Microbial enumeration testing in the pharmaceutical QC lab is based around well proven traditional manual methods that have changed little since the creation of the first pharmacopeia. These manual processes rely heavily on the training, expertise and judgment of the individuals who perform them. Improvements have been made to the processes to minimize variation such as: use of commercial media, validated incubators, verification signatures and electronic batch records; however, the ability to accurately see and enumerate colonies, then accurately record the information to paper or electronic system, is still a weak link in the forensic data trail.
In this four-part series, we will explore the unprecedented capabilities of automated plate counting: consistent counting, time savings and reduced fatigue for analysts, and automated capturing of complete, original data for review, monitoring and trending analysis. Along the way, we will also suggest key considerations for QC labs evolving from manual plate counts to automation.
Digital systems reduce manual transcription errors which are always present when people are involved. McDowall1 cites studies of “fat finger” error rates that range from 0.3% up to 39%; he believes the realistic rate in most analytical labs to be in the 0.3% – 3% range. These errors are eliminated with digital data collection and transfer.
It is important that digital systems collect all raw (original) data generated during the conduct of the assay, so a reviewer can determine if all decisions made by the analyst(s) can be scientifically justified. There are two actions that add complexity which must be included in the data set:
The regulatory expectation is set forth in the FDA Data Integrity Guidance2 on page 10:
FDA expects processes to be designed so that data required to be created and maintained cannot be modified without a record of the modification.
For automated (digital) plate counting systems, the original data required to reconstruct the test would include original plate images plus workflow configuration plus manual adjustments made by a scientist. It is the combination of these three that determines a reportable result value. For the first image capture of a plate, the workflow settings must be captured and linked to the image, along with the automated result counts. The image and workflow settings permit the result counts to be reconstructed at any point in the future.
Advanced systems can capture plate images over time and use algorithms to determine if an original “colony” was something inanimate such as a particle or a viable, growing colony. This capability permits more accurate colony counts. For this technology two options exist:
In addition to a time series of images, it is possible for an analyst to examine the images (or the plate) and determine that the reported result must be adjusted, based on their observation. From a data integrity perspective, this manual adjustment (override) is a high-risk activity. As a result, the system must preserve the original (automated) values and the new values entered by an authorized scientist. Of course, this override capability must be restricted to very few individuals. The system must require a change reason to be manually entered by the authorized scientist, and the change reason (along with the original and override values, date and time stamp, and the scientist’s digital identity) must be preserved. Ideally, the system would set a flag to indicate a manual override has been recorded. This flag is an aide to the second person reviewer.
Early automated plate count systems often captured a plate image, processed the image to produce a colony count, then deleted the image. Images were not retained due to storage limitations – thousands of plate images required storage space beyond the capabilities of most firms. This was considered as equivalent to the manual process since microbial plates were discarded several days after viewing. Cloud storage vendors now make it feasible to store all captured images online. This is a large step forward, as it permits review and re-calculation of results months after a plate has been physically discarded. If questions arise about the process, original data is available to permit a complete review of the testing record. This has important implications when sterile operations and their risks to patient safety are implicated in manufacturing issues.
The complete record of original data would be:
Original plate capture (plus workflow settings, date/time stamp, analyst ID)
All time sequence images (plus workflow settings, date/time stamp, analyst ID)
Manual adjustments made by authorized scientist (plus automated values prior to adjustment, scientist ID, date/time stamp, change justification)
In the concluding post of our four-part series, we will discuss best practices for security and control of automated plate counting systems. Look for it soon!
Mark Newton is an associate senior quality assurance consultant at Eli Lilly and Company. David L. Jones is director of marketing and industry affairs at Rapid Micro Biosystems. This content previously appeared in edited form in the April 2022 issue of Cleanroom Technology.
1McDowall, Robert. Fat Finger, Falsification, or Fraud? LCGC Europe. 24(4): 194-200. April, 2012. https://www.chromatographyonline.com/view/fat-finger-falsification-or-fraud
2Food and Drug Administration (FDA). Data Integrity and Compliance With Drug cGMP: Questions and Answers. Guidance for Industry. December 2018. https://www.fda.gov/media/119267/download