In vivo human keyhole limpet hemocyanin challenge in early phase drug development: A systematic review.

Experimental exposure of healthy volunteers to the T-cell dependent neoantigen keyhole limpet hemocyanin (KLH) permits the evaluation of immunomodulatory investigational medicinal product (IMP) pharmacology prior to the recruitment of patient populations. Despite widespread use, no standardized approach to the design and conduct of such studies has been agreed. The objective of this systematic review was to survey the published literature where KLH was used as a challenge agent, describing methodology, therapeutic targets addressed, and pharmacodynamic outcome measures. We searched MEDLINE, EMBASE, clinicaltrials.gov, and Cochrane CENTRAL for studies using KLH challenge in humans between January 1, 1994, and April 1, 2022. We described key study features, including KLH formulation, dose, use of adjuvants, route of administration, co-administered IMPs, and end points. Of 2421 titles and abstracts screened, 46 met the inclusion criteria, including 14 (31%) early phase trials of IMP, of which 10 (71%) targeted T-cell co-stimulation. IMPs with diverse mechanisms demonstrated modulation of the humoral response to KLH, suggesting limited specificity of this end point. Two early phase IMP studies (14%) described the response to intradermal re-challenge (delayed type hypersensitivity). Challenge regimens for IMP assessment were often incompletely described, and exhibited marked heterogeneity, including primary KLH dose (25-fold variation: 100-2500 mcg), KLH formulation, and co-administration with adjuvants. Methodological heterogeneity and failure to exploit the access to tissue-level mechanism-relevant end points afforded by KLH challenge has impaired the translational utility of this paradigm to date. Future standardization, characterization, and methodological development is required to permit tailored, appropriately powered, mechanism-dependent study design to optimize drug development decisions.

Mycobacterium tuberculosis transmission in Birmingham, UK, 2009-19: An observational study.

Background: Over 10-years of whole-genome sequencing (WGS) of Mycobacterium tuberculosis in Birmingham presents an opportunity to explore epidemiological trends and risk factors for transmission in new detail. Methods: Between 1st January 2009 and 15th June 2019, we obtained the first WGS isolate from every patient resident in a postcode district covered by Birmingham's centralised tuberculosis service. Data on patients' sex, country of birth, social risk-factors, anatomical locus of disease, and strain lineage were collected. Poisson harmonic regression was used to assess seasonal variation in case load and a mixed-effects multivariable Cox proportionate hazards model was used to assess risk factors for a future case arising in clusters defined by a 5 single nucleotide polymorphism (SNP) threshold, and by 12 SNPs in a sensitivity analysis. Findings: 511/1653 (31%) patients were genomically clustered with another. A seasonal variation in diagnoses was observed, peaking in spring, but only among clustered cases. Risk-factors for a future clustered case included UK-birth (aHR=2·03 (95%CI 1·35-3·04), p < 0·001), infectious (pulmonary/laryngeal/miliary) tuberculosis (aHR=3·08 (95%CI 1·98-4·78), p < 0·001), and M. tuberculosis lineage 3 (aHR=1·91 (95%CI 1·03-3·56), p = 0·041) and 4 (aHR=2·27 (95%CI 1·21-4·26), p = 0·011), vs. lineage 1. Similar results pertained to 12 SNP clusters, for which social risk-factors were also significant (aHR 1·72 (95%CI 1·02-2·93), p = 0·044). There was marked heterogeneity in transmission patterns between postcode districts. Interpretation: There is seasonal variation in the diagnosis of genomically clustered, but not non-clustered, cases. Risk factors for clustering include UK-birth, infectious forms of tuberculosis, and infection with lineage 3 or 4. Funding: Wellcome Trust, MRC, UKHSA.

Population pharmacokinetics of free flucloxacillin in patients treated with oral flucloxacillin plus probenecid.

Oral flucloxacillin may be coadministered with probenecid to reduce flucloxacillin clearance and increase attainment of pharmacokinetic-pharmacodynamic (PK/PD) targets. The aims of this study were to develop a population PK model of free flucloxacillin when administered orally with probenecid, and to identify optimal dosing regimens for this combination. METHODS: We performed a prospective observational study of adults (45 participants) treated with oral flucloxacillin 1000 mg and probenecid 500 mg 8-hourly for proven or probable staphylococcal infections. Steady-state mid-dose-interval flucloxacillin measurements (45 concentrations) were combined with existing data from a crossover study of healthy participants receiving flucloxacillin with and without probenecid (11 participants, 363 concentrations). We developed a population pharmacokinetic model of free flucloxacillin concentrations within Monolix, and used Monte Carlo simulation to explore optimal dosing regimens to attain PK/PD targets proposed in the literature (free drug time above minimum inhibitory concentration). RESULTS: Flucloxacillin disposition was best described by a 1-compartment model with a lag time and first-order absorption. Free flucloxacillin clearance depended on probenecid, allometrically-scaled fat free mass (FFM) and estimated glomerular filtration rate (eGFR). Predicted PK/PD target attainment was suboptimal with standard dosing regimens with flucloxacillin alone, but substantially improved in the presence of probenecid. CONCLUSION: The simulation results reported can be used to identify dose regimens that optimise flucloxacillin exposure according to eGFR and FFM. Patients with higher FFM and eGFR may require the addition of probenecid and 6-hourly dosing to achieve PK/PD targets. The regimen was well-tolerated, suggesting a potential for further evaluation in controlled clinical trials to establish efficacy.

Bayesian Forecasting for Intravenous Tobramycin Dosing in Adults With Cystic Fibrosis Using One Versus Two Serum Concentrations in a Dosing Interval.

BACKGROUND: Intravenous tobramycin treatment requires therapeutic drug monitoring (TDM) to ensure safety and efficacy when used for prolonged treatment, as in infective exacerbations of cystic fibrosis. The 24-hour area under the concentration-time curve (AUC24) is widely used to guide dosing; however, there remains variability in practice around methods for its estimation. The objective of this study was to determine the potential for a sparse-sampling strategy using a single postinfusion tobramycin concentration and Bayesian forecasting to assess the AUC24 in routine practice. METHODS: Adults with cystic fibrosis receiving once-daily tobramycin had paired concentrations measured 2 hours (c1) and 6 hours (c2) after the end of infusion as routine monitoring. AUC24 exposures were estimated using Tucuxi, a Bayesian forecasting application that incorporates a validated population pharmacokinetic model. Simulations were performed to estimate AUC24 using the full data set using c1 and c2, compared with estimates using depleted data sets (c1 or c2 only), with and without concentration data from earlier in the course. The agreement between each simulation condition and the reference was assessed graphically and numerically using the median difference (∆) AUC24 and (relative) root mean square error (rRMSE) as measures of bias and accuracy, respectively. RESULTS: A total of 55 patients contributed 512 concentrations from 95 tobramycin courses and 256 TDM episodes. Single concentration methods performed well, with median ∆AUC24 <2 mg·h·L-1 and rRMSE of <15% for sequential c1 and c2 conditions. CONCLUSIONS: Bayesian forecasting implemented in Tucuxi, using single postinfusion concentrations taken 2-6 hours after tobramycin administration, yield similar exposure estimates to more intensive (two-sample) methods and are suitable for routine TDM practice.

Predictive Performance of Bayesian Vancomycin Monitoring in the Critically Ill.

OBJECTIVES: It is recommended that therapeutic monitoring of vancomycin should be guided by 24-hour area under the curve concentration. This can be done via Bayesian models in dose-optimization software. However, before these models can be incorporated into clinical practice in the critically ill, their predictive performance needs to be evaluated. This study assesses the predictive performance of Bayesian models for vancomycin in the critically ill. DESIGN: Retrospective cohort study. SETTING: Single-center ICU. PATIENTS: Data were obtained for all patients in the ICU between 1 January, and 31 May 2020, who received IV vancomycin. The predictive performance of three Bayesian models were evaluated based on their availability in commercially available software. Predictive performance was assessed via bias and precision. Bias was measured as the mean difference between observed and predicted vancomycin concentrations. Precision was measured as the sd of bias, root mean square error, and 95% limits of agreement based on Bland-Altman plots. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: A total of 466 concentrations from 188 patients were used to evaluate the three models. All models showed low bias (-1.7 to 1.8 mg/L), which was lower with a posteriori estimate (-0.7 to 1.8 mg/L). However, all three models showed low precision in terms of sd (4.7-8.8 mg/L) and root mean square error (4.8-8.9 mg/L). The models underpredicted at higher observed vancomycin concentrations (bias 0.7-3.2 mg/L for < 20 mg/L; -5.1 to -2.3 for ≥ 20 mg/L) and the Bland-Altman plots showed a great deviation between observed and predicted concentrations. CONCLUSIONS: Bayesian models of vancomycin show not only low bias, but also low precision in the critically ill. Thus, Bayesian-guided dosing of vancomycin in this population should be used cautiously.

Determinants of vancomycin nephrotoxicity when administered to outpatients as a continuous 24-hour infusion.

Vancomycin continuous infusion (VCI) is used to treat serious Gram-positive infections in outpatients. This study was conducted to retrospectively investigate the rate of nephrotoxicity and associated risk factors in out-patients on VCI between May 2013 and November 2018. Vancomycin concentration was monitored twice-weekly to ensure adequate concentrations while avoiding high concentrations linked to nephrotoxicity (a rise in serum creatinine of ≥50% or 44 µmol/L from baseline). The likelihood of developing nephrotoxicity was evaluated using multivariable logistic regression. The 223 patients treated had a mean (standard deviation) age of 61 (16.7) years, baseline serum creatinine of 83.9 (21.2) µmol/L and estimated glomerular filtration rate (eGFR) of 80.6 (20.1) mL/min/1.73m2. Most patients (66%) were treated for bone and joint infections. Eight patients (3.6%) developed nephrotoxicity. In the most parsimonious model, nephrotoxicity was independently associated with an increased median (interquartile range) weighted-average serum vancomycin concentration (28.0 [24.3-32.6] vs. 22.4 [20.2-24.5] mg/L; odds ratio [OR] 1.25; 95% confidence interval [95% CI] 1.09-1.46; P<0.002) and Charlson co-morbidity index (OR 1.62; 95% CI 1.07-2.47; P=0.02). Post-hoc analysis identified 26 patients with a lower nephrotoxicity threshold (rise in serum creatinine of ≥30% or 27 µmol/L). Independent predictors of nephrotoxicity in this group were an increased weighted-average vancomycin concentration, diabetes, con-gestive heart failure and exposure to non-loop diuretics. The nephrotoxicity rate during VCI in this study was lower than previously reported (3.6% vs 15.0-17.0%).  Reducing the weighted-average serum vancomycin concentration may reduce nephrotoxicity while maintaining efficacy.

Clinical decision support in a hospital electronic prescribing system informed by local data: experience at a tertiary New Zealand centre.

BACKGROUND: An electronic prescribing and administration (ePA) system has been progressively rolled out to Canterbury District Health Board (CDHB, Christchurch, New Zealand) public hospitals since 2014, and is currently used for around 1300 tertiary beds. ePA data can be used to monitor user behaviour, and to evaluate and inform the local customisation of clinical decision support (CDS) tools within the ePA system. AIMS: To describe retrospectively illustrative vignettes of CDHB ePA analyses that have been used for CDS. METHODS: Alerts were developed according to a set of common principles agreed upon by the CDHB CDS Working Group. Alerts were informed and evaluated by extracting and parsing data for various time periods during 2016 to 2018 from the CDHB ePA database. RESULTS: There was a median of 74 000 prescriptions a month. After examining 525 spironolactone prescriptions, the high dose alert threshold was set at 100 mg with an expected alert burden of 3%. The presence of a ceftriaxone shortage prescribing alert for 1 week was associated with a prescribing rate that was lower than 95% of the preceding 52 weeks. Following review of 367 fentanyl patch alerts, revision of the alert led to false positives falling from 43% to 3% (P < 0.0001). At the point of firing, 6% of antithrombotic drug interactions alerts led to immediate changes in prescriptions (94% overridden), and a further 22% were changed within 30 min after the alert. CONCLUSIONS: Local data extracts from ePA systems can inform iterative configuration of the software and monitor user behaviour.

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.

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.