cystic fibrosis.

OBJECTIVES: To investigate factors affecting aminoglycoside clearance in adult patients with cystic fibrosis who received multiple courses of antibiotic therapy over a period of up to 15 years. METHODS: Aminoglycoside concentration-time data and relevant clinical characteristics were collated from clinical pharmacokinetic databases established in Glasgow, Scotland and The Hague, The Netherlands. Data from Glasgow (1993-2009) were used for population model development; data from The Hague (2002-11) were used for model validation. NONMEM was used to determine structural and covariate models, with a particular focus on between-occasion variability and changes in aminoglycoside handling over multiple courses of therapy. RESULTS: The Glasgow dataset comprised 1075 courses of aminoglycoside therapy (96% tobramycin and 4% gentamicin) in 166 patients and included 2238 concentration measurements. The data were best described by a two-compartment model with creatinine clearance and height influencing aminoglycoside clearance, and height influencing volume of distribution. Between-subject and between-occasion variabilities in clearance were low, at 18% and 11%, respectively; between-subject variability was 12% for volume of distribution. Internal and external model validations were satisfactory. Multiple courses of therapy (ranging from 2 to 28 courses per patient) were not associated with any systematic changes in aminoglycoside clearance. CONCLUSIONS: Height was a better descriptor of aminoglycoside pharmacokinetics than weight in adult patients with cystic fibrosis. No changes in clearance were observed over time, even in patients who had received multiple courses of therapy over several years.

Pharmacokinetic profiles of epidural bupivacaine and ropivacaine following single-shot and continuous epidural use in young infants.

AIMS: The primary aim of this study was to describe the pharmacokinetics of total and unbound bupivacaine and ropivacaine following epidural bolus and infusion in neonates and young infants. Secondary aims were to investigate the influence of alpha-1-acid glycoprotein (AAG) on the concentration-time profiles and to determine the efficacy and adverse event profile of the epidural regimen. METHODS/MATERIALS: Thirty-one infants aged 40-63 weeks of postmenstrual age (PMA) undergoing hernia repair or abdominal surgery received an epidural injection of 1.5 mg · kg(-1) bupivacaine (0.25%) or ropivacaine (0.2%) followed 2 h later by an infusion of 0.2 mg · kg(-1) · h(-1) in those undergoing abdominal surgery. Total and unbound concentrations of bupivacaine and ropivacaine were analyzed using nonmem. Hourly pain scores and adverse effects were recorded. RESULTS: Bupivacaine data were available from 11 infants (five had infusions) and ropivacaine from 13 infants (four had infusions). Alpha-1-acid glycoprotein and total bupivacaine and ropivacaine concentrations accumulated during infusions, but unbound concentrations did not. Maximum unbound concentrations for bupivacaine and ropivacaine were 0.12 mg · l(-1) (bupivacaine) and 0.13 mg · l(-1) (ropivacaine). Typical clearance/bioavailability estimates of total (unbound) bupivacaine were 0.215 (4.65) l · h(-1) · kg(-1) and of total (unbound) ropivacaine were 0.288 (3.31) l · h(-1) · kg(-1). Pain scores requiring pain team referral occurred once with bupivacaine and four times with ropivacaine. No toxicity was observed. CONCLUSIONS: Epidural infusions of 0.2 mg(-1) · kg(-1) · h(-1) bupivacaine or ropivacaine appeared to be well tolerated and efficacious in this population. No accumulation of unbound drug concentrations occurred.

Dosing regimens of oral ciprofloxacin for children with severe malnutrition: a population pharmacokinetic study with Monte Carlo simulation.

BACKGROUND: Severe malnutrition is frequently complicated by sepsis, leading to high case fatality. Oral ciprofloxacin is a potential alternative to the standard parenteral ampicillin/gentamicin combination, but its pharmacokinetics in malnourished children is unknown. METHODS: Ciprofloxacin (10 mg/kg, 12 hourly) was administered either 2 h before or up to 2 h after feeds to Kenyan children hospitalized with severe malnutrition. Four plasma ciprofloxacin concentrations were measured over 24 h. Population analysis with NONMEM investigated factors affecting the oral clearance (CL) and the oral volume of distribution (V). Monte Carlo simulations investigated dosage regimens to achieve a target AUC(0-24)/MIC ratio of ≥125. RESULTS: Data comprised 202 ciprofloxacin concentration measurements from 52 children aged 8-102 months. Absorption was generally rapid but variable; C(max) ranged from 0.6 to 4.5 mg/L. Data were fitted by a one-compartment model with first-order absorption and lag. The parameters were CL (L/h) = 42.7 (L/h/70 kg) × [weight (kg)/70](0.75) × [1 + 0.0368 (Na(+) - 136)] × [1 - 0.283 (high risk)] and V (L) = 372 × (L/70 kg) × [1 + 0.0291 (Na(+) - 136)]. Estimates of AUC(0-24) ranged from 8 to 61 mg·h/L. The breakpoint for Gram-negative organisms was <0.06 mg/L with doses of 20 mg/kg/day and <0.125 mg/L with doses of 30 or 45 mg/kg/day. The cumulative fraction of response with 30 mg/kg/day was ≥80% for Escherichia coli, Klebsiella pneumoniae and Salmonella species, but <60% for Pseudomonas aeruginosa. CONCLUSIONS: An oral ciprofloxacin dose of 10 mg/kg three times daily (30 mg/kg/day) may be a suitable alternative antibiotic for the management of sepsis in severely malnourished children. Absorption was unaffected by the simultaneous administration of feeds.

Pharmacokinetics and tissue penetration of vancomycin continuous infusion as prophylaxis for vascular surgery.

OBJECTIVES: To determine the tissue penetration of vancomycin into perivascular fat and arterial wall during a continuous infusion of vancomycin, given as prophylaxis for vascular surgery. PATIENTS AND METHODS: Patients undergoing arterial reconstruction requiring antibiotic prophylaxis were included. Patients received a loading infusion of vancomycin the evening prior to surgery followed by a continuous 24 h infusion, calculated according to renal function. Three peri-operative serum samples and intra-operative perivascular fat and arterial wall samples were collected for vancomycin assay. RESULTS: Twenty-eight patients were included. Three serum samples were obtained from all patients, fat samples were available from 27 (96.4%) patients and vessel wall samples were available from 23 (82.1%) patients. Serum vancomycin concentrations were maintained within a relatively narrow range, while fat and arterial wall concentrations were highly variable. CONCLUSIONS: This study has shown that prophylactic administration of vancomycin with a loading infusion followed by a continuous infusion before and during vascular surgery achieves serum and vascular tissue concentrations that are above the MICs for most common organisms implicated in post-operative graft infection. However, penetration into perivascular fat tissues is poor.