Optimising antimicrobial prescribing through bio-sensor guided precision prescribing
Lead Research Organisation:
Imperial College London
Department Name: Infectious Disease
Abstract
The sensor technology has been developed for some beta-lactam agents and we have aptamers for other critical antimicrobials, including colistin, voriconazole, and aminoglycosides. Within this project we aim to extend the technology to develop and evaluate the biosensor closed-loop technology for antimicrobials targeting resistant Gram-negative bacteria, including the novel drug cefiderocol. To achieve this the following objectives will be addressed:
1. Evaluate the efficacy and acceptability of the biosensor in healthy volunteers at the Imperial Clinical Research Facility (ICRF). Up to 60 individuals will be recruited to attend the ICRF for 2-3 dosing periods. Rich plasma PK sampling will be taken during this period, which will provide data for validation of the device, whilst also allowing population pharmacokinetics of these populations to be reported and assessed at the same time. The data gathered will inform further biosensor optimisation. Patients will also be consented to undergo subcutaneous tissue microdialysis at the time of sensing to ensure calibration between the current gold standard for monitoring interstitial antimicrobial levels. Months 1 - 12 months
2. Develop and optimise an aptamer-based biosensor for a range of antimicrobials, including cefiderocol which target AMR Gram-negative bacteria. The aptamer will be selected using an established selection pipeline. Biosensor fabrication will be based on that previously developed in the group for other targets and will be optimised for cefiderocol. The efficacy of the biosensor will be assessed in vitro. Months 4 - 24
3. Use the rich plasma and microdialysis data to characterise PK-PD responses to identify optimal PK-PD targets and develop PK-PD model. This will support the development of the closed-loop controller algorithms. Months 1 - 24
4. Evaluate the sensor within different patient cohorts and compare to plasma PK samples, taken during dosing periods whilst wearing the sensor device. Individuals will be stratified to ensure that the sensor is tested on individuals who may have wide PK variability including those on renal replacement, obese individuals, and septic patients. Routine PD data, such as C-Reactive Protein (CRP), creatinine, and organism characteristics will be collected to allow PK-PD model linkage and evaluation to determine the optimal PK-PD indicator for response to therapy and toxicity of these agents. Months 12 - 36
5. Develop closed-loop controller algorithms based upon the optimised PK-PD indices defined during the PK sampling work. Incorporate the sensor data into our closed-loop control system for optimised antimicrobial delivery. Months 24 - 36
1. Evaluate the efficacy and acceptability of the biosensor in healthy volunteers at the Imperial Clinical Research Facility (ICRF). Up to 60 individuals will be recruited to attend the ICRF for 2-3 dosing periods. Rich plasma PK sampling will be taken during this period, which will provide data for validation of the device, whilst also allowing population pharmacokinetics of these populations to be reported and assessed at the same time. The data gathered will inform further biosensor optimisation. Patients will also be consented to undergo subcutaneous tissue microdialysis at the time of sensing to ensure calibration between the current gold standard for monitoring interstitial antimicrobial levels. Months 1 - 12 months
2. Develop and optimise an aptamer-based biosensor for a range of antimicrobials, including cefiderocol which target AMR Gram-negative bacteria. The aptamer will be selected using an established selection pipeline. Biosensor fabrication will be based on that previously developed in the group for other targets and will be optimised for cefiderocol. The efficacy of the biosensor will be assessed in vitro. Months 4 - 24
3. Use the rich plasma and microdialysis data to characterise PK-PD responses to identify optimal PK-PD targets and develop PK-PD model. This will support the development of the closed-loop controller algorithms. Months 1 - 24
4. Evaluate the sensor within different patient cohorts and compare to plasma PK samples, taken during dosing periods whilst wearing the sensor device. Individuals will be stratified to ensure that the sensor is tested on individuals who may have wide PK variability including those on renal replacement, obese individuals, and septic patients. Routine PD data, such as C-Reactive Protein (CRP), creatinine, and organism characteristics will be collected to allow PK-PD model linkage and evaluation to determine the optimal PK-PD indicator for response to therapy and toxicity of these agents. Months 12 - 36
5. Develop closed-loop controller algorithms based upon the optimised PK-PD indices defined during the PK sampling work. Incorporate the sensor data into our closed-loop control system for optimised antimicrobial delivery. Months 24 - 36
People |
ORCID iD |
| Alison Holmes (Primary Supervisor) | |
| James McLeod (Student) |