Cefotaxime/sulbactam plus gentamicin as a potential carbapenem- and amikacin-sparing first-line combination for neonatal sepsis in high ESBL prevalence settings.

BACKGROUND: Infection with ESBL-producing Enterobacteriaceae infection is ubiquitous in some neonatal ICUs and increasing levels of antibiotic resistance are a cause for urgent concern. Delineation of bacterial and viral sepsis can be challenging, often leading to patients receiving empirical antibiotics without or whilst waiting for a definitive causal diagnosis. Empirical therapy is often dependent on broad-spectrum 'Watch' antibiotics, contributing to further resistance. METHODS: ESBL-producing Enterobacteriaceae clinical isolates found to have caused neonatal sepsis and meningitis underwent a detailed in vitro screening including susceptibility testing, chequerboard combination analysis and hollow-fibre infection model dynamic analyses using combinations of cefotaxime, ampicillin and gentamicin in combination with ß-lactamase inhibitors. RESULTS: Additivity or synergy was found for all antibiotic combinations against seven Escherichia coli and three Klebsiella pneumoniae clinical isolates. Cefotaxime or ampicillin plus sulbactam combined with gentamicin was able to consistently inhibit the growth of ESBL-producing isolates at typical neonatal doses, and the combination cleared the hollow-fibre infection model system of organisms resistant to each agent alone. The combination of cefotaxime/sulbactam and gentamicin was consistently bactericidal at clinically achievable concentrations (Cmax of 180, 60 and 20 mg/L for cefotaxime, sulbactam and gentamicin, respectively). CONCLUSIONS: The addition of sulbactam to cefotaxime or ampicillin to the typical first-line empirical therapy could obviate the need for carbapenems and amikacin in settings with high ESBL-infection prevalence.

The use of continuous electronic prescribing data to infer trends in antimicrobial consumption and estimate the impact of stewardship interventions in hospitalized children.

BACKGROUND: Understanding antimicrobial consumption is essential to mitigate the development of antimicrobial resistance, yet robust data in children are sparse and methodologically limited. Electronic prescribing systems provide an important opportunity to analyse and report antimicrobial consumption in detail. OBJECTIVES: We investigated the value of electronic prescribing data from a tertiary children's hospital to report temporal trends in antimicrobial consumption in hospitalized children and compare commonly used metrics of antimicrobial consumption. METHODS: Daily measures of antimicrobial consumption [days of therapy (DOT) and DDDs] were derived from the electronic prescribing system between 2010 and 2018. Autoregressive moving-average models were used to infer trends and the estimates were compared with simulated point prevalence surveys (PPSs). RESULTS: More than 1.3 million antimicrobial administrations were analysed. There was significant daily and seasonal variation in overall consumption, which reduced annually by 1.77% (95% CI 0.50% to 3.02%). Relative consumption of meropenem decreased by 6.6% annually (95% CI -3.5% to 15.8%) following the expansion of the hospital antimicrobial stewardship programme. DOT and DDDs exhibited similar trends for most antimicrobials, though inconsistencies were observed where changes to dosage guidelines altered consumption calculation by DDDs, but not DOT. PPS simulations resulted in estimates of change over time, which converged on the model estimates, but with much less precision. CONCLUSIONS: Electronic prescribing systems offer significant opportunities to better understand and report antimicrobial consumption in children. This approach to modelling administration data overcomes the limitations of using interval data and dispensary data. It provides substantially more detailed inferences on prescribing patterns and the potential impact of stewardship interventions.

Pharmacokinetic and pharmacodynamic study of intranasal and intravenous dexmedetomidine.

BACKGROUND: Intranasal dexmedetomidine produces safe, effective sedation in children and adults. It may be administered by drops from a syringe or by nasal mucosal atomisation (MAD NasalTM). METHODS: This prospective, three-period, crossover, double-blind study compared the pharmacokinetic (PK) and pharmacodynamic (PD) profile of i.v. administration with these two different modes of administration. In each session each subject received 1 µg kg-1 dexmedetomidine, either i.v., intranasal with the atomiser or intranasal by drops. Dexmedetomidine plasma concentration and Ramsay sedation score were used for PK/PD modelling by NONMEM. RESULTS: The i.v. route had a significantly faster onset (15 min, 95% CI 15-20 min) compared to intranasal routes by atomiser (47.5 min, 95% CI 25-135 min), and by drops (60 min, 95%CI 30-75 min), (P<0.001). There was no significant difference in sedation duration across the three treatment groups (P=0.88) nor in the median onset time between the two modes of intranasal administration (P=0.94). A 2-compartment disposition model, with transit intranasal absorption and clearance driven by cardiac output using the well-stirred liver model, was the final PK model. Intranasal bioavailability was estimated to be 40.6% (95% CI 34.7-54.4%) and 40.7% (95% CI 36.5-53.2%) for atomisation and drops respectively. Sedation score was modelled via a sigmoidal Emax model driven by an effect compartment. The effect compartment had an equilibration half time 3.3 (95% CI 1.8-4.7) min-1, and the EC50 was estimated to be 903 (95% CI 450-2344) pg ml-1. CONCLUSIONS: There is no difference in bioavailability with atomisation or nasal drops. A similar degree of sedation can be achieved by either method. CLINICAL TRIAL REGISTRATION: HKUCTR-1617.

Advanced Methods for Dose and Regimen Finding During Drug Development: Summary of the EMA/EFPIA Workshop on Dose Finding (London 4-5 December 2014).

Inadequate dose selection for confirmatory trials is currently still one of the most challenging issues in drug development, as illustrated by high rates of late-stage attritions in clinical development and postmarketing commitments required by regulatory institutions. In an effort to shift the current paradigm in dose and regimen selection and highlight the availability and usefulness of well-established and regulatory-acceptable methods, the European Medicines Agency (EMA) in collaboration with the European Federation of Pharmaceutical Industries Association (EFPIA) hosted a multistakeholder workshop on dose finding (London 4-5 December 2014). Some methodologies that could constitute a toolkit for drug developers and regulators were presented. These methods are described in the present report: they include five advanced methods for data analysis (empirical regression models, pharmacometrics models, quantitative systems pharmacology models, MCP-Mod, and model averaging) and three methods for study design optimization (Fisher information matrix (FIM)-based methods, clinical trial simulations, and adaptive studies). Pairwise comparisons were also discussed during the workshop; however, mostly for historical reasons. This paper discusses the added value and limitations of these methods as well as challenges for their implementation. Some applications in different therapeutic areas are also summarized, in line with the discussions at the workshop. There was agreement at the workshop on the fact that selection of dose for phase III is an estimation problem and should not be addressed via hypothesis testing. Dose selection for phase III trials should be informed by well-designed dose-finding studies; however, the specific choice of method(s) will depend on several aspects and it is not possible to recommend a generalized decision tree. There are many valuable methods available, the methods are not mutually exclusive, and they should be used in conjunction to ensure a scientifically rigorous understanding of the dosing rationale.

Predicting CD4 T-Cell Reconstitution Following Pediatric Hematopoietic Stem Cell Transplantation.

Hematopoietic stem cell transplantation (HSCT) is an increasingly common treatment for children with a range of hematological disorders. Conditioning with cytotoxic chemotherapy and total body irradiation leaves patients severely immunocompromised. T-cell reconstitution can take several years due to delayed restoration of thymic output. Understanding T-cell reconstitution in children is complicated by normal immune system maturation, heterogeneous diagnoses, and sparse uneven sampling due to the long time spans involved. We describe here a mechanistic mathematical model for CD4 T-cell immune reconstitution following pediatric transplantation. Including relevant biology and using mixed-effects modeling allowed the factors affecting reconstitution to be identified. Bayesian predictions for the long-term reconstitution trajectories of individual children were then obtained using early post-transplant data. The model was developed using data from 288 children; its predictive ability validated on data from a further 75 children, with long-term reconstitution predicted accurately in 81% of the patients.

New generalized poisson mixture model for bimodal count data with drug effect: An application to rodent brief-access taste aversion experiments.

Pharmacodynamic (PD) count data can exhibit bimodality and nonequidispersion complicating the inclusion of drug effect. The purpose of this study was to explore four different mixture distribution models for bimodal count data by including both drug effect and distribution truncation. An example dataset, which exhibited bimodal pattern, was from rodent brief-access taste aversion (BATA) experiments to assess the bitterness of ascending concentrations of an aversive tasting drug. The two generalized Poisson mixture models performed the best and was flexible to explain both under and overdispersion. A sigmoid maximum effect (Emax ) model with logistic transformation was introduced to link the drug effect to the data partition within each distribution. Predicted density-histogram plot is suggested as a model evaluation tool due to its capability to directly compare the model predicted density with the histogram from raw data. The modeling approach presented here could form a useful strategy for modeling similar count data types.

Mathematical modelling to restore circulating IGF-1 concentrations in children with Crohn's disease-induced growth failure: a pharmacokinetic study.

OBJECTIVES: Children with Crohn's disease grow poorly, and inflammation depresses the response of insulin-like growth factor-1 (IGF-1) to growth hormone. Correcting the inflammation normalises growth velocity; however, removing inflammation cannot be achieved in all children. Our lack of understanding of IGF-1 kinetics has hampered its use, particularly as high IGF-1 concentrations over long periods may predispose to colon cancer. We hypothesised that mathematical modelling of IGF-1 would define dosing regimes that return IGF-1 concentrations into the normal range, without reaching values that risk cancer. DESIGN: Pharmacokinetic intervention study. SETTING: Tertiary paediatric gastroenterology unit. PARTICIPANTS: 8 children (M:F; 4:4) entered the study. All completed: 5 South Asian British; 2 White British; 1 African British. INCLUSION CRITERIA: Children over 10 years with active Crohn's disease (C reactive protein >10 mg/l or erythrocyte sedimentation rate >25 mm/h) and height velocity <-2 SD score. EXCLUSION CRITERIA: closed epiphyses; corticosteroids within 3 months; neoplasia or known hypersensitivity to recombinant human IGF-1 (rhIGF-1). INTERVENTIONS: Subcutaneous rhIGF-1 (120 µg/kg) per dose over two admissions: the first as a single dose and the second as twice daily doses over 5 days. PRIMARY OUTCOME: Significant increase in circulating IGF-1. SECONDARY OUTCOMES: Incidence of side effects of IGF-1. A mathematical model of circulating IGF-1 (Ac) was developed to include parameters of endogenous synthesis (Ksyn); exogenous uptake (Ka) from the subcutaneous dose (As): and IGF-1 clearance: where dAc/dt=Ksyn - Kout×Ac+Ka×As. RESULTS: Subcutaneous IGF-1 increased concentrations, which were maintained on twice daily doses. In covariate analysis, disease activity reduced Ksyn (p<0.001). Optimal dosing was derived from least squares regression fitted to a dataset of 384 Crohn's patients, with model parameters assigned by simulation. CONCLUSIONS: By using age, weight and disease activity scaling in IGF-1 dosing, over 95% of children will have normalised IGF-1 concentrations below +2.5 SDs of the normal population mean, a level not associated with cancer risk.