Excerpt from Cleaning
Validation: An Exclusive Publication
Using Swabs for Cleaning Validation A Review
Using Swabs for Cleaning Validation A Review
Cleaning
and cleaning validation are crucial to many industries. Clean swabs applied
skillfully to areas that have been cleaned can be used to show the
effectiveness of that cleaning. The swab, usually wet, is wiped across a
cleaned region. The swab, or an extract from the swab, is then analyzed
physically, chemically or biologically for contamination. The levels of
contamination found are compared against the "blanks," the levels in
swabs of the same type that were not rubbed on the surface being tested, and
against a limit. Sufficient replication is done to make a statistically valid
statement that cleaning was effective. The major choices - swabs, cleaning
liquid, areas to be sampled, extraction, analytical method and statistical
analysis - are discussed.
Introduction
Pharmaceutical,
bio-medical device and even food preparation industries are concerned about the
cleanliness - physical, chemical and especially biological - of their products.
These industries have materials that need regular careful cleaning, and some
have requirements for validating such cleaning, demonstrating that required
levels of cleanliness have been met. They want to prove the efficacy of their
cleaning methods. For example, "Cleaning and validation of cleaning are
among the most critical issues facing producers of recombinant DNA protein
products, monoclonal antibodies (MAbs), and oligonucleotide therapeutics,"
according to Adner and Sofer (1994). As noted below, the Food and Drug
Administration (FDA) has taken validation of cleaning very seriously.
It
is widely recognized that contamination control is crucial to these industries.
Here we deal with the cleaning of surfaces, rather than the cleaning of gases
or liquids, generally done by filtration. This article discusses the use of
swabs (fabrics on handles or shafts) for cleaning validation.
Contaminants
Contamination
comes from the environment, from the materials in use, the processes and the
people. Viable and non-viable particles and various organic and inorganic
materials often contaminate the surfaces of interest. Biological contamination
in clean rooms, such as those used for aseptic filling, has been discussed in a
monograph by the IES (Institute of Environmental Sciences, 1993).
Autoclaved
pharmaceutical residues can be particularly hard to clean due to their
proteinaceous nature, probably requiring an acidic cleaner, but only somewhat
less hard are product residues, such as lipids, sugars and salts (Parenteral
Drug Association (PDA), 1996), requiring different solvents. Solvents and
cleaning compounds generally are relatively easy to remove, and product
residues may or may not be.
Validation
Validation is proof or demonstration that something is what it claims to be. Carlberg (1995) defined it as "Full, detailed documentation that all processes and procedures are functioning in the manner they were designed for. Required by the FDA." Byers (in Carleton and Agalloco, 1985) gives several definitions, including, "A scientifically designed program to prove that a process consistently does what it is designed (intended) to do." The FDA (U.S. Food and Drug Administration, 1993) stated, "In the end, the test of any validation process is whether scientific data shows that the system consistently does as expected and produces a result that consistently meets predetermined specifications." The essence of all these definitions seems to be: documented, scientific proof of consistent successful performance.
Validation is proof or demonstration that something is what it claims to be. Carlberg (1995) defined it as "Full, detailed documentation that all processes and procedures are functioning in the manner they were designed for. Required by the FDA." Byers (in Carleton and Agalloco, 1985) gives several definitions, including, "A scientifically designed program to prove that a process consistently does what it is designed (intended) to do." The FDA (U.S. Food and Drug Administration, 1993) stated, "In the end, the test of any validation process is whether scientific data shows that the system consistently does as expected and produces a result that consistently meets predetermined specifications." The essence of all these definitions seems to be: documented, scientific proof of consistent successful performance.
The
FDA Guide to Inspections (U.S. Food and Drug Administration, 1993),
"intended to cover equipment cleaning for chemical residues only,"
includes:
- "FDA expects firms to have written procedures (SOPs) detailing the cleaning processes...."
- "FDA expects firms to have written general procedures on how cleaning processes will be validated."
- These procedures will "address who is responsible for performing and approving the validation study, the acceptance criteria, and when revalidation will be required."
- "FDA expects firms to conduct the validation studies in accordance with the protocols and to document the results of studies."
- Besides assuring chemical cleanliness, "the microbiological aspects of equipment cleaning should be considered. This consists largely of preventive measures...."
- Sterilization is not part of the scope of the document, except that reduction of the biological material will assist in successful sterilization and minimization of pyrogens.
- "Determine the specificity and sensitivity of the analytical method used to detect residuals."
- The sampling and analysis combination should be challenged to determine what fraction of the target material is actually sampled and then detected.
- " Direct sampling (e.g., with swabs) is "most desirable," although rinse sampling may be satisfactory.
References
cited in this FDA document include Harder (1984), Smith (1992), and Fourman and
Mullen (1993).
Recently,
Gold (1996) presented an extended discussion of validation, stating,
"Validation is necessary since testing of a product to assess its quality
is not enough." Rare failures can escape testing but might be prevented by
improved procedures. Table 1 shows the probability (binomial distribution) that
a sample of size "n" will find no defectives, when the true fraction
of the population is "p," which probability is (1-p) to the nth
power. The table shows, for example, that if the true fraction defective is 1%,
samples of size n=100 will find no defectives in 36.6% of the cases.
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