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

Population variability in animal health: Influence on dose-exposure-response relationships: Part II: Modelling and simulation

During the 2017 Biennial meeting, the American Academy of Veterinary Pharmacology and Therapeutics hosted a 1‐day session on the influence of population variability on dose‐exposure‐response relationships. In Part I, we highlighted some of the sources of population variability. Part II provides a summary of discussions on modelling and simulation tools that utilize existing pharmacokinetic data, can integrate drug physicochemical characteristics with species physiological characteristics and dosing information or that combine observed with predicted and in vitro information to explore and describe sources of variability that may influence the safe and effective use of veterinary pharmaceuticals

Dose rationale and pharmacokinetics of dexmedetomidine in mechanically ventilated new-borns : impact of design optimisation

Purpose: There is a need for alternative analgosedatives such as dexmedetomidine in neonates. Given the ethical and practical difficulties, protocol design for clinical trials in neonates should be carefully considered before implementation. Our objective was to identify a protocol design suitable for subsequent evaluation of the dosing requirements for dexmedetomidine in mechanically ventilated neonates. Methods: A published paediatric pharmacokinetic model was used to derive the dosing regimen for dexmedetomidine in a first-in-neonate study. Optimality criteria were applied to optimise the blood sampling schedule. The impact of sampling schedule optimisation on model parameter estimation was assessed by simulation and re-estimation procedures for different simulation scenarios. The optimised schedule was then implemented in a neonatal pilot study. Results: Parameter estimates were more precise and similarly accurate in the optimised scenarios, as compared to empirical sampling (normalised root mean square error: 1673.1% vs. 13,229.4% and relative error: 46.4% vs. 9.1%). Most importantly, protocol deviations from the optimal design still allowed reasonable parameter estimation. Data analysis from the pilot group (n = 6) confirmed the adequacy of the optimised trial protocol. Dexmedetomidine pharmacokinetics in term neonates was scaled using allometry and maturation, but results showed a 20% higher clearance in this population compared to initial estimates obtained by extrapolation from a slightly older paediatric population. Clearance for a typical neonate, with a post-menstrual age (PMA) of 40 weeks and weight 3.4 kg, was 2.92 L/h. Extension of the study with 11 additional subjects showed a further increased clearance in pre-term subjects with lower PMA. Conclusions: The use of optimal design in conjunction with simulation scenarios improved the accuracy and precision of the estimates of the parameters of interest, taking into account protocol deviations, which are often unavoidable in this event-prone population

Artemisinins

Artemisinins were discovered to be highly effective antimalarial drugs shortly after the isolation of the parent artemisinin in 1971 in China. These compounds combine potent, rapid antimalarial activity with a wide therapeutic index and an absence of clinically important resistance. Artemisinin containing regimens meet the urgent need to find effective treatments for multidrug resistant malaria and have recently been advocated for widespread deployment. Comparative trials of artesunate and quinine for severe malaria are in progress to see if the persistently high mortality of this condition can be reduced

Standard Error of Empirical Bayes Estimate in NONMEM® VI.

The pharmacokinetics/pharmacodynamics analysis software NONMEM® output provides model parameter estimates and associated standard errors. However, the standard error of empirical Bayes estimates of inter-subject variability is not available. A simple and direct method for estimating standard error of the empirical Bayes estimates of inter-subject variability using the NONMEM® VI internal matrix POSTV is developed and applied to several pharmacokinetic models using intensively or sparsely sampled data for demonstration and to evaluate performance. The computed standard error is in general similar to the results from other post-processing methods and the degree of difference, if any, depends on the employed estimation options

Pharmacokinetic–pharmacodynamic integration and modelling of oxytetracycline for the calf pathogens Mannheimia haemolytica and Pasteurella multocida

A calf tissue cage model was used to study the pharmacokinetics (PK) and pharmacodynamics (PD) of oxytetracycline in serum, inflamed (exudate) and noninflamed (transudate) tissue cage fluids. After intramuscular administration, the PK was characterized by a long mean residence time of 28.3 hr. Based on minimum inhibitory concentrations (MICs) for six isolates each of Mannheimia haemolytica and Pasteurella multocida, measured in serum, integration of in vivo PK and in vitro PD data established area under serum concentration–time curve (AUC0–∞)/MIC ratios of 30.0 and 24.3 hr for M. haemolytica and P. multocida, respectively. Corresponding AUC0–∞/MIC ratios based on MICs in broth were 656 and 745 hr, respectively. PK-PD modelling of in vitro bacterial time–kill curves for oxytetracycline in serum established mean AUC0–24 hr/MIC ratios for 3log10 decrease in bacterial count of 27.5 hr (M. haemolytica) and 60.9 hr (P. multocida). Monte Carlo simulations predicted target attainment rate (TAR) dosages. Based on the potency of oxytetracycline in serum, the predicted 50% TAR single doses required to achieve a bacteriostatic action covering 48-hr periods were 197 mg/kg (M. haemolytica) and 314 mg/kg (P. multocida), respectively, against susceptible populations. Dosages based on the potency of oxytetracycline in broth were 25- and 27-fold lower (7.8 and 11.5 mg/kg) for M. haemolytica and P. multocida, respectively

Informatics: the fuel for pharmacometric analysis

The current informal practice of pharmacometrics as a combination art and science makes it hard to appreciate the role that informatics can and should play in the future of the discipline and to comprehend the gaps that exist because of its absence. The development of pharmacometric informatics has important implications for expediting decision making and for improving the reliability of decisions made in model-based development. We argue that well-defined informatics for pharmacometrics can lead to much needed improvements in the efficiency, effectiveness, and reliability of the pharmacometrics process. The purpose of this paper is to provide a description of the pervasive yet often poorly appreciated role of informatics in improving the process of data assembly, a critical task in the delivery of pharmacometric analysis results. First, we provide a brief description of the pharmacometric analysis process. Second, we describe the business processes required to create analysis-ready data sets for the pharmacometrician. Third, we describe selected informatic elements required to support the pharmacometrics and data assembly processes. Finally, we offer specific suggestions for performing a systematic analysis of existing challenges as an approach to defi ning the next generation of pharmacometric informatics

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

Towards personalized treatment of pain using a quantitative systems pharmacology approach

Pain is a complex biopsychosocial phenomenon of which the intensity, location and duration depends on various underlying components. Treatment of pain is associated with considerable inter-individual variability, and as such, requires a personalized approach. However, a priori prediction of optimal analgesic treatment for individual patients is still challenging. Another challenge is the assessment and treatment of pain in patients unable to self-report pain. In this mini-review, we first provide a brief overview of the various components underlying pain, and their associated biomarkers. These include clinical, psychosocial, neurophysiological, and biochemical components. We then discuss the use of empirical and mechanism-based pharmacokinetic-pharmacodynamic modelling to support personalized treatment of pain. Finally, we propose how these concepts can be extended to a quantitative systems pharmacology (QSP) approach that integrates the components of clinical pain and treatment response. This integrative approach can support predictions of optimal pharmacotherapy of pain, compared with approaches that focus on single components of pain. Moreover, combination of QSP modelling with state-of-the-art metabolomics approaches may offer unique possibilities to identify novel pain biomarkers. Such biomarkers could support both the personalized treatment of pain and translational drug development of novel analgesic agents. In conclusion, a QSP approach will likely improve our ability to predict pain and treatment response, paving the way for personalized treatment of pain

Pharmacotherapy in paediatric epilepsy: from trial and error to rational drug and dose selection – a long way to go

Whereas ongoing efforts in epilepsy research focus on the underlying disease processes, the lack of a physiologically-based rationale for drug and dose selection contributes to inadequate treatment response in children. In fact, limited information on the interindividual variation in pharmacokinetics and pharmacodynamics of anti-epileptic drugs (AEDs) in children drive prescription practice, which relies primarily on dose regimens according to a mg/kg basis. Such practice has evolved despite advancements in paediatric pharmacology showing that growth and maturation processes do not correlate linearly with changes in body size. Areas covered: In this review we aim to provide 1) a comprehensive overview of the sources of variability in the response to AEDs, 2) insight into novel methodologies to characterise such variation and 3) recommendations for treatment personalisation. Expert Opinion: The use of pharmacokinetic-pharmacodynamic principles in clinical practice is hindered by the lack of biomarkers and by practical constraints in the evaluation of polytherapy. The identification of biomarkers and their validation as tools for drug development and therapeutics will require some time. Meanwhile, one should not miss the opportunity to integrate the available pharmacokinetic data with modelling and simulation concepts to prevent further delays in the development of personalised treatments for paediatric patients