Pharmacokinetics of intravenous piperacillin/tazobactam among patients with peritoneal dialysis-associated peritonitis.

Currently, pharmacokinetic information on intravenous (IV) piperacillin/tazobactam in patients with peritoneal dialysis-associated peritonitis (PD peritonitis) is limited. This study employed a prospective single-dose pharmacokinetic design to assess the pharmacokinetics of IV piperacillin/tazobactam in these patients. Four patients with PD peritonitis who received an IV loading dose of 4000 mg/500 mg piperacillin/tazobactam were enrolled in this study. The concentrations of piperacillin and tazobactam in plasma, peritoneal dialysis fluid (PDF) and urine were determined by high-performance liquid chromatography. Non-compartmental methods were used for pharmacokinetic analysis. During a 6-h dwell time for chronic ambulatory peritoneal dialysis (CAPD), 9.23 ± 4.01% of the piperacillin was recovered in the PDF. This result is greater than that observed in patients without peritonitis in prior research. Piperacillin's PD clearance (CLPD), steady-state volume of distribution (Vss) and terminal half-life (t 1/2) were 5.79 ± 2.55 mL/min, 24.35 ± 11.26 L and 5.74 ± 1.53 h, respectively. These values are also higher than those of patients without peritonitis in a prior study. Eight hours following the loading dosage, the plasma and PDF piperacillin concentrations of all patients (98.25 ± 26.03 and 52.70 ± 22.99 mg/L, respectively) surpassed the Pseudomonas aeruginosa and Enterobacterales Clinical and Laboratory Standards Institute susceptible breakpoints. In summary, the CLPD, Vss and t 1/2 for piperacillin were found to be greater in patients with PD peritonitis than in CAPD patients without peritonitis when compared with the results of a previous study. The IV loading dose of 4000 mg/500 mg piperacillin/tazobactam is sufficient to treat peritonitis caused by susceptible P. aeruginosa and Enterobacterales. The multiple-dose pharmacokinetics of IV piperacillin and tazobactam in this specific patient group should be further investigated.

Citrate pharmacokinetics in critically ill liver failure patients receiving CRRT.

Citrate has been proposed as anticoagulation of choice in continuous renal replacement therapy (CRRT). However, little is known about the pharmacokinetics (PK) and metabolism of citrate in liver failure patients who require CRRT with regional citrate anticoagulation (RCA). This prospective clinical PK study was conducted at King Chulalongkorn Memorial Hospital between July 2019 to April 2021, evaluating seven acute liver failure (ALF) and seven acute-on-chronic liver failure (ACLF) patients who received CRRT support utilizing RCA as an anticoagulant at a citrate dose of 3 mmol/L. For evaluation of the citrate PK, we delivered citrate for 120 min and then stopped for a further 120 min. Total body clearance of citrate was 152.5 ± 50.9 and 195.6 ± 174.3 mL/min in ALF and ACLF, respectively. The ionized calcium, ionized magnesium, and pH slightly decreased after starting citrate infusion and gradually increased to baseline after stopping citrate infusion. Two of the ACLF patients displayed citrate toxicity during citrate infusion, while, no ALF patient had citrate toxicity. In summary, citrate clearance was significantly decreased in critically ill ALF and ACLF patients receiving CRRT. Citrate use as an anticoagulation in these patients is of concern for the risk of citrate toxicity.

Introduction of new alternative pipeline using multiplexed fast COLD­PCR together with sequencing approach highlighting pharmacoeconomics by detection of CYP variants.

In precision medicine, multiple factors are involved in clinical decision-making because of ethnic and racial genetic diversity, family history and other health factors. Although advanced techniques have evolved, there is still an economic obstacle to pharmacogenetic (PGx) implementation in developing countries. The aim of the present study was to provide an alternative pipeline that roughly estimate patient carrier type and prescreen out wild-type samples before sequencing or genotyping to determine genetic status. Fast co-amplification at lower denaturation temperature (COLD)-PCR was used to differentiate genetic variant non-carriers from carriers. The majority of drugs are hepatically cleared by cytochrome P450 (CYP) enzymes and genes encoding CYP enzymes are highly variable. Of all the CYPs, CYP2 family of CYP2C9, CYP2C19, and CYP2D6 isoforms have clinically significant impact on drugs of PGx testing. Therefore, five variants associated with these CYPs were selected for preliminary testing with this novel pipeline. For fast COLD-PCR, the optimal annealing temperature and critical denaturation temperature were determined and evaluated via Sanger sequencing of 27 randomly collected samples. According to precise Tc, to perform in a single-reaction is difficult. However, in this study, this issue was resolved by combination of precise Tc using 10+10+20 cycles. The results showed 100% sensitivity and specificity, with perfect agreement (κ=1.0) compared with Sanger sequencing. The present study provides a prescreening platform by introducing multiplex fast COLD-PCR as a pharmacoeconomic implementation. Our study just present in five variants which are not enough to describe patient metabolic status. Therefore, other actional genetic variants are still needed to cover the actual patient's genotypes. Nevertheless, the proposed method can well-present its efficiency and reliability for serving as a PGx budget platform in the future.

Correlation of the vancomycin 24-h area under the concentration-time curve (AUC24) and trough serum concentration in children with severe infection: A clinical pharmacokinetic study.

BACKGROUND: Vancomycin is a common drug used in children with severe infection. In adults, at least 15 mg/L of the optimal vancomycin trough concentration (Ctrough) is needed to generate the target 24-h area under the concentration-time curve (AUC24) to the minimum inhibitory concentration (MIC) of 400 for a pathogen with the MIC ≤1 mg/L. OBJECTIVES: To determine vancomycin PK in children with severe infection and to explore the correlation between vancomycin Ctrough and AUC24 in children, as well as to propose the appropriate vancomycin dosages using Monte Carlo simulation. MATERIALS AND METHODS: Children aged 2-18 years who were admitted to Chiang Mai University Hospital and received intravenous vancomycin for severe infection were included in the study. Serum samples for vancomycin PK were obtained before and serially after the administration of the first dose according to the protocol. Pharmacokinetic analyses were performed using Phoenix WinNonlin® 7.0 and NLME™7.0. RESULTS: Fourteen children with 64% males and age range from 2 to 13 years were included in this study. Non-compartmental analysis revealed the median volume of distribution, clearance, and elimination half-life of 0.58 L/kg, 2.82 mL/kg/min and 2.33 h, respectively. Vancomycin serum concentrations were best described by a two-compartmental model with first-order elimination.The observed Ctrough at 6 h correlated well with the AUC24. The median vancomycin Ctrough at steady state that correlated with the AUC24 ≥ 400 and <800 were 11.18, 9.50, 7.91 and 6.55 mg/L in simulated children receiving vancomycin 40, 60, 80 and 100 mg/kg/day, respectively. CONCLUSION: Correlation between vancomycin Ctrough and AUC24 values in children has been observed. However, the values of Ctrough that correlate with the target AUC24≥400 in children are lower than the values observed and targeted in adults.

Quantitative Prediction of CYP3A4- and CYP3A5-Mediated Drug Interactions.

We verified a physiologically-based pharmacokinetic (PBPK) model to predict cytochrome P450 3A4/5-mediated drug-drug interactions (DDIs). A midazolam (MDZ)-ketoconazole (KTZ) interaction study in 24 subjects selected by CYP3A5 genotype, and liquid chromatography and mass spectroscopy quantification of CYP3A4/5 abundance from independently acquired and genotyped human liver (n = 136) and small intestinal (N = 12) samples, were conducted. The observed CYP3A5 genetic effect on MDZ systemic and oral clearance was successfully replicated by a mechanistic framework incorporating the proteomics-informed CYP3A abundance and optimized small intestinal CYP3A4 abundance based on MDZ intestinal availability (FG ) of 0.44. Furthermore, combined with a modified KTZ PBPK model, this framework recapitulated the observed geometric mean ratio of MDZ area under the curve (AUCR) following 200 or 400 mg KTZ, which was, respectively, 2.7-3.4 and 3.9-4.7-fold in intravenous administration and 11.4-13.4 and 17.0-19.7-fold in oral administration, with AUCR numerically lower (P > 0.05) in CYP3A5 expressers than nonexpressers. In conclusion, the developed mechanistic framework supports dynamic prediction of CYP3A-mediated DDIs in study planning by bridging DDIs between CYP3A5 expressers and nonexpressers.

Factors Associated with Mortality in Immunocompetent Patients with Hospital-acquired Pneumonia.

AIM: The aim of the study is to determine the factors associated with 28-day mortality in immunocompetent patients with hospital-acquired pneumonia (HAP). METHODS: This was a 42-month retrospective cohort study in Chiang Kham Hospital. Patients with HAP diagnosed between January 2013 and June 2016 who did not have an immunocompromised status were recruited into the study. STATISTICAL ANALYSIS USED: Univariable and multivariable binary logistic regression analyses were performed to determine the factors associated with mortality in patients with HAP. RESULTS: A total of 181 HAP patients. The most causative pathogens were nonfermenting Gram-negative bacilli. Fifty-two (28.7%) patients had died within 28 days after HAP diagnosis. Multivariable analysis demonstrated that mechanical ventilation (MV) dependency (adjusted odds ratio [OR] = 3.58, 95% confidence interval [CI] 1.53-8.37, P = 0.003), antibiotic duration (adjusted OR = 0.79, 95% CI 0.70-0.88, P < 0.001), acute kidney injury (adjusted OR = 5.93, 95% CI 1.29-27.22, P = 0.022), and hematologic diseases (adjusted OR = 11.45, 95% CI 1.61-81.50, P = 0.015) were the significant factors associated with 28-day mortality. CONCLUSIONS: The factors associated with mortality were MV dependency, HAP duration of treatment, acute kidney injury, and hematologic disease. Early recognition of these factors in immunocompetent patients with HAP and treatment with intensive care may improve the outcome.

Comparative performance of pharmacogenetics-based warfarin dosing algorithms derived from Caucasian, Asian, and mixed races in Thai population.

AIM: This study was conducted to compare predictive accuracy of the available pharmacogenetics (PGx)-guided warfarin dosing algorithms derived from Caucasian, Asian, and mixed population to identify a suitable algorithm for Thai population. METHODS: Ten warfarin dosing algorithms derived from different population including Caucasian, East Asian, South-East Asian, and mixed races were selected and tested with clinical and genetic data of Thai patients. Comparative performances of these algorithms were tested using mean dose error (MDE) between actual warfarin maintenance dose (AWMD) and predicted dose generated by each dosing algorithm, and percentage of ideal dose prediction (IDP). Sensitivity analysis for predictive accuracy was also conducted by stratifying patients into low (AWMD ≤21 mg/wk), intermediate (AWMD >21 to <49 mg/wk), and high maintenance dose (AWMD ≥49 mg/wk) groups. RESULTS: Data of 165 patients were included for the analyses. Mean actual warfarin dose of the study population was 25.03 ± 10.53 mg/wk. Large variability of MDE, ranging from -12.11 to 11.24 mg/wk, among algorithms was observed. International Warfarin Pharmacogenetics Consortium, Gage et al, and Ohno et al algorithms had comparable performances to Sangviroon et al algorithm, as observed by MDE of <1 mg/wk with percentage of IDP ≥40%. Further sensitivity analyses among patients requiring low and intermediate maintenance doses confirmed such findings with IDP percentage ranging from 37.8% to 59.2%. Among high-dose group, only Ohno et al and Sarapakdi et al algorithms had acceptable performance. CONCLUSIONS: Warfarin PGx-guided dosing algorithms derived from large, mixed population performed comparably to Sangviroon et al algorithm. Certain algorithms should be avoided due to significant dose prediction error.

The pharmacokinetics of vancomycin during the initial loading dose in patients with septic shock.

OBJECTIVE: To characterize the pharmacokinetics (PK) of vancomycin in patients in the initial phase of septic shock. METHODS: Twelve patients with septic shock received an intravenous infusion of vancomycin 30 mg/kg over 2 h. The vancomycin PK study was conducted during the first 12 h of the regimen. Serum vancomycin concentration-time data were analyzed using the standard model-independent analysis and the compartment model. RESULTS: For the noncompartment analysis the mean values ± standard deviation (SD) of the estimated clearance and volume of distribution of vancomycin at steady state were 6.05±1.06 L/h and 78.73±21.78 L, respectively. For the compartmental analysis, the majority of vancomycin concentration-time profiles were best described by a two-compartment PK model. Thus, the two-compartmental first-order elimination model was used for the analysis. The mean ± SD of the total clearance (3.70±1.25 L/h) of vancomycin was higher than that obtained from patients without septic shock. In contrast, the volume of the central compartment (8.34±4.36 L) and volume of peripheral compartment (30.99±7.84 L) did not increase when compared with patients without septic shock. CONCLUSION: The total clearance of vancomycin was increased in septic shock patients. However, the volume of the central compartment and peripheral compartment did not increase. Consequently, a loading dose of vancomycin should be considered in all patients with septic shock.

Pharmacokinetics and pharmacodynamics of meropenem in children with severe infection.

This study aimed to describe the pharmacokinetic (PK) characteristics of meropenem in children with severe infections and to assess the pharmacokinetic/pharmacodynamic (PK/PD) profiles of various meropenem dosage regimens in these patients. Fourteen children with severe infections received intravenous (i.v.) bolus doses of meropenem (20 mg/kg/dose) every 8 h (q8h). Serum samples were obtained before and serially after the second dose of meropenem, and a population PK analysis was performed. The final model was used to simulate serum concentration-time profiles with various dosage regimens. The PK/PD target was to achieve a serum meropenem concentration higher than the minimum inhibitory concentration (MIC) of the causative organism (i.e. Pseudomonas aeruginosa and Enterobacteriaceae) for ≥40% of the dosing interval (40%T>MIC). The median age and weight of the children were 6.0 years and 20.0 kg, respectively. Meropenem serum concentration-time profiles were best described by a two-compartmental model with first-order elimination. The simulations showed that the probabilities of target attainment (PTAs) for organisms with an MIC of 1 mg/L were 0.678 and 1.000 following i.v. bolus and 3-h infusion of meropenem (20 mg/kg/dose), respectively. Using a 3-h infusion of a 20 mg/kg/dose, the PTA was 0.999 and 0.765 for organisms with MICs of 4 mg/L and 8 mg/L, respectively. Meropenem given as i.v. bolus doses of 20 mg/kg/dose q8h appeared to be inadequate for PK/PD target attainment for organisms with an MIC of 1 mg/L. The simulations showed that meropenem administration via a 3-h infusion using the same dose improved the PTA.

Physiologically based pharmacokinetic model of mechanism-based inhibition of CYP3A by clarithromycin.

The prediction of clinical drug-drug interactions (DDIs) due to mechanism-based inhibitors of CYP3A is complicated when the inhibitor itself is metabolized by CYP3Aas in the case of clarithromycin. Previous attempts to predict the effects of clarithromycin on CYP3A substrates, e.g., midazolam, failed to account for nonlinear metabolism of clarithromycin. A semiphysiologically based pharmacokinetic model was developed for clarithromycin and midazolam metabolism, incorporating hepatic and intestinal metabolism by CYP3A and non-CYP3A mechanisms. CYP3A inactivation by clarithromycin occurred at both sites. K(I) and k(inact) values for clarithromycin obtained from in vitro sources were unable to accurately predict the clinical effect of clarithromycin on CYP3A activity. An iterative approach determined the optimum values to predict in vivo effects of clarithromycin on midazolam to be 5.3 microM for K(i) and 0.4 and 4 h(-1) for k(inact) in the liver and intestines, respectively. The incorporation of CYP3A-dependent metabolism of clarithromycin enabled prediction of its nonlinear pharmacokinetics. The predicted 2.6-fold change in intravenous midazolam area under the plasma concentration-time curve (AUC) after 500 mg of clarithromycin orally twice daily was consistent with clinical observations. Although the mean predicted 5.3-fold change in the AUC of oral midazolam was lower than mean observed values, it was within the range of observations. Intestinal CYP3A activity was less sensitive to changes in K(I), k(inact), and CYP3A half-life than hepatic CYP3A. This semiphysiologically based pharmacokinetic model incorporating CYP3A inactivation in the intestine and liver accurately predicts the nonlinear pharmacokinetics of clarithromycin and the DDI observed between clarithromycin and midazolam. Furthermore, this model framework can be applied to other mechanism-based inhibitors.

A new probabilistic rule for drug-dug interaction prediction.

An innovative probabilistic rule is proposed to predict the clinical significance or clinical insignificance of DDI. This rule is coupled with a hierarchical Bayesian model approach to summarize substrate/inhibitor's PK models from multiple published resources. This approach incorporates between-subject and between-study variances into DDI prediction. Hence, it can predict both population-average and subject-specific AUCR. The clinically significant DDI, weak DDI, and clinically insignificant inhibitions are decided by the probabilities of predicted AUCR falling into three intervals, (-infinity, 1.25), (1.25, 2), and (2, infinity). The main advantage of this probabilistic rule to predict clinical significance of DDI over the deterministic rule is that the probabilistic rule considers the sample variability, and the decision is independent of sampling variation; while deterministic rule based decision will vary from sample to sample. The probabilistic rule proposed in this paper is best suited for the situation when in vivo PK studies and models are available for both the inhibitor and substrate. An early decision on clinically significant or clinically insignificant inhibition can avoid additional DDI studies. Ketoconazole and midazolam are used as an interaction pair to illustrate our idea. AUCR predictions incorporating between-subject variability always have greater variances than population-average AUCR predictions. A clinically insignificant AUCR at population-average level is not necessarily true when considering between-subject variability. Additional simulation studies suggest that predicted AUCRs highly depend on the interaction constant K(i) and dose combinations.

Influence of hemodialysis on gentamicin pharmacokinetics, removal during hemodialysis, and recommended dosing.

BACKGROUND AND OBJECTIVES: Aminoglycoside antibiotics are commonly used in chronic kidney disease stage 5 patients. The purpose of this study was to characterize gentamicin pharmacokinetics, dialytic clearance, and removal by hemodialysis and to develop appropriate dosing strategies. Design Setting, Participants, and Measurements: Eight subjects receiving chronic, thrice-weekly hemodialysis with no measurable residual renal function received gentamicin after a hemodialysis session. Blood samples were collected serially, and serum concentrations of gentamicin were determined. RESULTS: Median (range) systemic clearance, volume of distribution at steady state, and terminal elimination half-life were 3.89 ml/min (2.69-4.81 ml/min), 13.5 L (8.7-17.9 L), and 39.4 h (32.0-53.6 h), respectively. Median (range) dialytic clearance, estimated amount removed, and percent maximum rebound were 103.5 ml/min (87.2-132.7 ml/min), 39.6 mg (19.7-43.9 mg), and 38.7% (0%-71.8%), respectively. Gentamicin dialytic clearance was statistically significantly related to creatinine dialytic clearance (r(2) = 0.52, P = 0.04), although this relationship is not likely to be strong enough to serve as a surrogate for gentamicin monitoring. The pharmacokinetic model was used to simulate gentamicin serum concentrations over a one-wk period. CONCLUSIONS: In clinical situations where gentamicin is used as the primary therapy in a patient receiving hemodialysis with a CAHP hemodialyzer, conventional doses after each dialysis session are not as efficient at achieving treatment targets as predialysis dosing with larger doses.

Drug-drug interaction prediction: a Bayesian meta-analysis approach.

In drug-drug interaction (DDI) research, a two drug interaction is usually predicted by individual drug pharmacokinetics (PK). Although subject-specific drug concentration data from clinical PK studies on inhibitor/inducer or substrate's PK are not usually published, sample mean plasma drug concentrations and their standard deviations have been routinely reported. In this paper, an innovative DDI prediction method based on a three-level hierarchical Bayesian meta-analysis model is developed. The first level model is a study-specific sample mean model; the second level model is a random effect model connecting different PK studies; and all priors of PK parameters are specified in the third level model. A Monte Carlo Markov chain (MCMC) PK parameter estimation procedure is developed, and DDI prediction for a future study is conducted based on the PK models of two drugs and posterior distributions of the PK parameters. The performance of Bayesian meta-analysis in DDI prediction is demonstrated through a ketoconazole-midazolam example. The biases of DDI prediction are evaluated through statistical simulation studies. The DDI marker, ratio of area under the concentration curves, is predicted with little bias (less than 5 per cent), and its 90 per cent credible interval coverage rate is close to the nominal level. Sensitivity analysis is conducted to justify prior distribution selections.

Stochastic prediction of CYP3A-mediated inhibition of midazolam clearance by ketoconazole.

Conventional methods to forecast CYP3A-mediated drug-drug interactions have not employed stochastic approaches that integrate pharmacokinetic (PK) variability and relevant covariates to predict inhibition in terms of probability and uncertainty. Empirical approaches to predict the extent of inhibition may not account for nonlinear or non-steady-state conditions, such as first-pass effects or accumulation of inhibitor concentration with multiple dosing. A physiologically based PK model was developed to predict the inhibition of CYP3A by ketoconazole (KTZ), using midazolam (MDZ) as the substrate. The model integrated PK models of MDZ and KTZ, in vitro inhibition kinetics of KTZ, and the variability and uncertainty associated with these parameters. This model predicted the time- and dose-dependent inhibitory effect of KTZ on MDZ oral clearance. The predictive performance of the model was validated using the results of five published KTZ-MDZ studies. The model improves the accuracy of predicting the inhibitory effect of increasing KTZ dosing on MDZ PK by incorporating a saturable KTZ efflux from the site of enzyme inhibition in the liver. The results of simulations using the model supported the KTZ dose of 400 mg once daily as the optimal regimen to achieve maximum inhibition by KTZ. Sensitivity analyses revealed that the most influential variable on the prediction of inhibition was the fractional clearance of MDZ mediated by CYP3A. The model may be used prospectively to improve the quantitative prediction of CYP3A inhibition and aid the optimization of study designs for CYP3A-mediated drug-drug interaction studies in drug development.

Levofloxacin pharmacokinetics in ESRD and removal by the cellulose acetate high performance-210 hemodialyzer.

BACKGROUND: No published data are available describing the pharmacokinetics of intravenous levofloxacin in patients with end-stage renal disease (ESRD). Objectives of this study are to determine the pharmacokinetics and dialytic clearance of levofloxacin and develop dosing strategies in these patients. METHODS: Eight noninfected subjects receiving long-term thrice-weekly hemodialysis, with no measurable residual renal function, were administered intravenous levofloxacin, 250 mg, over 1 hour after a scheduled hemodialysis session. Blood samples were collected serially during the interdialytic period, during the next intradialytic period, and immediately after the next hemodialysis session. Serum concentrations of levofloxacin were determined by high-performance liquid chromatography. Differential equations describing a 2-compartment open-infusion pharmacokinetic model were fit to each individual subject's serum concentration-time data by iterative nonlinear weighted least-squares regression analysis using Adapt II (Biomedical Simulations Resource, University of Southern California, Los Angeles, CA). Ratios of maximum serum concentration (C(max)) to minimum inhibitory concentration (MIC) were calculated for common respiratory pathogens by using MIC for 90% of isolates (MIC90) data from published studies. RESULTS: All subjects completed the study, and no adverse events were reported. Median systemic clearance, volume of distribution at steady state, elimination half-life, and C(max) were 37.0 mL/min (range, 12.8 to 42.7 mL/min), 103.3 L (range, 39.8 to 139.3 L), 34.4 hours (range, 28.4 to 39.3 hours), and 5.2 microg/mL (range, 4.1 to 11.3 microg/mL), respectively. Median dialytic clearance and levofloxacin reduction ratios were 84.4 mL/min (range, 61.8 to 107.6 mL/min) and 0.244 (range, 0.181 to 0.412), respectively. Median C(max)-MIC90 ratios were 10 or greater for Haemophilus influenzae, Moraxella catarrhalis, Enterobacter cloacae, and Klebsiella pneumoniae, approximately 5 for Streptococcus pneumoniae, and less than 1 for Pseudomonas aeruginosa. CONCLUSION: The administration of levofloxacin to patients with ESRD as 500 mg initially, followed by 250 mg every 48 hours, will provide adequate C(max)-MIC ratios after the first and subsequent doses for most patients with respiratory tract infections caused by organisms with levofloxacin MICs of 1 microg/mL or less.

CAHP-210 dialyzer influence on intra-dialytic vancomycin removal.

BACKGROUND: Vancomycin is often administered during the last hour of haemodialysis because it was not removed significantly by older hemodialyzers. However, newer higher permeability hemodialyzers remove vancomycin, although the amount removed varies considerably between dialyzers. The purpose of this study was to determine the apparent amount of vancomycin removed during the last hour of haemodialysis with a CAHP-210 hemodialyzer. METHODS: Eight subjects with end-stage renal disease (ESRD) received i.v. vancomycin 15 mg/kg after their regular haemodialysis session ended. Serum samples for the determination of vancomycin concentrations were obtained serially for 44 h. After a 3-week washout, the study was repeated with the vancomycin infused during the last hour of their regular haemodialysis session using a CAHP-210 hemodialyzer. Vancomycin concentrations were determined by the Enzyme Multiplied Immunoassay Technique. Differential equations describing a two-compartment open infusion model were fitted to the serum concentration vs time data and pharmacokinetic parameters and apparent vancomycin removal was estimated. RESULTS: The median age and weight of the subjects were 52 years (range 37-71) and 75.6 kg (range 37.6-89.8), respectively. The apparent vancomycin intra-dialytic removal was 0.24 (range -0.07-0.35), which was statistically significantly different from zero. CONCLUSIONS: Vancomycin administered during the last hour of CAHP-210 dialysis results in 24% less vancomycin exposure than when administered post-haemodialysis. This intra-dialytic drug loss should be accounted for when dosing vancomycin in this manner.