Conclusion
In addition to the various factors previously shown to affect VRL (such as viewing angle, distance, and lighting conditions),
the new data in this study indicate that there is also a large variation in the VRL across different surface types, both in
terms of materials for construction and, in the case of metal surfaces, the roughness. The data also provide supplementary
evidence that the VRL varies with individual compounds, thereby further adding to the repository of knowledge concerning the
effectiveness of the visual-inspection process during cleaning as well as helping to define the scope of applicability. If
visual examination is to be used as the sole criterion for ensuring equipment cleanliness, a wide range of factors need to
be considered. For example, where equipment is constructed from more than one material type, the absolute surface areas for
each type of material should be taken into consideration in calculating the maximum theoretical residual contamination level.
The relationship between metal-surface roughness and VRL indicates the importance of knowing the roughness for each equipment
item in order to determine the maximum potential contamination level accurately. Accordingly, any procedural use of "visibly
clean" as a pass criterion should be supported by periodic checks of the surface roughness to ensure that the basis for acceptance
is not compromised. Metal-surface roughness is a factor to be considered for any user requirement specification when ordering
new equipment.
In view of the variability in VRLs on some surfaces between different compounds, in a multiproduct plant, it is necessary
to conduct a test on each new material to determine the individual VRL. This test is particularly important as currently there
is no evident predictor of VRL from any physical or chemical property of the subject material. The test is straightforward
and significantly more rapid to perform than development of a swab or rinse method.
The above data offer definite potential for improving the efficiency and accuracy of the cleaning process by using VRLs alone.
The limitations should, however, be recognized and the risk assessed on a case-by-case basis (i.e., the applicability under
potentially different lighting and access conditions in the plants should be risk-assessed). Even if visual inspection, supported
by the above data, is not directly used as a basis for total plant-cleaning verification, it may prove useful for individual
items of equipment, or as an aid to deviation investigations.
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David Ian Fletcher, PhD, is lead quality advisor/Lean Sigma Black Belt at AstraZeneca Pharmaceutical Development, Silk Road Business Park, Macclesfield,
Cheshire, SK10 2NA, UK. David.Fletcher@astrazeneca.com
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