Dr Timothy Miles Rawson
Precision Prescribing Theme Lead at the NIHR Health Protection Research
Unit for Healthcare Associated Infections and Antimicrobial Resistance,
Imperial College London
A new study is aiming to help combat antimicrobial resistance by identifying ways to better tailor antibiotic prescribing to individual patients.
Current antibiotic prescribing focuses on a ‘one-size-fits-all’ approach and does not account for the differences in antibiotic drug concentration that similar antibiotic doses achieve within individual patients. That, according to Dr Timothy Rawson from Imperial College London (ICL), is a major knowledge gap.
Study on precision antibiotic prescribing
The DATA-TDM study will use technology and artificial intelligence (AI) techniques to analyse patient data to develop precision prescribing approaches. It can potentially reduce the threat of antimicrobial resistance (AMR) and of antibiotics becoming less effective. Rawson explains that AMR is a global health security issue with around 1.27 million deaths directly caused by drug-resistant infections in 2019.
Impact of antibiotic drug concentration
DATA-TDM seeks to address how to optimise the use of agents currently available by delivering a better understanding of how antibiotic drug concentration in individual patients impacts treatment outcomes.
Rawson says: “It will give us a unique dataset to perform analyses to better understand the true impact of that individual variation in drug concentration on outcome of infection and drive changes in practice to optimise how we deliver treatment for patients.” DATA-TDM is now recruiting 400 patients in a pilot programme at three London hospitals.
Unsuitable concentrations of drugs can be
associated with worse outcomes, lead to
side effects and the development of AMR.
Optimising antibiotics efficacy
With some antibiotics already becoming less effective, Rawson says understanding what happens to an antibiotic in an individual patient and then developing methods of adjusting the dose to optimise treatment is vital.
Unsuitable concentrations of drugs can be associated with worse outcomes, lead to side effects and the development of AMR. He explains that optimising antibiotic concentration gives patients the best chance of effective clinical outcomes; helps better understand side effects; and can characterise what may drive antibiotic resistance.
Unique dataset for targeted intervention
Rawson notes that research has focused on developing new antibiotics rather than how antibiotics are prescribed and used. The DATA-TDM study group is working with iCARE (imperial clinical analytics, research and evaluation) to create a powerful dataset for the development of tools and novel technologies to directly measure the concentration of antibiotics in patients and lead to targeted interventions.
The study will utilise wearable technology for real-time monitoring of antibiotics in patients; AI algorithms to inform individualised decision-making on antibiotic prescribing; and computer-controlled systems that deliver precise doses based on patient response to treatment.