This joint presentation provides an overview of the APAS Independence, a laboratory automation device using artificial intelligence to read and interpret microbial growth on culture plates.

Introduction of automation into laboratories is a multi-faceted consideration requiring several stakeholders to inform decisions.

This presentation discusses the application of artificial intelligence for environmental monitoring during pharmaceutical manufacturing.

This presentation discusses the opportunity to improve environmental monitoring plate reading workflows at AstraZeneca through the use of artificial intelligence for automated reading of agar plates using APAS PharmaQC.

Microbiological methods remain deeply rooted in traditional practices and new technologies are being considered to improve the agility, accuracy, consistency, and data integrity within pharmaceutical laboratories.

A key foundation to Good Manufacturing Practice, is the execution and routine review of a robust environmental monitoring program. This takes the form of collecting environmental samples from surfaces, personnel and the cleanroom air, whether that be active or passive sampling.

This study assessed the performance of the APAS Independence with PharmaQC analysis module to identify growth on TSA culture media. The study assessed the performance on 1,515 environmental monitoring plates collected at AstraZeneca’s manufacturing facility during routine production.

Nitroxoline is one of the recommended first-line drugs for the treatment of uncomplicated urinary tract infections (uUTIs), but it is not included in the usual panels of automated susceptibility testing (AST) platform systems, such as MicroScan or Vitek.

Direct antimicrobial susceptibility testing (dAST) from urine samples using disc diffusion methods is in widespread use in some countries, allowing for the provision of results earlier than traditional AST methods, at a lower cost.

The LADR Zentrallabor Dr. Kramer & Kollegen, a laboratory in Geesthacht, Germany presented their evaluation of the APAS technology for both Infection Control (MRSA and VRE screening) and Urine screening applications at DGHM 2022 in Berlin.

This study evaluated the APAS Independence automated plate reader system and compared it to the laboratory’s manual standard of care (SOC) for processing urine cultures.

Laboratory automation with Artificial Intelligence (AI) features have now emerged into routine diagnostic clinical use to interpret growth on agar plates.

The low prevalence (~1% in UK) of MRSA colonisation means much time is spent reading and reporting negative culture plates. Similarly, a large proportion of urine cultures yield no significant bacterial growth. As such, a large amount of scientist time is spent reporting negative samples.

Urine cultures (UC) constitute up to 30-40% of the workflow in clinical microbiology laboratories. Staffing considerations represent contemporary challenges, new tools are needed to address increasing demands and the evolving diversification of microbiology workflow.

Urine cultures are amongst the highest volume tests run in clinical microbiology laboratories and usually require considerable manual labor to perform.

Investigation of urine samples remains a core focus for microbiology laboratories and has largely remained manual in nature.

Screening of MRSA samples in routine microbiology is an important service to assist with infection control surveillance.

Examination of urine culture is one of the most commonly performed microbiology tests accounting for a significant proportion of the microbiology workload.

Urine cultures are amongst the highest volume tests run in clinical microbiology laboratories and usually require considerable manual labour to perform.

Disc diffusion remains an essential part of AST and EUCAST has recently expanded its guidelines to include breakpoints for rapid disc diffusion reading at 4, 6 or 8 hours.

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Screening for MRSA colonisation is a routine task in the microbiology laboratory, with the standard method being culture on chromogenic media.

Culture-based MRSA screening is an important part of infection control in everyday clinical practice where fast and reliable results are essential.

Screening for MRSA colonisation is a routine task in the microbiology laboratory, with the standard method being culture on chromogenic media.

Automated systems have emerged to facilitate the interpretation of bacteriology culture with and without artificial intelligence (AI).

This study was conducted to evaluate artificial intelligence (AI)-based VRE-detection algorithms in combination…

In clinical diagnostic laboratories, the early detection of bacteria directly impacts early reporting of clinical results and thus patient care.

Watch the webinar: Microbiology Workstation Automation: An alternative approach to laboratory automation

Automated imaging and interpretation of urine cultures using artificial intelligence with composite reference standard…

An evaluation of the APAS Independence’s ability to accurately triage MRSA cultures compared to human interpretation.

Dr Glen Hansen’s Poster on Intelligent Automation presented at the American Society of Microbiology (ASM) Microbe in…

As culture reading can be highly subjective and time-demanding the use of artificial intelligence such as the APAS®…

AI-based systems that aid in the plate-reading process may increase the overall sample throughout.

Despite significant developments in automation, microbiology remains a highly manual and labour-intensive discipline.

Comparison Between Digital Image and Traditional Plate Reading Using Urine Cultures.

The subject of laboratory error was examined during a symposium at the ASM Microbe 2016 conference in Boston, MA.

In recent years there has been an increase in the application of image analysis technologies within the clinical…

While advancements have been made in some areas of pathology with diagnostic materials being screened using image…