In a previous post, I introduced the calculation to estimate the earliest time of bioreactor contamination.
And the reason anyone'd ever bother running this calculation is to help direct the focus of contamination investigation.
Have a look at the example from the previous post. The sterility samples collected showed that the 12,000-liter bioreactor was "clean" all the way through 84-hours. By the time 108-hours culture duration rolled around, the dO2 and pH had crashed, prompting us to send the bottles to QC Micro. QC Micro reports that then 96-hour sample was also "hot."
There are folks who'd look at this data and say,
Saying the 84-hour sample was "clean" is actually a mistake. It is more accurate to say, "Bioburden levels of the 84-hour sample were less than detectable." And using a clean 84-hour sample to vindicate prior manipulations would be a mistake by disqualifying true root causes.
On the other side of the spectrum are folks who say:
The most effective approach lies somewhere in between and - we think - is to estimate the growth rate of the microbe by assuming the last "clean" sample was simply less-than-detectable. And computing this growth rate.
Using this growth rate to estimate the earliest 1 CFU could have penetrated sterile barriers is one scientifically defensible way of balancing the last-clean vs. boil-the-oceans approaches.
As for the assumptions of this method, they are:
Get "Time of Contamination" Spreadsheet
And the reason anyone'd ever bother running this calculation is to help direct the focus of contamination investigation.
Have a look at the example from the previous post. The sterility samples collected showed that the 12,000-liter bioreactor was "clean" all the way through 84-hours. By the time 108-hours culture duration rolled around, the dO2 and pH had crashed, prompting us to send the bottles to QC Micro. QC Micro reports that then 96-hour sample was also "hot."There are folks who'd look at this data and say,
If we were clean at 84-hours, but hot at 96-hours, then bioreactor manipulations in that time-frame (84 to 96) are culprits for contamination.But what if there were no bioreactor manipulations in that time frame but a sterile envelope manipulation at 77-hours?
Saying the 84-hour sample was "clean" is actually a mistake. It is more accurate to say, "Bioburden levels of the 84-hour sample were less than detectable." And using a clean 84-hour sample to vindicate prior manipulations would be a mistake by disqualifying true root causes.
On the other side of the spectrum are folks who say:
We need to look at every single sterile-envelope manipulation of the bioreactor starting from the time of inoculation at 0-hours.This ocean-boiling approach is expensive and includes improbable root causes that ought to be disqualified.
The most effective approach lies somewhere in between and - we think - is to estimate the growth rate of the microbe by assuming the last "clean" sample was simply less-than-detectable. And computing this growth rate.
Using this growth rate to estimate the earliest 1 CFU could have penetrated sterile barriers is one scientifically defensible way of balancing the last-clean vs. boil-the-oceans approaches.
As for the assumptions of this method, they are:
- Constant growth rate of microbe. This method assumes that microbes entered the bioreactor in the growth phase and didn't stop. Since microbes (like spore-formers) can be in the stationary phase, the constant growth assumption tends to not include as much time as perhaps should be.
- 1 CFU inoculated the bioreactor. While it is unlikely that a bioreactor breach let in a single CFU or that the SIP killed all organisms except one, assuming 1 CFU tends to include more time and helps counter the assumption of constant growth.
- Once sample pulled, growth stopped. If the organism is an aerobe, this is a good assumption. If not, use the time of QC Micro count for (t).
Bioreactor contamination response is a lot like crime-scene response and investigation, and the contamination time-window calculation is a lot like estimating the time of death (of a murder victim). This information can be used to help rank probable cause and ultimately the most probable cause (i.e. identify the killer).
Get "Time of Contamination" Spreadsheet
1 comment:
Good point! We have taken a look at data from our samples before and ruled something out because the sample was "clean," but hadn't asked exactly how many CFUs were observed.
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