Press Release
Five separate posters featuring the APAS Independence were presented at the 31st European Congress of Clinical Microbiology & Infectious Diseases (ECCMID) held online on 9th – 12th of July 2021
The posters were from laboratories around the world and represented the largest body of clinical data featuring the APAS Independence presented at ECCMID to date. The studies focussed on the use of APAS Independence for infection control and assessed the performance of the APAS Independence artificial intelligence (AI)-algorithms for the detection of VRE and MRSA.
The APAS Independence consistently demonstrated a high sensitivity and specificity for the detection of bacterial growth when compared with traditional manual reading methods (plate in hand). The body of evidence highlighted the suitability of the APAS Independence to be used in a variety of clinical environments, including alongside total laboratory automation systems.
One study also evaluated the potential use of the APAS Independence for early culture plate reading. In an initial pilot study, the ability of the APAS technology to detect bacterial growth was compared to a microbiologist over 30-minute time intervals. The results suggest that the APAS technology can assist in early reads of VRE culture plates and contribute to improved infection control surveillance.
Peter Bradley, General Manager at Clever Culture Systems said:
“Laboratories are challenged to do more with the staff they have. The increase in multi-drug resistant organisms around the world is driving an increase in infection control screening programs resulting in greater testing volumes for clinical laboratories. The data presented at ECCMID 2021 provide a clear demonstration of how the APAS Independence can be used to safely and reliably automate the reading of infection control samples, enabling laboratories to meet this growing challenge.”
The 5 Posters are available to view under the scientific library, including an interview with the presenting authors of each poster:
Validation of APAS Independence (CCS) AI-Algorithms to detect MRSA in a routine setup
Evaluation of an automated culture plate reading instrument for MRSA culture screening