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WEBINAR: Know It Before You Grow It: Case Studies and Approaches for Rapid Mold Detection

Presented by Danielle DeCesaro, Product Manager, Growth Direct® Automation, Rapid Micro Biosystems

Rapid Micro Biosystems®, Product Manager, Danielle DeCesaro, discusses a comparison of traditional-manual microbial colony counting to advanced automation technologies, such as microbial detection and enumeration with the Growth Direct® System, providing study data specific to the criticality and impact of rapid mold detection.



The use of environmental monitoring (EM) testing is crucial for contamination control in cleanrooms and production areas. Mold contamination is considered a loss of control over the environment according to Annex 1. Due to the significant impact of mold contamination, detecting the presence of mold quickly is essential for patient safety. Sophisticated vision algorithms combined with automated colony counting can confirm the qualitative presence of mold in less than 24 hours and has shown to detect a panel of sixteen common environmental mold isolates with ≥ 95% accuracy. In software verification studies, automated mold detection was shown to detect mold when present across those sixteen species within 12 – 24 hours, with a consistent overall count within validated testing parameters, in this case: 72 hours.


Case studies have demonstrated that automated mold detection enhances EM testing workflow and eliminates the need for additional operator assessment. This leads to faster remediation using validated cleaning procedures to return facilities to a decontaminated state. This presentation will explore validation approaches for this rapid microbial method, including deviation investigations and reporting for mold contamination when it has been detected.

In this webinar you'll learn:

* Demonstration of accelerated time-to-detect within as little as a day for mold species

* Comparison of workflow values using case study examples

* Relationship of rapid, automated, mold differentiation to Annex 1


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