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Evaluating the APAS Independence System for Automated Microbial Detection in Environmental Monitoring: Poster
1Bristol Myers Squibb jennifer.hester@bms.com.
PDA Journal of Pharmaceutical Science and Technology
|February 28, 2026
Summary
Automated microbial detection systems, like the APAS Independence System, are crucial for pharmaceutical manufacturing. This evaluation shows the system offers high accuracy and reliability for environmental monitoring, supporting Good Manufacturing Practice (GMP) compliance.
Area of Science:
- Microbiology
- Pharmaceutical Manufacturing
- Quality Control
Background:
- Automated microbial detection systems are vital for pharmaceutical manufacturing efficiency, accuracy, and Good Manufacturing Practice (GMP) compliance.
- The APAS Independence System by Clever Culture Systems was assessed for environmental monitoring (EM) at Bristol Myers Squibb (BMS).
Purpose of the Study:
- To evaluate the APAS Independence System's suitability for automated microbial colony counting in pharmaceutical environmental monitoring.
- To compare the automated counts from the APAS system against traditional manual counts for compendial strains and EM samples.
Main Methods:
- The APAS Independence System was used for automated counting of 55 mm and 90 mm microbial plates after standard incubation.
- Automated colony counts were compared to manual counts, analyzing performance metrics like accuracy, precision, and false positive/negative rates for various organisms.
Main Results:
- The APAS system demonstrated high accuracy (≥70%) and reliability across most tested organisms for both plate sizes.
- Performance metrics indicated the system's robustness for routine environmental monitoring applications.
Conclusions:
- The APAS Independence System is suitable for GMP use in pharmaceutical environmental monitoring.
- Implementation involves a validation strategy combining vendor AI validation with site-specific instrument qualification.
- This study informs digitalization strategies in microbiological quality control by highlighting the capabilities and limitations of automated colony detection.
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