CyteCount: a novel bacterial electrophysiology method for rapid phenotypic antibiotic susceptibility testing of bacteria detected in clinical blood cultures.

Background Annually, 100,000 bloodstream infections are reported in the UK. Untreated infections can quickly lead to sepsis, a global health priority with 11 million deaths per year. While initial empirical therapy prior to blood culture results follows epidemiological data on drug resistance, laboratory antimicrobial susceptibility testing (AST), applied after detection of positive cultures, provides the first opportunity to optimise antibiotic treatment, a time-critical element in reducing mortality, morbidity and hospital stay. The rise in antimicrobial resistance makes minimising this dependence on empirical therapy a clinical priority. This is a primary data generation project taking Cytecom technology from proof of principle through to laboratory validation in preparation for clinical validation. Aim To enable communication of definitive chemotherapeutic advice to the clinical team up to 2 days earlier than conventional testing by a novel early and rapid AST Objectives To develop and validate our CyteCount technology for AST To establish the performance criteria (speed and cost threshold) for rapid AST to justify its uptake by the healthcare sector To produce an evidence generation pipeline for CyteCount system ready for assessment in a healthcare setting, conforming to NICE standards Research Question and Methods CyteCount uses cell fluorescence responses to electrical stimulation to provide excellent culture-independent estimates of colony forming units, with minimal operation time. Using a bench-top proof-of-concept system, we have shown this approach can detect antibiotic effects in under 1 hour. Building on this, we will use Sensitive and Resistant (S&R) strains of Escherichia coli to establish the protocol and automated analytical system for clinical use validated against the gold-standard EUCAST methods, thereby minimising time to assignment of S/R for clinically relevant antibiotic-organism combinations. This will enable assessment of our approach against requirements for uptake by the healthcare sector both locally in the NHS and globally. We will establish an automated computational analytical pipeline to support assessment of the technology for regulatory approval as a class A (hardware) and class C (software) medical device. Anticipated Impact and Dissemination Acceleration of AST after cultures flag positive from ~24 to under 2 hours offers major advantages to clinical management with early selection of the most appropriate antimicrobials potentially reducing patient length of stay and selection of narrow spectrum agents where appropriate. Applying these improvements to E. coli infections alone could equate to a financial saving for the NHS of ~£36 million per annum and a saving of 38 million tons of CO2 emissions. We will present at conferences and public outreach events with the support of the PPI advisory group and anticipate generating sufficient data for at least five research publications in high-quality peer-reviewed journals. We also plan to design a promotion campaign and webinars aimed at the NHS to engage with service users.