Intermittent Presumptive Treatment for Malaria

A better understanding of the pharmacodynamics of intermittent presumptive treatment, says White, will guide more rational policymakin

Population Pharmacokinetics and Pharmacodynamics of Extended-Infusion Piperacillin and Tazobactam in Critically Ill Children

The study objective was to evaluate the population pharmacokinetics and pharmacodynamics of extended-infusion piperacillintazobactam in children hospitalized in an intensive care unit. Seventy-two serum samples were collected at steady state from 12 patients who received piperacillin-tazobactam at 100/12.5 mg/kg of body weight every 8 h infused over 4 h. Population pharmacokinetic analyses were performed using NONMEM, and Monte Carlo simulations were performed to estimate the piperacillin pharmacokinetic profiles for dosing regimens of 80 to 100 mg/kg of the piperacillin component given every 6 to 8 h and infused over 0.5, 3, or 4 h. The probability of target attainment (PTA) for a cumulative percentage of the dosing interval that the drug concentration exceeds the MIC under steady-state pharmacokinetic conditions (TMIC) of\u3e50% was calculated at MICs ranging from 0.25 to 64 mg/liter. The mean ± standard deviation (SD) age, weight, and estimated glomerular filtration rate were 5 ± 3 years, 17 ± 6.2 kg, and 118 ± 41 ml/min/1.73m2, respectively. A one-compartment model with zero-order input and first-order elimination best fit the pharmacokinetic data for both drugs. Weight was significantly associated with piperacillin clearance, and weight and sex were significantly associated with tazobactam clearance. Pharmacokinetic parameters (mean ± SD) for piperacillin and tazobactam were as follows: clearance, 0.22 ± 0.07 and 0.19 ± 0.07 liter/h/kg, respectively; volume of distribution, 0.43 ± 0.16 and 0.37 ± 0.14 liter/kg, respectively. All extended-infusion regimens achieved PTAs of\u3e90% at MICs of/liter. Only the 3-h infusion regimens given every 6 h achieved PTAs of\u3e90% at an MIC of 32 mg/liter. For susceptible bacterial pathogens, piperacillin-tazobactam doses of\u3e80/10 mg/kg given every 8 h and infused over 4 h achieve adequate pharmacodynamic exposures in critically ill children

Pharmacodynamic Analysis of a Fluid Challenge.

OBJECTIVE: This study aims to describe the pharmacodynamics of a fluid challenge over a 10-minute period in postoperative patients. DESIGN: Prospective observational study. SETTING: General and cardiothoracic ICU, tertiary hospital. PATIENTS: Twenty-six postoperative patients. INTERVENTION: Two hundred and fifty-milliliter fluid challenge performed over 5 minutes. Data were recorded over 10 minutes after the end of fluid infusion MEASUREMENTS AND MAIN RESULTS:: Cardiac output was measured with a calibrated LiDCOplus (LiDCO, Cambridge, United Kingdom) and Navigator (Applied Physiology, Sydney, Australia) to obtain the Pmsf analogue (Pmsa). Pharmacodynamics outcomes were modeled using a Bayesian inferential approach and Markov chain Monte Carlo estimation methods. Parameter estimates were summarized as the means of their posterior distributions, and their uncertainty was assessed by the 95% credible intervals. Bayesian probabilities for groups' effect were also derived. The predicted maximal effect on cardiac output was observed at 1.2 minutes (95% credible interval, -0.6 to 2.8 min) in responders. The probability that the estimated area under the curve of central venous pressure was smaller in nonresponders was 0.12. (estimated difference, -4.91 mm Hg·min [95% credible interval, -13.45 to 3.3 mm Hg min]). After 10 minutes, there is no evidence of a difference between groups for any hemodynamic variable. CONCLUSIONS: The maximal change in cardiac output should be assessed 1 minute after the end of the fluid infusion. The global effect of the fluid challenge on central venous pressure is greater in nonresponders, but not the change observed 10 minutes after the fluid infusion. The effect of a fluid challenge on hemodynamics is dissipated in 10 minutes similarly in both groups

Metabolism of ticagrelor in patients with acute coronary syndromes.

© The Author(s) 2018Ticagrelor is a state-of-the-art antiplatelet agent used for the treatment of patients with acute coronary syndromes (ACS). Unlike remaining oral P2Y12 receptor inhibitors ticagrelor does not require metabolic activation to exert its antiplatelet action. Still, ticagrelor is extensively metabolized by hepatic CYP3A enzymes, and AR-C124910XX is its only active metabolite. A post hoc analysis of patient-level (n = 117) pharmacokinetic data pooled from two prospective studies was performed to identify clinical characteristics affecting the degree of AR-C124910XX formation during the first six hours after 180 mg ticagrelor loading dose in the setting of ACS. Both linear and multiple regression analyses indicated that ACS patients presenting with ST-elevation myocardial infarction or suffering from diabetes mellitus are more likely to have decreased rate of ticagrelor metabolism during the acute phase of ACS. Administration of morphine during ACS was found to negatively influence transformation of ticagrelor into AR-C124910XX when assessed with linear regression analysis, but not with multiple regression analysis. On the other hand, smoking appears to increase the degree of ticagrelor transformation in ACS patients. Mechanisms underlying our findings and their clinical significance warrant further research.Peer reviewedFinal Published versio

Fluconazole Monotherapy Is a Suboptimal Option for Initial Treatment of Cryptococcal Meningitis Because of Emergence of Resistance.

Cryptococcal meningitis is a lethal disease with few therapeutic options. Induction therapy with fluconazole has been consistently demonstrated to be associated with suboptimal microbiological and clinical outcomes. Exposure to fluconazole causes dynamic changes in antifungal susceptibility, which are associated with the development of aneuploidy. The implications of this phenomenon for pharmacodynamics of fluconazole for cryptococcal meningitis are poorly understood. The pharmacodynamics of fluconazole were studied using a hollow-fiber infection model (HFIM) and a well-characterized murine model of cryptococcal meningoencephalitis. The relationship between drug exposure and both antifungal killing and the emergence of resistance was quantified. The same relationships were further evaluated in a recently described group of patients with cryptococcal meningitis undergoing induction therapy with fluconazole at 800 to 1,200 mg/day. The pattern of emergence of fluconazole resistance followed an "inverted U." Resistance amplification was maximal and suppressed at ratios of the area under the concentration-time curve for the free, unbound fraction of the drug to the MIC (fAUC:MIC) of 34.5 to 138 and 305.6, respectively. Emergence of resistance was observed in vivo with an fAUC:MIC of 231.4. Aneuploidy with duplication of chromosome 1 was demonstrated to be the underlying mechanism in both experimental models. The pharmacokinetic (PK)-pharmacodynamic model accurately described the PK, antifungal killing, and emergence of resistance. Monte Carlo simulations from the clinical pharmacokinetic-pharmacodynamic model showed that only 12.8% of simulated patients receiving fluconazole at 1,200 mg/day achieved sterilization of the cerebrospinal fluid (CSF) after 2 weeks and that 83.4% had a persistent subpopulation that was resistant to fluconazole. Fluconazole is primarily ineffective due to the emergence of resistance. Treatment with 1,200 mg/day leads to the killing of a susceptible subpopulation but is compromised by the emergence of resistance.IMPORTANCE Cryptococcal meningitis is a lethal disease with few treatment options. The incidence remains high and intricately linked with the HIV/AIDS epidemic. In many parts of the world, fluconazole is the only agent that is available for the initial treatment of cryptococcal meningitis despite considerable evidence that it is associated with suboptimal microbiological and clinical outcomes. Fluconazole has a fungistatic mode of action: it predominantly inhibits growth rather than causing fungal killing. Our work shows that the pattern of fluconazole activity is caused by the emergence of resistance in Cryptococcus not detected by standard susceptibility tests, with chromosomal duplication/aneuploidy as the main mechanism. Resistance emergence is related to drug exposure and occurs with the use of clinically relevant regimens. Hence, fluconazole (and potentially other agents that target 14-alpha-demethylase) is compromised by an intrinsic property that limits its effectiveness. However, this resistance may be potentially overcome by dosage escalation or the use of combination therapy

Single dose pharmacodynamics of amphotericin B against Aspergillus species in an in vitro pharmacokinetic/pharmacodynamic model

Conventional MIC testing of amphotericin B results in narrow MIC ranges challenging the detection of resistant strains. In order to discern amphotericin B pharmacodynamics, the in vitro activity of amphotericin B was studied against Aspergillus isolates with the same MIC with a new in vitro pharmacokinetic/pharmacodynamic (PK/PD) model that simulates amphotericin B human plasma levels. Clinical isolates of A. fumigatus, A. terreus and A flavus with the same CLSI modal MICs of 1 mg/l were exposed to amphotericin B concentrations following the plasma concentration-time profile after single bolus administration with Cmax 0.6, 1.2, 2.4 and 4.8 mg/L. Fungal growth was monitored up to 72h based on galactomannan production. Complete growth inhibition was observed only against A. fumigatus with amphotericin B Cmax ≥2.4 mg/L. At lower Cmaxs 0.6 and 1.2 mg/L, a significant growth delay of 34h and 52h was observed, respectively (pA flavus>A. terreus in the in vitro PK/PD model possibly reflecting the different concentration- and time-dependent inhibitory/killing activities amphotericin B exerting against these species

Can we prevent antimicrobial resistance by using antimicrobials better?

Since their development over 60 years ago, antimicrobials have become an integral part of healthcare practice worldwide. Recently, this has been put in jeopardy by the emergence of widespread antimicrobial resistance, which is one of the major problems facing modern medicine. In the past, the development of new antimicrobials kept us one step ahead of the problem of resistance, but only three new classes of antimicrobials have reached the market in the last thirty years. A time is therefore approaching when we may not have effective treatment against bacterial infections, particularly for those that are caused by Gram-negative organisms. An important strategy to reduce the development of antimicrobial resistance is to use antimicrobials more appropriately, in ways that will prevent resistance. This involves a consideration of the pharmacokinetic and pharmacodynamics properties of antimicrobials, the possible use of combinations, and more appropriate choice of antimicrobials, which may include rapid diagnostic testing and antimicrobial cycling. Examples given in this review include Mycobacterium tuberculosis, Gram-negative and Gram-positive organisms. We shall summarise the current evidence for these strategies and outline areas for future development

Pharmacokinetic/pharmacodynamic modelling approaches in paediatric infectious diseases and immunology.

Pharmacokinetic/pharmacodynamic (PKPD) modelling is used to describe and quantify dose-concentration-effect relationships. Within paediatric studies in infectious diseases and immunology these methods are often applied to developing guidance on appropriate dosing. In this paper, an introduction to the field of PKPD modelling is given, followed by a review of the PKPD studies that have been undertaken in paediatric infectious diseases and immunology. The main focus is on identifying the methodological approaches used to define the PKPD relationship in these studies. The major findings were that most studies of infectious diseases have developed a PK model and then used simulations to define a dose recommendation based on a pre-defined PD target, which may have been defined in adults or in vitro. For immunological studies much of the modelling has focused on either PK or PD, and since multiple drugs are usually used, delineating the relative contributions of each is challenging. The use of dynamical modelling of in vitro antibacterial studies, and paediatric HIV mechanistic PD models linked with the PK of all drugs, are emerging methods that should enhance PKPD-based recommendations in the future