COPAN continues to innovate and is leading the field of Artificial Intelligence (A.I.) and digital culture plate reading in clinical Microbiology.

A groundbreaking study titled “Automated Detection of Streptococcus pyogenes pharyngitis using COLOREX Strep A CHROMagar and WASPLab™ Artificial Intelligence Chromogenic Detection Module Software” was recently published on the Journal of Clinical Microbiology (JCM).

The study is the first-in-its class peer-reviewed publication on PhenoMATRIX™ used with COLOREX Strep A culture media for the automatic detection of Group A Strep (GAS). Group A Strep (GAS) pharyngitis is an infection caused by Streptococcus pyogenes, responsible for 20% to 30% of sore throats in children between 5 and 15 years old. Pharyngeal swab samples were collected from pediatric patients with suspected pharyngitis at the Children’s Hospital Los Angeles (CHLA).

The samples were analyzed using COPAN’s Chromogenic Detection Module (CDM), which is part of the PhenoMATRIX™ suite of A.I. algorithms. The Chromogenic Detection Module is designed to accurately detect and differentiate Strep A on chromogenic agar allowing the laboratory to provide faster results than with traditional culture methods and manual reading.  Any suspected positive Group A Strep growth detected by the algorithm was confirmed by Matrix-Assisted Laser Desorption/Ionization-Time of Flight (MALDI-ToF) mass spectrometry.

All specimens in this study were collected using COPAN ESwab™, which enabled specimens to be processed in parallel using a molecular assay. The study concluded that “PhenoMATRIX™ CDM software and COLOREX Strep A Agar can improve detection of GAS from throat specimens and compared favorable to molecular testing.” This breakthrough publication is the first of its kind using PhenoMATRIX™ with the novel COLOREX™ chromogenic media for the automatic detection of Group A Strep.  It reflects the advancements in Artificial Intelligence technology occurring in Microbiology laboratories and the way they are impacting laboratory medicine favorably.

Microbiology is one of the most labor-intensive disciplines within the clinical laboratory field, and its role is of vital importance to overall healthcare.  It is well established that laboratory professionals are asked to do more with fewer resources and to constantly demonstrate the value of laboratory medicine in clinical outcomes.

“As the demand for laboratory testing increases and reimbursement rates and qualified personnel dwindle at a rapid speed, COPAN is investing in developing comprehensive A.I. solutions to support and amplify the laboratories’ ingenuity and maximize the use of their resources,” stated Norman Sharples, CEO of COPAN Diagnostics, Inc.  “Having worked in a clinical laboratory in the past, it is fascinating to see Microbiology at an interesting juxtaposition where traditional techniques, like planting and streaking on culture media, combine with incredible advances in Artificial Intelligence and digital plate reading. COPAN is staying at the forefront of this new exciting frontier for Microbiology” added Sharples.

With the interest in A.I. in Microbiology increasing, COPAN is excited to support a new American Society for Microbiology (ASM) webinar series titled “Artificial Intelligence: Applications for the Clinical Microbiology Laboratory of Today.”

The ASM advanced level webinar series consists of five presentations. It is designed for technologists, Microbiologists, Microbiology Supervisors, Laboratory Directors, Infectious Disease Physicians, among others. Each presentation in the series is approved for 1.0 Continuing Education credit provided by the ASCLS P.A.C.E.® Program. The next webinar is on October 30^th at 2:00 pm (Eastern). The webinars are conducted every other Wednesday thereafter at 2:00 pm (Eastern) concluding on Wednesday December 11^th, 2019.

To learn more about A.I. and to register for the next thought-provoking webinar on this series, visit: https://www.pathlms.com/asm/courses/14014.

To access the unprecedented open-access JCM publication of the use of A.I. for automated detection of Group A Strep, visit: https://jcm.asm.org/content/early/2019/08/22/JCM.00811-19.