Visible particles in pharmaceutical powder excipients are typically counted manually. However, because the human eye’s ability to detect particles is subjective, manual counting is prone to operator-dependent bias and potential under- or overestimation of the presence of visible particles
This white paper describes an automated system to count visible particles without bias. This method can classify detected particles based on color, size and shape, allowing for discernment between technically unavoidable particles (TUPs) and atypical visible particles (AVPs). Utilizing this method can facilitate the detection of deviations in the production process and guide the optimization of excipient production processes.
We used this automated detection system to compare the levels of detectable and visible particles of various microcrystalline cellulose (MCC) grades produced by three global manufacturers. It was found that the number and type of detectable particles are different across different brands of MCC; for example, one brand contained more particles than the other two, the majority of which were 50-100 μm black particles.
The automated method presented here can provide an unprecedented level of reliability and detail in the counting of visible particles in powders.