Probenecid effects on cephalexin pharmacokinetics and pharmacodynamics in healthy volunteers.

OBJECTIVES: We evaluated the effects of probenecid on the Pharmaco Kinetics (PK) and pharmacodynamics (PD) of oral cephalexin in healthy volunteers. METHODS: Cephalexin 1000 mg was administered orally to 11 healthy volunteers following a standardized meal, with and without probenecid 500 mg orally, on two separate days one week apart. Total plasma concentrations of cephalexin and probenecid over a 12 h period were measured by liquid chromatography tandem mass spectrometry. Standard pharmacokinetic measures and contemporary PK/PD targets were compared. RESULTS: Probenecid increased the mean (95% CI) cephalexin area under the concentration-time curve (AUC0-∞) 1.73-fold (1.61-1.85, p < 0.0001), peak concentration 1.37-fold (1.16-1.58, p < 0.01), time to peak concentration 1.45-fold (1.1-1.8, p < 0.01), and half-life 1.33-fold (1.03-1.62, p < 0.05). The effects resulted in clinically meaningful increases in the probability of PK/PD target attainment (PTA). As an example, the PTA of total concentrations above the minimum inhibitory concentration required to inhibit methicillin-susceptible Staphylococcus aureus isolates (MIC ≤ 8 mg/L) for 70% of a 6 h dose interval approached 100% for cephalexin + probenecid while for cephalexin alone it was <15%. CONCLUSIONS: Probenecid prolonged and flattened the plasma concentration-time curve, enhancing the probability of attaining PK/PD targets. Co-administration of probenecid may expand the clinical benefits of oral cephalexin.

Probenecid and food effects on flucloxacillin pharmacokinetics and pharmacodynamics in healthy volunteers.

OBJECTIVES: To measure the effect of probenecid, fasting and fed, on flucloxacillin pharmacokinetic and pharmacodynamic endpoints. METHODS: Flucloxacillin 1000 mg orally was given to 11 volunteers alone while fasting ('flucloxacillin alone'), and with probenecid 500 mg orally while fasting ('probenecid fasting') and with food ('probenecid fed'). Flucloxacillin pharmacokinetic and pharmacodynamic endpoints were compared. RESULTS: Probenecid, fasting and fed, increased free plasma flucloxacillin area under the concentration-time curve (zero to infinity) ∼1.65-fold (p < 0.01) versus flucloxacillin alone. Probenecid fed prolonged time to peak flucloxacillin concentrations ∼2-fold versus the other two regimens (p < 0.01). Probenecid fasting or fed increased free flucloxacillin concentrations exceeding 30%, 50% and 70% of the first 6, 8 and 12 h post-dose by 1.58- to 5.48-fold compared with flucloxacillin alone. As an example of this pharmacodynamic improvement, the probability of target attainment of free concentrations above the minimum inhibitory concentration for Staphylococcus aureus (0.5 mg/L) for 50% of a 6-hour dose interval was > 80% for flucloxacillin plus probenecid (fasting or fed) and < 20% for flucloxacillin alone. CONCLUSIONS: Probenecid increased flucloxacillin exposure, with predicted pharmacodynamic effects greater than pharmacokinetic effects because of the altered shape of the concentration-time curve. Probenecid may improve the applicability of oral flucloxacillin regimens.

The dosing and monitoring of vancomycin: what is the best way forward?

We have evaluated the literature to review optimal dosing and monitoring of intravenous vancomycin in adults, in response to evolving understanding of targets associated with efficacy and toxicity. The area under the total concentration-time curve (0-24 h) divided by the minimum inhibitory concentration (AUC24/MIC) is the most commonly accepted index to guide vancomycin dosing for the treatment of Staphylococcus aureus infections, with a value of 400 h a widely recommended target for efficacy. Upper limits of AUC24 exposure of around 700 (mg/L).h have been proposed, based on the hypothesis that higher exposures of vancomycin are associated with an unacceptable risk of nephrotoxicity. If AUC24/MIC targets are used, sources of variability in the assessment of both AUC24 and MIC need to be considered. Current consensus guidelines recommend measuring trough vancomycin concentrations during intermittent dosing as a surrogate for the AUC24. Trough concentrations are a misleading surrogate for AUC24 and a poor end-point in themselves. AUC24 estimation using log-linear pharmacokinetic methods based on two plasma concentrations, or Bayesian methods are superior. Alternatively, a single concentration measured during continuous infusion allows simple AUC24 estimation and dose-adjustment. All of these methods have logistical challenges which must be overcome if they are to be adopted successfully.

Simultaneous Determination of Cefalexin, Cefazolin, Flucloxacillin, and Probenecid by Liquid Chromatography-Tandem Mass Spectrometry for Total and Unbound Concentrations in Human Plasma.

BACKGROUND: Pharmacokinetic studies and therapeutic drug monitoring of antibiotics require a simple, rapid, and reliable analytical method for monitoring the concentrations in plasma, including unbound concentrations for highly protein-bound drugs. The aim of the current work was to develop and validate a liquid chromatography-tandem mass spectrometry method for the simultaneous determination of total and unbound concentrations of 3 widely used ß-lactam antibiotics (cefalexin, cefazolin, and flucloxacillin) and the often coadministered drug probenecid in human plasma, suitable for pharmacokinetic studies and for routine use in ordinary, busy hospital laboratories. METHODS: Unbound drug was separated from bound drug by ultrafiltration. A simple 1-step protein precipitation was used for sample preparation. Cefalexin, cefazolin, flucloxacillin, probenecid, and their corresponding isotopically labeled internal standards were then resolved on a C18 (2) column. All the compounds were detected using electrospray ionization in the positive mode. RESULTS: Standard curves were linear for all compounds over the concentration range of 0.2-100 mg/L (r > 0.99) for total drug in plasma and 0.01-10 mg/L (r > 0.99) for unbound drug in plasma ultrafiltrate. For both total and unbound drugs, bias was <±10%, and intra- and interday coefficients of variation (imprecision) were <10%. The limit of quantification was 0.2 mg/L for total plasma concentrations and 0.01 mg/L for plasma ultrafiltrate concentrations of all drugs. CONCLUSIONS: The method has proven to be simple, rapid, robust, and reliable and is currently being used in clinical pharmacokinetic studies and in the routine clinical service to enhance the effective use of the ß-lactam antibiotics.

In healthy volunteers, taking flucloxacillin with food does not compromise effective plasma concentrations in most circumstances.

It is usually recommended that flucloxacillin is given on an empty stomach. The aim of this study was to compare total and free flucloxacillin concentrations after oral flucloxacillin, given with and without food, based on contemporary pharmacokinetic and pharmacodynamic targets. Flucloxacillin 1000 mg orally was given to 12 volunteers, after a standardised breakfast and while fasting, on two separate occasions. Flucloxacillin concentrations over 12 hours were measured by liquid chromatography-tandem mass spectrometry. Pharmacokinetic parameters, and pharmacodynamic endpoints related to target concentration achievement, were compared in the fed and fasting states. For free flucloxacillin, the fed/fasting area under the concentration-time curve from zero to infinity (AUC0-∞) ratio was 0.80 (p<0.01, 90% CI 0.70-0.92), the peak concentraton (Cmax) ratio 0.51 (p<0.001, 0.42-0.62) and the time to peak concentration (Tmax) ratio 2.2 (p<0.001, 1.87-2.55). The ratios for total flucloxacillin concentrations were similar. The mean (90% CI) fed/fasting ratios of free concentrations exceeded for 30%, 50% and 70% of the first 6 hours post-dose were 0.74 (0.63-0.87, fed inferior p<0.01), 0.95 (0.81-1.11, bioequivalent) and 1.15 (0.97-1.36, fed non-inferior), respectively. Results for 8 hours post-dose and those predicted for steady state were similar. Comparison of probability of target attainments for fed versus fasting across a range of minimum inhibitory concentrations (MICs) were in line with these results. Overall, this study shows that food reduced the AUC0-∞ and Cmax, and prolonged the Tmax of both free and total flucloxacillin concentrations compared with the fasting state, but achievement of free concentration targets associated with efficacy was in most circumstances equivalent. These results suggest that taking flucloxacillin with food is unlikely to compromise efficacy in most circumstances.

The performance of contemporary cystatin C-based GFR equations in predicting gentamicin clearance.

AIMS: We aimed to compare the performances of contemporary cystatin C (Cys)-based GFR equations, and the creatinine only Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation for predicting gentamicin clearance. METHODS: The bias and imprecision of the CKD-EPI, CKD-EPI_Cys and creatinine-cystatin C CKD-EPI (CKD-EPI_CrCys) equations for predicting gentamicin clearances, were assessed in 260 patients treated with gentamicin during 2012-2013. The creatinine-cystatin C Berlin Initiative Study equation (BIS_CrCys) was examined in the ≥70 year subgroup. The reference gentamicin clearance was calculated using post-dose plasma concentrations. RESULTS: The CKD-EPI_CrCys equation had the highest percentage of estimates within 30% of the reference gentamicin clearance (70%, P = 0.003) and lowest root mean square error (95% CI) of 29 (25, 23) ml min(-1) of the three equations for the entire cohort. There was no significant improvement in the performances of the equations with the exclusion of 41 patients with abnormal thyroid function tests or steroid co-prescription at the time of the index gentamicin dose. Of the remaining 219 patients, adjustment for individual BSA improved the performances of all GFR equations (P ≤ 0.003) in those with body mass indices (BMI) <18.5 or ≥30 kg m(-2) , but not those with BMI 18.5-29.9 kg m(-2) . There was no advantage of the BIS_CrCys over the CKD-EPI_CrCys equation in the ≥70 year subgroup. CONCLUSIONS: The CKD-EPI_CrCys equation provided the best estimate of gentamicin clearance. If used for guiding gentamicin dosing, the results from GFR equations should be adjusted for individual BSA at the extremes of body size.

Gentamicin and renal function: lessons from 15 years' experience of a pharmacokinetic service for extended interval dosing of gentamicin.

BACKGROUND: Extended interval dosing (EID) of gentamicin most commonly involves dosing every 24 hours, but patients with impaired renal function may require a longer dose interval. This study examines a large database of patients treated with gentamicin from 1996 to 2010 to see how many patients with renal impairment would have benefited from dose intervals >24 hours and to define the incidence of nephrotoxicity. METHODS: All patients aged ≥ 16 years who had received gentamicin by EID over the 14-year period and had concentration data available were examined. End points included the numbers (%) achieving the target peak concentration [predicted maximum gentamicin concentration (C(max))] >10 mg/L, the target trough concentration at 24 hours [predicted minimum gentamicin concentration (C(min24)] <0.5 mg/L, and the target area under the curve over 24 hours of 70-100 mg/L · h. How these related to various creatinine clearance (CL(cr)) groupings was also examined, as was the number who developed nephrotoxicity (increase in creatinine of ≥ 0.04 mmol/L). RESULTS: After exclusions, information was available on 4523 patients. Of these, 96% achieved the target C(max), 83% the target C(min24), and 54% the target area under the curve over 24 hours. Of the 73% of patients with CL(cr) ≥ 60 mL/min, 98% and 97% achieved the target Cmax and C(min24), respectively. Of the 19% of patients with CL(cr) of 40-59 mL/min, 94% and 61% achieved the target C(max) and C(min24), respectively. Of the 8% of patients with CL(cr) of 20-39 mL/min, 83% and 15% achieved the target Cmax and C(min24), respectively. Nephrotoxicity, "probably" because of gentamicin, was observed in approximately 4% of the patients studied, which was irreversible in 25% of these (ie, 1% overall). CONCLUSIONS: Extending the dose interval of gentamicin to >24 hours is useful in patients with renal impairment to achieve the aims of EID. These results support initial dose intervals for gentamicin of 24, 36, and 48 hours for patients with CL(cr) ≥ 60, 40-59, and 20-39 mL/min, respectively. Irreversible nephrotoxicity was observed in approximately 1% of the patients studied.

Correlation between trough plasma dabigatran concentrations and estimates of glomerular filtration rate based on creatinine and cystatin C.

AIMS: Dabigatran is largely cleared by renal excretion. Renal function is thus a major determinant of trough dabigatran concentrations, which correlate with the risk of thromboembolic and haemorrhagic outcomes. Current dabigatran dosing guidelines use the Cockcroft-Gault (CG) equation to gauge renal function, instead of contemporary equations including the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equations employing creatinine (CKD-EPI_Cr), cystatin C (CKD-EPI_Cys) and both renal biomarkers (CKD-EPI_CrCys). METHODS: A linear regression model including the dabigatran etexilate maintenance dose rate, relevant interacting drugs and genetic polymorphisms (including CES1), was used to analyse the relationship between the values from each renal function equation and trough steady-state plasma dabigatran concentrations. RESULTS: The median dose-corrected trough steady-state plasma dabigatran concentration in 52 patients (38-94 years) taking dabigatran etexilate was 60 µg/L (range 9-279). The dose-corrected trough concentration in a patient on phenytoin and phenobarbitone was >3 standard deviations below the cohort mean. The CG, CKD-EPI_Cr, CKD-EPI_Cys and CKD-EPI_CrCys equations explained (R (2), 95 % CI) 32 % (9-55), 37 % (12-60), 41 % (16-64) and 47 % (20-69) of the variability in dabigatran concentrations between patients, respectively. One-way analysis of variance (ANOVA) comparing the R (2) values for each equation was not statistically significant (p = 0.74). DISCUSSION: Estimates of renal function using the four equations accounted for 32-47 % of the variability in dabigatran concentrations between patients. We are the first to provide evidence that co-administration of phenytoin/phenobarbitone with dabigatran etexilate is associated with significantly reduced dabigatran exposure.

Population PK modelling and simulation based on fluoxetine and norfluoxetine concentrations in milk: a milk concentration-based prediction model.

AIMS: Population pharmacokinetic (pop PK) modelling can be used for PK assessment of drugs in breast milk. However, complex mechanistic modelling of a parent and an active metabolite using both blood and milk samples is challenging. We aimed to develop a simple predictive pop PK model for milk concentration-time profiles of a parent and a metabolite, using data on fluoxetine (FX) and its active metabolite, norfluoxetine (NFX), in milk. METHODS: Using a previously published data set of drug concentrations in milk from 25 women treated with FX, a pop PK model predictive of milk concentration-time profiles of FX and NFX was developed. Simulation was performed with the model to generate FX and NFX concentration-time profiles in milk of 1000 mothers. This milk concentration-based pop PK model was compared with the previously validated plasma/milk concentration-based pop PK model of FX. RESULTS: Milk FX and NFX concentration-time profiles were described reasonably well by a one compartment model with a FX-to-NFX conversion coefficient. Median values of the simulated relative infant dose on a weight basis (sRID: weight-adjusted daily doses of FX and NFX through breastmilk to the infant, expressed as a fraction of therapeutic FX daily dose per body weight) were 0.028 for FX and 0.029 for NFX. The FX sRID estimates were consistent with those of the plasma/milk-based pop PK model. CONCLUSIONS: A predictive pop PK model based on only milk concentrations can be developed for simultaneous estimation of milk concentration-time profiles of a parent (FX) and an active metabolite (NFX).

A proposal for dose-adjustment of dabigatran etexilate in atrial fibrillation guided by thrombin time.

Dabigatran is an oral anticoagulant that is increasingly used for atrial fibrillation (AF). Presently, many authorities state that routine laboratory coagulation monitoring is not required. However, data have recently been published demonstrating that higher trough plasma dabigatran concentrations are associated with lower thromboembolic and higher haemorrhagic event rates. Using these data, we simulate a range of AF patients with varying risks for these events and derive a target range of trough plasma dabigatran concentrations (30-130 µg l(-1) ). Finally, we propose that a conventional screening coagulation assay, the thrombin time (TT), can be used to discern whether or not patients are within this range of dabigatran concentrations.

Coagulation assays and plasma fibrinogen concentrations in real-world patients with atrial fibrillation treated with dabigatran.

AIMS: In patients with atrial fibrillation prescribed dabigatran, the aim was to examine the correlation between plasma dabigatran concentrations and the three screening coagulation assays [international normalized ratio (INR), activated partial thromboplastin time (aPTT) and thrombin time (TT)] as well as the dilute thrombin time (dTT) and to examine the contribution of plasma fibrinogen concentrations to the variability in TT results. METHODS: Plasma from patients with atrial fibrillation on dabigatran were analysed for clotting times and concentrations of fibrinogen and dabigatran. Correlation plots (and associated r(2) values) were generated using these data. The variability in TT results explained by fibrinogen concentrations was quantified using linear regression. RESULTS: Fifty-two patients (38-94 years old) contributed 120 samples, with plasma dabigatran concentrations ranging from 9 to 408 µg l(-1) . The r(2) values of INR, aPTT, TT and dTT against plasma dabigatran concentrations were 0.49, 0.54, 0.70 and 0.95, respectively. Plasma fibrinogen concentrations explained some of the residual variability in TT values after taking plasma dabigatran concentrations into account (r(2) = 0.12, P = 0.02). CONCLUSIONS: Of the screening coagulation assays, the TT correlated best with plasma dabigatran concentrations. Variability in fibrinogen concentrations accounts for some of the variability in the TT.

Thirteen years' experience of pharmacokinetic monitoring and dosing of busulfan: can the strategy be improved?

BACKGROUND: A busulfan concentration monitoring and dosing service has been provided by Christchurch Hospital since 1998. This study aimed to see (1) the percentage of patients with an area under the concentration time curve (AUC) outside the target range and had dose adjustment, (2) how busulfan clearance (CL) relates to body weight, and (3) if fewer samples could be used to predict doses. METHODS: Blood samples were taken from patients after oral administration, usually at 0.5, 1, 1.5, and 6 hours, and after the start of a 2-hour intravenous (IV) infusion of busulfan, at 1, 2, 2.5, 3, 6, and 8 hours. Dose adjustment was made based on the AUC compared with the target range. The relationship of CL and body weight for the IV group was used to develop a revised IV dosing schedule. The bias and imprecision of AUCs estimated using fewer sampling points were examined to see if sampling could be economized. RESULTS: Data were available for 150 patients but for 6 patients, data were incomplete and excluded. Of the remaining 144 patients (256 sample sets, 209 oral, 47 IV, 62% with repeats), 38% (IV) and 35% (oral) of patients had AUCs within the target range after the first dose. Dose adjustment was made in 47% and 34% of patients dosed IV and orally, respectively, after which there was a trend to more patients achieving the target AUC. A nonlinear relationship was found between CL and body weight. The initial IV dosing schedule was revised to take this into account. Sampling for busulfan concentration measurement at 3 points (2.5, 4, 8 hours) or 2 points (2.5, 8 hours) after the start of the infusion enabled accurate and precise estimates of AUC0₋24. CONCLUSIONS: Around two thirds of patients treated with busulfan were outside the target AUC range after the first dose. Dose adjustment was made in 37% of patients. The relationship between CL and body weight was used to revise the initial IV dosing schedule. Sampling for AUC estimation could be reduced to 2 time points after IV dosing.

A simple high-performance liquid chromatography method for simultaneous determination of three triazole antifungals in human plasma.

A rapid and simple high-performance liquid chromatography (HPLC) assay was developed for the simultaneous determination of three triazole antifungals (voriconazole, posaconazole, and itraconazole and the metabolite of itraconazole, hydroxyitraconazole) in human plasma. Sample preparation involved a simple one-step protein precipitation with 1.0 M perchloric acid and methanol. After centrifugation, the supernatant was injected directly into the HPLC system. Voriconazole, posaconazole, itraconazole, its metabolite hydroxyitraconazole, and the internal standard naproxen were resolved on a C(6)-phenyl column using gradient elution of 0.01 M phosphate buffer, pH 3.5, and acetonitrile and detected with UV detection at 262 nm. Standard curves were linear over the concentration range of 0.05 to 10 mg/liter (r(2) > 0.99). Bias was <8.0% from 0.05 to 10 mg/liter, intra- and interday coefficients of variation (imprecision) were <10%, and the limit of quantification was 0.05 mg/liter.

Determination of imatinib and its active metabolite N-desmethyl imatinib in human plasma by liquid chromatography/tandem mass spectrometry.

Imatinib is a first-line treatment for chronic myelogenous leukaemia (CML). The pharmacokinetics of imatinib in patients with CML are characterised by large interpatient variability. Concentration monitoring of imatinib and its active metabolite N-desmethyl imatinib (DMI) is considered necessary to enhance the safe and effective use of imatinib. A rapid, simple and sensitive liquid chromatography/tandem mass spectrometry assay was developed for the simultaneous determination of imatinib and its metabolite DMI in human plasma. After proteins were precipitated with acetonitrile, imatinib, DMI and the internal standard D8-imatinib were resolved on a Gemini-NX 3 µm C18 column using gradient elution of 0.05 % formic acid and methanol. The three compounds were detected using electrospray ionisation in the positive mode. Standard curves of imatinib and DMI were adequately fitted by quadratic equations (r > 0.999) over the concentration range of 10 to 2,000 ng/mL which encompasses clinical concentrations. Bias was ≤±8.3 %, intra- and inter-day coefficients of variation (imprecision) were ≤8.0 % and the limit of quantification was 10 ng/mL for both imatinib and DMI. The assay is being used successfully in clinical practice to enhance the safe and effective use of imatinib.

Institutional profile: The Carney Centre for Pharmacogenomics: a New Zealand focus for personalized medicine research.

The integration of genetics and genomics with pharmacology and clinical medicine has enriched our understanding of all of these disciplines and is steadily providing a more complete picture of the etiology, pathophysiology and treatment of disease. To capitalize on this new knowledge requires the ability to evaluate the underlying evidence base and to test the utility of any proposed pharmacogenetic or genomic approaches to personalized medicine, within local or regional healthcare structures. The Carney Centre for Pharmacogenomics is now in its eighth year of operation, and although small by international standards, it has proven to be a valuable focus for research, training and dissemination of such knowledge in New Zealand and beyond. By focusing predominantly on research and training, the center has raised awareness about the value and limitations of pharmacogenetics and pharmacogenomic approaches.