Traditionally, QC microbiology has involved a lot of repetitive manual tasks using highly skilled technical staff to set up, read tests, and interpret results. However, automation, AI, and data analytics can lead to a much more efficient and more accurate microbial QC process, reducing the potential for human error and improving overall quality control in various industries such as pharmaceuticals, food and beverage, and healthcare.

Why should labs embrace change?
The advantages of using more technology are manifold, including:

• Increased Workflow Efficiency - from sample collection, processing, reading, and recording results - removes skilled staff from error-prone, dull, repetitive tasks with potential for RSI.
• Achieve the Impossible - such as processing higher throughput of samples with the same resources or reducing operator contamination via robotic sampling.
• Objective and Fully Traceable Data - remove operator bias, have access to and share trends, highlight problems, and transform lab results into really usable data.

In this rapidmicrobiology special focus, we showcase some key technologies that can revolutionize workflows and make your QC systems work better and smarter. Discover from Anke Hossfield (Merck), a recent guest on the rapidmicrobiology podcast, how automation and digitalization are helping pharma QC microbiologists and why it's important to choose the right partner for your journey.

Starting at the beginning, sample collection can be automated to reduce the potential of operator contamination in clean room, Micronview have a robotic system which can open and close doors and automatically move itself to where it needs to be and do the sampling!

Food safety is also moving ahead, bioMerieux have invested in Augmented Diagnostics, i.e. bringing various technologies together that do not just report results but data that allows food manufacturers make better, more informed, and faster decisions. Biomire offers a turn-key solution, nomad microbial solutions fully integrate field-ready test devices, smart data management applications, and expert services, offering producers everything they need to design a custom monitoring plan or launch an investigation in a matter of days.

But is it AI? For true AI vs. data interpretation, a system needs to have the ability to learn from its data and be able to apply that knowledge – Clever Culture’s APAS^® PharmaQC, Rapid Micro Biosystem's Growth Direct^®, and Diamidex's MICA use advanced imaging technology combined with learning algorithms to automate the analysis and interpretation of microbiology culture plates. For clinical labs, COPAN ITALIA's PhenoMATRIX^® A.I. algorithms analyze colony growth, morphology, color, and hemolysis using your custom interpretation rules, sorting and suggesting a follow-up for each plate that just needs to be validated with a click of a button. PhenoMATRIX^® TAG automatically detects and tags the best colonies to be picked to perform the proper workup for each colony according to your custom rules which can include a patient's clinical data.

Are Microbiologists Out of a Job?
At the moment, mostly it's just the mundane, tedious work and data handling/interpretation/sharing that is removed, which allows microbiologists to spend more time focussing on the result interpretation and QC improvement side, or they could just create more artistic culture plate pictures.

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