Manufacturers utilizing bioprocesses for production need accurate and reliable tools for monitoring bioreactors. The key monitoring parameter that many bioprocess engineers rely on is viable cell density. This is a compound parameter arising from measurement of the cellular concentration and the total cellular viability. Viable cell density is the mathematical product of these two primary pieces of information.
As bioprocess manufacturing has grown in size and scope over the last several decades, so too have the needs for making accurate measurements across reactors within a single manufacturing plant, and amongst manufacturing plants that may be spread around the world. While the viable cell density parameter is well understood by professionals at all levels, the underlying principles affecting its measurement are subtly complex: on the surface, they are simple to understand, but can produce unexpected results if one is not careful in their application. In particular, a common concern amongst bioprocess manufacturers is instrument-to-instrument variability, which refers to the expected coefficient of variance of a measurement made on two identical instruments with two identical samples.
While this is a simple concept, once again, complexity awaits the unprepared. There are many different factors which can lead to instrument-to-instrument variability. These include: instrument service history, pipetting errors, underlying measurement principle, sample volume and concentration, sample temperature history, etc. At the most basic level, since viable cell density is a compound parameter, the variability of each of the primary measurements (concentration and viability) must be understood separately. While there are many methods for measuring cellular viability with various strengths and weaknesses, the trypan blue analysis remains the most popular and well-tested.
The purpose of this application note is to provide advice on best practices to minimize instrument to instrument variability for the Vi-CELL* Automated Cell Viability Analyzer and to demonstrate what levels of variability may be expected under nearly ideal circumstances.