12 results found
Wilson R, Arkell P, Riezk A, et al., 2022, Addition of probenecid to oral beta-lactam antibiotics: a systematic review and meta-analysis, Journal of Antimicrobial Chemotherapy, ISSN: 0305-7453
Arkell P, Wilson R, Antcliffe DB, et al., 2022, A pilot observational study of CSF vancomycin therapeutic drug monitoring during the treatment of nosocomial ventriculitis., Journal of Infection, ISSN: 0163-4453
McLeod J, Stadler E, Wilson R, et al., 2021, Electrochemical detection of cefiderocol for therapeutic drug monitoring, Electrochemistry Communications, Vol: 133, ISSN: 1388-2481
Cefiderocol is a novel siderophore-conjugated β-lactam antibiotic which has been approved for clinical use. It has demonstrated efficacy against infections caused by Gram-negative bacteria, including carbapenem-resistant strains. Novel antibiotics are rarely brought to market and, as such, are ideal candidates for therapeutic drug monitoring which enables optimised dosing across a range of clinical scenarios whilst also reducing the chances of antimicrobial resistance. Here we demonstrate direct electrochemical detection of cefiderocol by oxidation using untreated gold and glassy carbon electrodes as well as multi-walled carbon nanotube (MWCNT)-coated glassy carbon and foamed gold electrodes. Quantification of cefiderocol in the therapeutic range is demonstrated in spiked whole human blood using MWCNT-coated pyrolytic carbon screen-printed electrodes.
Rawson TM, Wilson R, Moore L, et al., 2021, Exploring the pharmacokinetics of phenoxymethylpenicillin (Penicillin-V) in adults: a healthy volunteer study, Open Forum Infectious Diseases, Vol: 8, Pages: 1-4, ISSN: 2328-8957
This healthy volunteer study aimed to explore Phenoxymethylpenicillin (Penicillin-V) pharmacokinetics (PK) to support the planning of large, dosing studies in adults. Volunteers were dosed with penicillin-V at steady state. Total and unbound penicillin-V serum concentration was determined and a base population PK model were fitted to the data.
Ming DK, Jangam S, Gowers SAN, et al., 2021, Real-time Continuous Measurement of Lactate through a Minimally-invasive Microneedle Biosensor: a Phase I Clinical Study
<jats:title>Abstract</jats:title><jats:sec><jats:title>Introduction</jats:title><jats:p>Determination of blood lactate levels supports decision-making in a range of medical conditions. Invasive blood-sampling and laboratory access are often required, and measurements provide a static profile at each instance. We conducted a Phase I clinical study validating performance of a microneedle patch for minimally-invasive, continuous lactate measurement in healthy volunteers.</jats:p></jats:sec><jats:sec><jats:title>Methods</jats:title><jats:p>Five healthy adult participants wore a solid microneedle biosensor on their forearms and undertook aerobic exercise for 30 minutes. The microneedle biosensor quantifies lactate concentrations in interstitial fluid (ISF) within the dermis continuously and in real-time. Outputs were captured as sensor current and compared with lactate concentrations from venous blood and microdialysis.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>The biosensor was well-tolerated. Participants generated a median peak venous lactate of 9.25 mmol/L (Interquartile range, 6.73 to 10.71). Microdialysate concentrations of lactate closely correlated with blood. Microneedle biosensor current followed venous lactate concentrations and dynamics, with good agreement seen in all participants. There was an estimated lag-time of 5 minutes (IQR -4 to 11 minutes) between microneedle and blood lactate measurements.</jats:p></jats:sec><jats:sec><jats:title>Conclusion</jats:title><jats:p>This study provides first-in-human data on use of a minimally-invasive microneedle biosensor for continuous lactate measurement, providing dynamic monitoring. The platform offers distinct advantages to frequent blood sampling in a wide range of clinical settings, especially where access to laboratory services is limited or b
Rawson TM, Wilson RC, O'Hare D, et al., 2021, Optimizing antimicrobial use: challenges, advances and opportunities, NATURE REVIEWS MICROBIOLOGY, Vol: 19, Pages: 747-758, ISSN: 1740-1526
Rawson TM, Hernandez B, Moore L, et al., 2021, A real-world evaluation of a case-based reasoning algorithm to support antimicrobial prescribing decisions in acute care, Clinical Infectious Diseases, Vol: 72, Pages: 2103-2111, ISSN: 1058-4838
BackgroundA locally developed Case-Based Reasoning (CBR) algorithm, designed to augment antimicrobial prescribing in secondary care was evaluated.MethodsPrescribing recommendations made by a CBR algorithm were compared to decisions made by physicians in clinical practice. Comparisons were examined in two patient populations. Firstly, in patients with confirmed Escherichia coli blood stream infections (‘E.coli patients’), and secondly in ward-based patients presenting with a range of potential infections (‘ward patients’). Prescribing recommendations were compared against the Antimicrobial Spectrum Index (ASI) and the WHO Essential Medicine List Access, Watch, Reserve (AWaRe) classification system. Appropriateness of a prescription was defined as the spectrum of the prescription covering the known, or most-likely organism antimicrobial sensitivity profile.ResultsIn total, 224 patients (145 E.coli patients and 79 ward patients) were included. Mean (SD) age was 66 (18) years with 108/224 (48%) female gender. The CBR recommendations were appropriate in 202/224 (90%) compared to 186/224 (83%) in practice (OR: 1.24 95%CI:0.392-3.936;p=0.71). CBR recommendations had a smaller ASI compared to practice with a median (range) of 6 (0-13) compared to 8 (0-12) (p<0.01). CBR recommendations were more likely to be classified as Access class antimicrobials compared to physicians’ prescriptions at 110/224 (49%) vs. 79/224 (35%) (OR: 1.77 95%CI:1.212-2.588 p<0.01). Results were similar for E.coli and ward patients on subgroup analysis.ConclusionsA CBR-driven decision support system provided appropriate recommendations within a narrower spectrum compared to current clinical practice. Future work must investigate the impact of this intervention on prescribing behaviours more broadly and patient outcomes.
Rawson TM, Hernandez B, Wilson R, et al., 2021, Supervised machine learning to support the diagnosis of bacterial infection in the context of COVID-19, JAC-Antimicrobial Resistance, Vol: 3, Pages: 1-4, ISSN: 2632-1823
Background: Bacterial infection has been challenging to diagnose in patients with COVID-19. We developed and evaluated supervised machine learning algorithms to support the diagnosis of secondary bacterial infection in hospitalized patients during COVID-19.Methods: Inpatient data at three London hospitals for the first COVD-19 wave in March and April 2020 were extracted. Demographic, blood test, and microbiology data for individuals with and without SARS-CoV-2 positive PCR were obtained. A Gaussian-Naïve Bayes (GNB), Support Vector Machine (SVM), and Artificial Neuronal Network (ANN) were trained and compared using the area under the receiver operating characteristic curve (AUCROC). The best performing algorithm (SVM with 21 blood test variables) was prospectively piloted in July 2020. AUCROC was calculated for the prediction of a positive microbiological sample within 48 hours of admission. Results: A total of 15,599 daily blood profiles for 1,186 individual patients were identified to train the algorithms. 771/1186 (65%) individuals were SARS-CoV-2 PCR positive. Clinically significant microbiology results were present for 166/1186 (14%) patients during admission. A SVM algorithm trained with 21 routine blood test variables and over 8000 individual profiles had the best performance. AUCROC was 0.913, sensitivity 0.801, and specificity 0.890. Prospective testing on 54 patients on admission (28/54, 52% SARS-CoV-2 PCR positive) demonstrated an AUCROC of 0.960 (0.90-1.00). Conclusion: A SVM using 21 routine blood test variables had excellent performance at inferring the likelihood of positive microbiology. Further prospective evaluation of the algorithms ability to support decision making for the diagnosis of bacterial infection in COVID-19 cohorts is underway.
Arkell P, Mahboobani S, Wilson R, et al., 2021, Bronchoalveolar lavage fluid IMMY Sona Aspergillus lateral-flow assay for the diagnosis of invasive pulmonary aspergillosis: a prospective, real life evaluation, MEDICAL MYCOLOGY, Vol: 59, Pages: 404-408, ISSN: 1369-3786
Rawson TM, Wilson R, Holmes A, 2020, Understanding the role of bacterial and fungal infection in COVID-19, Clinical Microbiology and Infection, ISSN: 1198-743X
Rawson TM, Gowers SAN, Freeman DME, et al., 2019, Microneedle biosensors for real-time, minimally invasive drug monitoring of phenoxymethylpenicillin: a first-in-human evaluation in healthy volunteers, The Lancet Digital Health, Vol: 1, Pages: e335-e343, ISSN: 2589-7500
Background: Enhanced methods of drug monitoring are required to support the individualisation of antibiotic dosing. We report the first-in-human evaluation of real-time phenoxymethylpenicillin monitoring using a minimally invasive microneedle-based β-lactam biosensor in healthy volunteers.Methods: This first-in-human, proof-of-concept study was done at the National Institute of Health Research/Wellcome Trust Imperial Clinical Research Facility (Imperial College London, London, UK). The study was approved by London-Harrow Regional Ethics Committee. Volunteers were identified through emails sent to a healthy volunteer database from the Imperial College Clinical Research Facility. Volunteers, who had to be older than 18 years, were excluded if they had evidence of active infection, allergies to penicillin, were at high risk of skin infection, or presented with anaemia during screening. Participants wore a solid microneedle β-lactam biosensor for up to 6 h while being dosed at steady state with oral phenoxymethylpenicillin (five 500 mg doses every 6 h). On arrival at the study centre, two microneedle sensors were applied to the participant's forearm. Blood samples (via cannula, at −30, 0, 10, 20, 30, 45, 60, 90, 120, 150, 180, 210, 240 min) and extracellular fluid (ECF; via microdialysis, every 15 min) pharmacokinetic (PK) samples were taken during one dosing interval. Phenoxymethylpenicillin concentration data obtained from the microneedles were calibrated using locally estimated scatter plot smoothing and compared with free-blood and microdialysis (gold standard) data. Phenoxymethylpenicillin PK for each method was evaluated using non-compartmental analysis. Area under the concentration–time curve (AUC), maximum concentration, and time to maximum concentration were compared. Bias and limits of agreement were investigated with Bland–Altman plots. Microneedle biosensor limits of detection were estimated. The study was registered with Clinical
Gowers SAN, Freeman DME, Rawson TM, et al., 2019, Development of a minimally invasive microneedle-based sensor for continuous monitoring of β-lactam antibiotic concentrations in vivo, ACS sensors, Vol: 4, Pages: 1072-1080, ISSN: 2379-3694
Antimicrobial resistance poses a global threat to patient health. Improving the use and effectiveness of antimicrobials is critical in addressing this issue. This includes optimizing the dose of antibiotic delivered to each individual. New sensing approaches that track antimicrobial concentration for each patient in real time could allow individualized drug dosing. This work presents a potentiometric microneedle-based biosensor to detect levels of β-lactam antibiotics in vivo in a healthy human volunteer. The biosensor is coated with a pH-sensitive iridium oxide layer, which detects changes in local pH as a result of β-lactam hydrolysis by β-lactamase immobilized on the electrode surface. Development and optimization of the biosensor coatings are presented, giving a limit of detection of 6.8 μM in 10 mM PBS solution. Biosensors were found to be stable for up to 2 weeks at -20 °C and to withstand sterilization. Sensitivity was retained after application for 6 h in vivo. Proof-of-concept results are presented showing that penicillin concentrations measured using the microneedle-based biosensor track those measured using both discrete blood and microdialysis sampling in vivo. These preliminary results show the potential of this microneedle-based biosensor to provide a minimally invasive means to measure real-time β-lactam concentrations in vivo, representing an important first step toward a closed-loop therapeutic drug monitoring system.
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