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Frail older people have a high prevalence of drug use and are susceptible to adverse drug reactions. The physiological changes of frailty are likely to affect pharmacokinetics and pharmacodynamics. We reviewed the methods and findings of published studies of pharmacokinetics in frailty. Nine studies describing pharmacokinetics and an additional three of pharmacokinetic pathways in frail older people were identified. Most pharmacokinetic studies investigated a single administration of a medication, dose or formulation, in small populations, often with limited representation of males or females, and applied variable definitions of frailty. Pharmacokinetic sampling designs generally utilised saturated sampling followed by analysis based on the trapezoidal rule for area under the curve, with more recent studies using sparser sampling and more sophisticated modelling to obtain individual and population values of all pharmacokinetic parameters. Overall, the pharmacokinetic studies reported only small changes in some parameters for some drugs with frailty, with the most consistent change reduced hepatic clearance in frail older people. Recommendations for future studies of pharmacokinetics in frailty include (i) standard objective definitions of frailty; (ii) larger studies including people with mild, moderate and severe frailty; (iii) population pharmacokinetic modelling to allow sparser sampling and consideration of multiple influences on pharmacokinetics; (iv) physiologically based modelling as the physiology of frailty emerges and (v) longitudinal pharmacokinetic studies of chronic drug therapy from middle to old age and from robust to pre-frail to frail, including pre-clinical studies. These data, accompanied by pharmacodynamics data in frailty, will inform safe, effective prescribing for frail older people.

Background Respiratory syncytial virus (RSV) causes high morbidity, with mortality rates approaching or exceeding that of influenza in adult and infant patient populations, respectively. Lumicitabine (ALS-008176 or JNJ-64041575) is an oral nucleoside analogue prodrug in clinical development to treat RSV infections. This prodrug converts to plasma-circulating ALS-8112, and then to the 5'-active nucleoside triphosphate (NTP) form within host cells. We conducted an RSV-A challenge study in healthy adults to evaluate lumicitabine's activity during an active RSV infection. Objectives To develop a semi-mechanistic mathematical model describing RSV kinetics, and the pharmacokinetics (PK) and pharmacodynamics (PD) of lumicitabine during treatment. Methods Nasopharyngeal viral load and concentrations of ALS-8112 and ALS-8144 (uridine metabolite) were measured frequently over the study duration. Population viral kinetic and PK/PD models were developed using NONMEM. The RSV life-cycle was described using a target-cell-limited model that included a physiological delay. Results The estimated clearances of ALS-8112 and ALS-8144 were 54.2 and 115 L/h/70 kg, respectively. A semi-physiological model was linked to predict ALS-8112 conversion to active intracellular NTP. Extensive and rapid RSV reduction occurred after lumicitabine treatment (EC50 = 1.79 μM), with >99% viral inhibition at 2 h after loading dose. Simulated NTP exposures and time to EC50 attainment suggested that rapid therapeutic effects and reduced dosing frequency are achievable in adult and paediatric patients. Conclusions The semi-mechanistic model characterizes RSV kinetics and the antiviral effectiveness of lumicitabine in an adult challenge population. This model is applicable to guide dose selection in adult and paediatric patients.

OBJECTIVES: The primary objectives were to investigate the prescribing practices of primary antifungal prophylaxis (PAP) and incidence of invasive fungal disease (IFD) in adult patients with ALL receiving induction-consolidation chemotherapy. Secondary objectives were to determine risk factors for IFD and resource utilization associated with IFD. METHODS: A retrospective chart review of adult patients with ALL from commencement of induction until completion of consolidation chemotherapy was undertaken from January 2008 to June 2013 in four hospitals in Melbourne, Australia. IFD was classified according to the revised European Organisation for Research and Treatment of Cancer criteria. Cost analysis was performed from an Australian public hospital perspective. RESULTS: Ninety-eight patients were included in the audit; 83 (85%) received PAP. Most patients (49/83, 59%) switched between two different antifungal agents, predominantly between liposomal amphotericin B and an azole. Five proven/probable and six possible IFD cases were identified. Proven/probable IFD was most common in patients receiving the BFM95 chemotherapy protocol. The incidence of proven/probable IFD was significantly lower in patients receiving PAP compared with those who did not (2/78, 2.6% versus 3/14, 21.4%; P = 0.024). For every five patients receiving PAP, one proven/probable IFD case would be prevented. Proven/probable IFD was associated with an additional median cost of 121,520 Australian dollars (95% CI: 90,781-180,141 Australian dollars; P < 0.001) compared with patients without IFD. CONCLUSIONS: This is the first multicentre study evaluating PAP use in patients with ALL. With the caveats of interpretation of retrospective, non-randomized data, PAP was associated with a reduced IFD risk.

Background The use of fosfomycin for treatment of systemic infections due to MDR Pseudomonas aeruginosa is increasing. However, pharmacodynamic data for fosfomycin are limited. Methods Sixty-four clinical isolates of P. aeruginosa (MDR and non-MDR) from two Australian hospitals were collected; 59 isolates were from patients with cystic fibrosis and 5 isolates were from critically ill patients. The in vitro pharmacodynamic properties of fosfomycin (disodium) were investigated via MICs (all isolates) and, for selected isolates, via time-kill kinetics (static and dynamic models; concentration range, 1-1024 mg/L), population analysis profiles (PAPs) and post-antibiotic effect (PAE). Two inocula (∼10(6) and ∼10(8) cfu/mL) were included in static time-kill studies to examine the effect of inocula on bacterial killing. Results MICs ranged from 1 to >512 mg/L, with 61% of isolates considered fosfomycin susceptible (MIC ≤64 mg/L). The MIC distributions for MDR and non-MDR isolates were similar. Baseline PAPs indicated heteroresistance in all isolates tested. Time-kill studies showed moderate (maximum killing ∼3 log10 cfu/mL), time-dependent killing at the low inoculum with regrowth at 24 h. Most concentrations resulted in complete replacement of fosfomycin-susceptible colonies by fosfomycin-resistant colonies. Bacterial killing was virtually eliminated at the high inoculum. The PAE ranged from 0.3 to 5.5 h. Conclusions These data suggest monotherapy with fosfomycin may be problematic for the treatment of infections caused by P. aeruginosa. Further investigation of fosfomycin combination therapy is warranted.

Objectives The objective of this study was to describe the population pharmacokinetics of cefazolin in plasma and the interstitial fluid of subcutaneous tissue of post-trauma critically ill patients and provide clinically relevant dosing recommendations that result in optimal concentrations at the target site. Patients and methods This was a pharmacokinetic study in a tertiary referral ICU. We recruited 30 post-trauma critically ill adult patients and collected serial total and unbound plasma cefazolin concentrations. Interstitial fluid concentrations were determined using in vivo microdialysis. Population pharmacokinetic analysis and Monte Carlo simulations were undertaken with Pmetrics®. Fractional target attainment against an MIC distribution for Staphylococcus aureus isolates was calculated. Results The mean (SD) age, weight, APACHE II score and CLCR were 37.0 (14.1) years, 86.8 (22.7) kg, 16.9 (5.3) and 163 (44) mL/min, respectively. A three-compartment linear population pharmacokinetic model was most appropriate. Covariates included in the model were CLCR on drug clearance and serum albumin concentration and body weight on the volume of the central compartment. The fractional target attainment for a 1 g intravenous 8-hourly dose for a CLCR of 50 mL/min was 88%, whereas for a patient with a CLCR of 215 mL/min, a dose of 2 g 6-hourly achieved 84% fractional target attainment. Conclusions Clinicians should be mindful of the effects of elevated CLCR and serum albumin concentrations on dosing requirements for post-trauma critically ill patients.

Free to read on publisher's website Objectives To describe the interstitial fluid (ISF) and plasma pharmacokinetics of meropenem in patients on continuous venovenous haemodiafiltration (CVVHDF). Patients and methods This was a prospective observational pharmacokinetic study. Meropenem (500 mg) was administered every 8 h. CVVHDF was targeted as a 2–3 L/h exchange using a polyacrylonitrile filter with a surface area of 1.05 m2 and a blood flow rate of 200 mL/min. Serial blood (pre- and post-filter), filtrate/dialysate and ISF concentrations were measured on 2 days of treatment (Profiles A and B). Subcutaneous tissue ISF concentrations were determined using microdialysis. Results A total of 384 samples were collected. During Profile A, the comparative median (IQR) ISF and plasma peak concentrations were 13.6 (12.0–16.8) and 40.7 (36.6–45.6) mg/L and the trough concentrations were 2.6 (2.4–3.4) and 4.9 (3.5–5.0) mg/L, respectively. During Profile B, the ISF trough concentrations increased by ∼40%. Meropenem ISF penetration was estimated at 63% (60%–69%) and 69% (65%–74%) for Profiles A and B, respectively, using comparative plasma and ISF AUCs. For Profile A, the plasma elimination t1/2 was 3.7 (3.3–4.0) h, the volume of distribution was 0.35 (0.25–0.46) L/kg, the total clearance was 4.1 (4.1–4.8) L/h and the CVVHDF clearance was 2.9 (2.7–3.1) L/h. Conclusions This is the first known report of concurrent plasma and ISF concentrations of a meropenem antibiotic during CVVHDF. We observed that the ISF concentrations of meropenem were significantly lower than the plasma concentrations, although the present dose was appropriate for infections caused by intermediately susceptible pathogens (MIC ≤4 mg/L).

OBJECTIVES To develop a mechanism-based model that describes the time course of the malaria parasite in infected mice receiving a combination therapy regimen of dihydroartemisinin and piperaquine. METHODS Total parasite density-time data from Swiss mice inoculated with Plasmodium berghei were used for the development of population models in S-ADAPT. The mice were administered a single intraperitoneal dose of 30 mg/kg dihydroartemisinin, 10 mg/kg piperaquine phosphate or a combination of both antimalarials at 64 h post-inoculation. In a separate study, mice received multiple dihydroartemisinin doses (5 × 10 mg/kg or 30 mg/kg dihydroartemisinin followed by two 10 mg/kg doses). Parasite recrudescence after treatment was defined using a model that incorporated each erythrocytic stage of the P. berghei life cycle. RESULTS The disposition of dihydroartemisinin and piperaquine was described by a one-compartment and two-compartment model, respectively. The estimated clearance was 1.95 L/h for dihydroartemisinin and 0.109 L/h for piperaquine. A turnover model described the parasite killing curve after single-agent dosing, with an estimated mean IC50 of 0.747 μg/L for dihydroartemisinin and 16.8 μg/L for piperaquine. In addition, the rate of parasite killing by dihydroartemisinin was almost 50-fold faster than for piperaquine. Parameters from the monotherapy models adequately described the parasite density-time curve following dihydroartemisinin/piperaquine combination therapy or multiple-dose regimens of dihydroartemisinin. CONCLUSIONS This study has developed mechanistic models that describe the parasite-time curve after single, multiple or combination dosing of antimalarials to mice. These structural models have potential application for pre-clinical investigations to design and refine artemisinin-based combination therapy dosage regimens.

Infections in critically ill patients continue to result in unacceptably high morbidity and mortality. Although few data exist for correlating antibiotic exposure with outcome, antibiotic dosing is likely to be highly important for maximizing resolution of infection in many patients. The practical and financial difficulties of performing pharmacokinetic (PK) studies in critically ill patients mean that analyses to maximize data such as Monte Carlo simulation (MCS) are highly valuable. MCS uses computer software to perform virtual clinical trials. The building blocks for MCS are: firstly, a robust population PK model from the patient population of interest; secondly, descriptors of the effect of covariates that influence the PK parameters; thirdly, description of the susceptibility of bacteria to the antibiotic and finally a PK/pharmacodynamic (PD) target associated with antibiotic efficacy. Probability of target attainment (PTA) outputs can then be generated that describe the proportion of patients that will achieve a pre-specified PD target for an MIC distribution. Such analyses can then inform dosing requirements, which can be used to have a high likelihood of achieving PK/PD targets for organisms with different MICs. In this issue of JAC, Zelenitsky et al. provide a very useful example of MCS for interpreting the optimal methods for dosing meropenem, piperacillin/tazobactam, cefepime and ceftobiprole in critically ill patients.

Background: Although QT prolongation is associated with increased risk of torsade de pointes (TdP), the precise relationship is not well defined. Aim: To evaluate the performance of a QT nomogram in assessing the risk of TdP from QTRR combinations. Design: Systematic review. Methods: We systematically searched MEDLINE/EMBASE for cases of drug-induced TdP. Controls were patients taking non-cardiotoxic drugs in overdose. Inclusion criteria were definite TdP, normal ECG before or after the event, association with a drug/toxin and QTRR measurements available. The upper bound of a QTRR cloud diagram developed from human preclinical studies was converted into a QT nomogram [QT vs. heart rate (HR)]. QTHR combinations for TdP cases and controls were plotted with the QT nomogram, and curves corresponding to a QTc 440 ms and QTc 500 ms for comparison (Bazetts correction). Results: We identified 129 cases of TdP. TdP cases occurred at lower HR values with longer QT intervals, with most cases occurring at HR 3090 bpm. Controls were more evenly distributed, with HR 40160 bpm. The sensitivity and specificity of the QT nomogram were 96.9 (95CI 93.999.9) and 98.7 (95CI 96.8100), respectively. For Bazett QTc 440 ms, sensitivity and specificity were 98.5 (95CI 96.3100) and 66.7 (95CI 58.674.7), respectively, whereas for Bazett QTc 500 ms they were 93.8 (95CI 89.698.0) and 97.2 (95CI 94.3100), respectively. Discussion: The QT nomogram is a clinically relevant risk assessment tool that accurately predicts arrhythmogenic risk for drug-induced QT prolongation. Further prospective evaluation of the nomogram is needed.

Free and total concentrations of cefazolin were compared in plasma and interstitial fluid during continuous intravenous infusion therapy. Seven patients, median age 53 (25-74) years, were administered a constant infusion of cefazolin at a mean (+/-s.d.) dose of 3.5 g (+/-1.1) per 24 h for greater than or equal to5 days. Four blisters were induced on the forearm of each patient for sampling of interstitial fluid. Free concentrations in plasma and interstitial fluid were similar, and correlated better than total concentrations (r(2) = 0.82, P = 0.005 versus r(2) = 0.54, P = 0.056). In all patients, the free concentrations in the interstitial fluid were at least two-fold the MIC90 for Staphylococcus aureus.

Wu DBC1, Chaiyakunapruk N1,2,3,4, Pratoomsoot C5, Lee KKC1, Chong HY1, Nelson RE6, Smith PF7, Kirkpatrick C8, Kamal MA9, Nieforth K7, Dall G7, Toovey S10, Kong DCM8, Kamauu A11, Rayner CR7 1School of Pharmacy, Monash University, Sunway, Malaysia ,2 Center of Pharmaceutical Outcomes Research (CPOR), Department of Pharmacy Practice, Faculty of Pharmaceutical Sciences, Naresuan University, Thailand, 3 School of Pharmacy, University of Wisconsin, Madison, USA, 4 School of Population Health, University of Queensland, Brisbane, Australia, 5Faculty of Public Health, Naresuan University, Thailand, 6University of Utah, Salt Lake City, UT, 7 d3 Medicine LLC, 8Monash University, Melbourne, Australia, 9Hoffman-La Roche, Inc., Nutley, NJ, 10Royal Free and University College Medical School, London, UK, 11Anolinx LLC, Salt Lake City