I have been very interested in recent popular discussions of “models”. No, I don’t mean fashion models; I mean models in scientific thinking. We in the cleaning validation community have a certain model of what happens in a cleaning process that could lead to cross-contamination of the next manufactured product. That model usually envisions that residues left on the cleaned equipment surfaces will transfer more or less completely and uniformly to the next manufactured product. How do we know this? Well, it seems like a reasonable scenario, even though we know there are probably situations where it is not exactly true. But, it is the model we use in designing our cleaning validation program.
Now, you are probably asking yourself “What does this have to do with solving problems by analogy?”
Okay, thinking of “models” caused me to think of one of my favorite books dealing with the nature of science, The Structure of Scientific Revolutions, by Thomas S. Kuhn. Kuhn, who is probably the premier historian of science, wrote this book in 1962. When I was an undergraduate at Michigan, we had a short class (one credit, I believe) that covered this book and Kuhn’s model of how science works, and specifically how scientific “revolutions” happened. So, I recently took the opportunity to reread the book (actually a second enlarged addition of 1970), and it was truly refreshing. Kuhn talks about how scientists ordinarily work under a paradigm (think “model”) of how the world operates (at least within their own scientific discipline). And, because a paradigm always has “loose ends”, the primary scientific endeavor within a given paradigm is puzzle solving, or in essence addressing all the loose ends that a paradigm entails. Kuhn addresses the issue of trying to solve a problem for which the scientist has no literal equivalent before. How is this done? Here is Kuhn’s answer:
“A phenomenon familiar to both students of science and historians of science provides a clue. The former regularly report that they have read through a chapter of their text, understood it perfectly, but nonetheless had difficulty solving a number of problems at the chapter’s end. Ordinarily, also, those difficulties dissolve in the same way. The student discovers, with or without the assistance of his instructor, a way to see his problem as like a problem he has already seen. Having seen the resemblance, grasped the analogy, between two or distinct problems, he can interrelate symbols and attach them to the nature in the ways that have proved effective before.”
Kuhn goes on to say “Scientists solve puzzles by modeling them on previous puzzle solutions….” The examples he discusses are related to mathematical equations used in the physical sciences. But, the principle of looking for analogies is helpful in non- mathematical puzzling problems. So, when you come across a puzzle (problem) in cleaning validation, think of things that might be similar, and see if you can come to an analogous solution.
Here is an example. If you follow my writings on swab sampling recovery studies, you are probably aware that I teach (or I believe) that as the amount of residue on the surface increases, then (other things being equal) the recovery percentage decreases. How do I know that? Well, I don’t have a lab, so I have not done any clear experiments to demonstrate that (although I have proposed experiments to do so). One possible analogy that might be appropriate to support my contention is the actual cleaning of soils (think of your product as a soil, even though most don’t like to call it that) on equipment surfaces. What is easier to clean, a surface with a large amount of soil, or a surface with a much smaller amount of soil? I think we all might intuitively say “the surface with the smaller amount” (and that is also based on prior experience). That is, other things being equal, the same cleaning process might remove “all” of the soil in the situation with the smaller amount of soil, but leave some soil behind in the situation with the greater amount of soil. So, in that latter situation, I would have to use a more aggressive cleaning process.
How does this apply to swab sampling recovery? Isn’t a cleaning process completely different from a swab sampling process; after all, the objectives are different? Yes, they are different, but there are similarities. In both a cleaning process and a swab sampling process, I am essentially (here is my analogy) removing a material from a surface. In one case I am removing it in cleaning process so the material can be safely disposed of; in the other case I am removing it in a swabbing process so the material can be analyzed by my HPLC (or TOC) process. If the larger amount of soil on the surface makes it more difficult to remove a larger percentage of that soil, might it not also be the case that the same principle holds true for swab sampling. In other words, even though the purpose of a cleaning process and a swabbing process are fundamentally different, from a process perspective there are similarities. (Note that this similarity is something I also point out in my webinars as to the variability of swabbing, because swabbing is like a type of manual cleaning and has elements of variability present in manual cleaning procedures.)
Are there other situations in cleaning validation where such analogies may be useful? I think so! Think about a Clean Hold Time (CHT) and look for similar situation which might suggest that a formal CHT protocol is not required if the equipment is stored dry and protected from external sources of bioburden. Thinking about a situation and doing an appropriate risk assessment is often a better approach to cleaning validation “puzzles” as compared to a “cookbook” answer.