Cleaning validation-volume-iii

Institute of Validation Technology4
E D I T O R I A L A D V I S O R Y B O A R D
J O U R N A L M I S S I O N
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Gamal Amer, Ph.D.
Validation and Process
Associates, Inc.
Louis A. Angelucci, III
Foster Wheeler Corporation
George N. Brower
Analex Corporation
Kenneth G. Chapman
Drumbeat Dimensions, Inc.
Dennis Christensen
Consultant
Robert C. Coleman
US Food & Drug Administration
Shahid Dara
Independent Consultant
David R. Dills
Medtronic Xomed
Michael Ferrante
Catalytica Pharmaceuticals
Patricia Stewart
Flaherty
Bayer Corporation
Roberta D. Goode
Consultant
CYNTHIA GREEN
Northwest Regulatory Support
Daniel Harpaz, Ph.D.
PCI, Pharmachem International
William E. Hall, Ph.D.
Hall & Associates
Eldon Henson
Boehringer Ingelheim
Animal Health
JAY H. KING
LifeScan, a Johnson & Johnson Company
JOHN G. LANESE, Ph.D.
The Lanese Group, Inc.
Barbara Mullendore
AstraZeneca
ROBERT A. NASH, Ph.D.
St. John’s University
Charlie Neal, Jr.
BE&K
TOD E. RANSDELL
Bio-Rad Laboratories
MELVIN R. SMITH
Independent Consultant
ROBERT W. STOTZ, Ph.D.
Validation Technologies, Corporation
ERIC D. VEIT
Johnson & Johnson
David W. Vincent
Validation Technologies, Inc.
Special Edition n Cleaning Validation
III
Editor and Publisher
Glenn Melvin
Vice President
Terri Kulesa
Production Director
Edward Eick
Associate Publisher
Brandon Melvin
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ISSN 1079-6630

Equipment Cleaning Validation: Microbial Control Issues . . . . . . . . . . . . . . . . . . . . . . . 6
by Destin A. LeBlanc, M.A.
Cleaning Validation: Maximum Allowable Residue: Question and Answer . . . . . . . 13
by William E. Hall, Ph.D.
Development of Total Organic Carbon (TOC) Analysis
for Detergent Residue Verification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
by James G. Jin and Cheryl Woodward
Total Organic Carbon Analysis for Cleaning Validation
in Pharmaceutical Manufacturing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
by Karen A. Clark
Detergent Selection – A First Critical Step in Developing
a Validated Cleaning Program . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
by Mark Altier
Analysis Cleaning Validation Samples: What Method? . . . . . . . . . . . . . . . . . . . . . . . . . . 35
by Herbert J. Kaiser, Ph.D., Maria Minowitz, M.L.S.
Control and Monitoring of Bioburden in
Biotech/Pharmaceutical Cleanrooms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46
by Raj Jaisinghani, Greg Smith and Gerald Macedo
A Cleaning Validation Program for the ELIFA System . . . . . . . . . . . . . . . . . . . . . . . . . . . 56
by LeeAnne Macaulay, Jeff Morier, Patti Hosler and Danuta Kierek-Jaszczuk, Ph.D.
A Cleaning Validation Master Plan for Oral Solid Dose
Pharmaceutical Manufacturing Equipment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61
by Julie A. Thomas
Proposed Validation standard — VS-3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71
BONUSBONUS
Special Edition: Cleaning Validation III 5
C O N T E N T S
T A B L E O F
Special Edition n Cleaning Validation III

T
he PDA spring conference
was held in Las Vegas,
Nevada in March 20, 2001.
The conference showcased clean
ing validation, residue limits, bio
burden, microbial limits, and sani
tization. This paper is based on a
presentation at that conference.
The initial focus of regulatory
documents relating to cleaning
validation for process equipment
in pharmaceutical manufacturing
involved measuring residues of the
drug active and the cleaning agent.
For example, the introduction to
the Food and Drug Administration
(FDA) guidance document on clean
ing validation1
states: “This guide is
intended to cover equipment clean
ing for chemical residues only.”
While admitting that microbial res
idues are beyond the scope of the
guideline, that guidance document
further states, “microbiological aspects of equip
ment cleaning should be considered,” particularly
with reference to preventive measures so that micro
bial proliferation does not occur during storage. The
European PIC/S document,2
that was issued several
years later, does explicitly mention microbial resi
dues. In Section 6.2.1, contaminants to be removed
include “the previous products, residues of cleaning
agents as well as the control of potential microbial con
taminants.” However, Section 6.7 of
thisdocumentthatcovers“Microbio
logical Aspects” focuses exclusively
on the same issue discussed in the
FDA guidance document, namely
the issue of preventing microbial pro
liferation during storage.
As a practical matter, microbial
residues on equipment surfaces are
part of the contaminants that should
be reduced to an acceptable level;
that acceptable level being what is
safe for the manufacture of the sub
sequently manufactured product.
Unfortunately, very little has been
written on what is a safe level for
microorganisms following cleaning
and/or sanitation.3,4
Part of the reason
for this is that microbial residues are
significantly different from chemi
cal residues. Chemical residues are
“inert” in the sense that it is easy to
calculate (especially using scenarios
of uniform contamination in the subsequently manu
factured product) the potential levels and effects of
those chemical residues in the subsequently manu
factured product should they be transferred to that
subsequently manufactured product. With microbial
residues left after the cleaning process, the situation
is somewhat different. Because microorganisms are
living organisms, those left as residues on equipment
may change in number after the cleaning process, but
Equipment Cleaning Validation:
Microbial Control Issues
By Destin A. LeBlanc, M.A.
Cleaning Validation Technologies
v
}…it is
becoming more
common for
regulatory
authorities
to cite
manufacturers
for deficiencies
related to
microbial
control in
cleaning
validation
programs.~

Special Edition: Cleaning Validation III
Destin A. LeBlanc, M.A.
before the manufacture of the subsequently manu
factured product. Those microbes transferred to the
subsequently manufactured product may also change
in number after they are incorporated into the subse
quently manufactured product in the manufacturing
step. This change may be a significant reduction in
bioburden, either due to drying of the equipment or
due to a preservative in the finished drug product,
for example. This change may also involve rapid
proliferation, either due to suitable growth conditions
in wet equipment during storage, or due to suitable
growth conditions in the finished drug product. Or,
they may result in no significant change in microbial
level, because the bioburden was due to bacterial
spores (that will survive readily in
dried equipment), or because the
subsequently manufactured product
was a dry product (with low water
activity). Therefore, knowing the
levels of microorganisms left on the
equipment following cleaning does
not necessarily give one the full
story of the potential hazards of those
microbialresidues.Additionalinfor
mation is required to assess those
potential hazards.
Why has microbial evaluation
during cleaning of process equip
ment been a little discussed topic?
Part of the reason is that it is not a
significant problem in process man
ufacturing. Yes, it could conceivably be a problem if
cleaning and storage were inadequate. However, for
the most part, cleaning and storage of process equip
ment, in so far as it applies to microbial residues,
probably is done relatively well in most pharmaceu
tical manufacturing facilities. On the other hand, it is
becoming more common for regulatory authorities to
cite manufacturers for deficiencies related to micro
bial control in cleaning validation programs. One
reason for this seeming anomaly is that while firms
are adequately controlling microbial contamination of
process equipment, there may be little documentation
to support this. This lack of documentation includes
any measurement of microbial residues during the
cleaning validation and/or during routine monitoring.
Some companies will measure the change in micro
bial levels on equipment surfaces during storage of
the cleaned equipment. However, many times this
does not include any assessment as to the effect of
that unchanged bioburden level on the subsequently
manufactured product.
This paper will address issues covering approaches
to control of microorganisms in process equipment,
setting of acceptance limits, sampling techniques, and
approaches to providing acceptable documentation.
Microbial Control Measures
Control measures to reduce the bioburden on
cleaned process equipment include control of bio
burden of raw materials, the cleaning process itself,
a separate sanitizing step, and drying of the equip
ment following cleaning. Bioburden of raw materials
includes the active, excipients, water, and any process
ing aids. In many cases, the manufacturer may have
little control over the bioburden of raw materials other
than to accept a specification by the raw material sup
plier. The most critical raw materials probably will be
natural products, in which there may be considerable
variation in the levels and types of microorganisms.
A solid monitoring program to control incoming bio
burden of raw material is necessary. If there could be
significant variation in bioburden, then that should
be addressed in the cleaning validation Performance
Qualification (PQ) trials. At least one PQ trial should
utilize the worst-case incoming bioburden of raw
materials to demonstrate adequate cleaning and micro
bial control under those conditions.
7
}Some companies will measure the
change in microbial levels on
equipment surfaces during storage
of the cleaned equipment. However,
many times this does not include any
assessment as to the effect
of that unchanged bioburden
level on the subsequently
manufactured product.~

Institute of Validation Technology
A second means of microbial control is the cleaning
process itself. The conditions of aqueous cleaning
are often hostile to microbial survival. These conditions
include high temperature (commonly 60-80ºC), pH
extremes (>11 and <4), and the presence of oxidizers
(such as sodium hypochlorite in biotechnology manu
facture). In addition, the presence of surfactants in the
cleaning solution can assist in providing good physical
removal of microbes (without necessarily killing them).
Good cleaning is also beneficial to microbial control in
that chemical residues left behind can provide a physi
cal “microbial trap” to allow microorganisms to survive
even in the presence of chemical sanitizers. Those
chemical residues left behind might also serve as a
nutrient source that allows microbes to proliferate dur
ing improper storage. Based on the author’s experience,
in most cases, effective control of microorganisms in
pharmaceutical process equipment can be achieved
with the use of an effective cleaning process, without
the need for a separate chemical sanitizing step.
In some cases, a separate sanitizing step may be
necessary. This may include sanitation by steam or by
chemical sanitizers. Suitable chemical sanitizers for
process equipment include sodium hypochlorite (chlo
rine bleach), quaternary ammonium compounds, alco
hol (ethyl or isopropyl), hydrogen peroxide, and per
acetic acid. It should be noted that, with the exception
of alcohol and hydrogen peroxide, additional rinses
would be necessary to remove any chemical residues
of the sanitizer from the equipment. Those chemical
residues may also have to be evaluated as residues to
be measured in the cleaning validation protocol. For
such chemical treatments, it is not an expectation that
the equipment be sterile. Unless the final rinse is with
sterile water, microorganisms will be reintroduced
into the equipment from the use of Water-for-Injection
(WFI) or purified water as the final rinse.
Some companies will use an alternative to sanitizing
immediately after cleaning. This usually involves sani
tizing after storage and immediately before use. This
may be used in situations where it is difficult to control
microbial recontamination or proliferation during stor
age. It should be noted that control of storage condi
tions, if possible, is preferable. The practice of relying
solely on a separate sanitizing step immediately before
manufacture should be discouraged. If this is practiced,
then the sanitization step should be shown to be effec
tive in reducing bioburden under the worst-case storage
conditions (“initial” bioburden, time, temperature, and
humidity). Needless to say, if the chemical sanitizing
step is performed immediately prior to manufacture of
the subsequently manufactured product, then removal
of the sanitizer chemical residues to an acceptable level
should also be demonstrated.
A fourth consideration for control of microor
ganisms is drying the process equipment surfaces
following the final rinse. Drying the surfaces will
further reduce the levels of vegetative organisms on
the surface. In addition, drying will assist in prevent
ing microbial proliferation during storage. Drying
can be achieved by heated air, heated nitrogen, or
by rinsing with alcohol. In all cases, the process can
be assisted by application of a vacuum (to speed the
evaporation of the water or, in the case of an alcohol
rinse, of the alcohol itself).
Limits for Microbes
As mentioned earlier, it is possible to reasonably
predict levels of chemical residues in subsequently
manufactured products based on the levels present on
equipment surfaces.5,6
With microorganisms, it is pos
sible to measure levels on equipment surfaces; how
ever, the effect of those residues will depend on what
happens to those microorganisms once they come in
contact with the subsequently manufactured product.
Areas that may have to be evaluated include the species
(including the so-called “objectionable” organisms),
type of organism (vegetative bacteria versus bacterial
spore, for example), the presence of preservatives in that
subsequently manufactured product, the water activity
of the subsequently manufactured product, as well as
any subsequent sterilization process performed on that
product. As a general rule, if the water activity is less
than 0.6, then it can be expected that microorganisms
will not proliferate (although they may continue to sur
vive without reproducing).7
Water activity is a physical-
chemical measurement that expresses the water vapor
pressure above the test sample as a fraction of the water
vapor pressure of pure water at the same temperature
as the test sample. For aqueous products with a neutral
pH, microbial proliferation can generally be expected
unless there is a preservative in the product. If there
is a possibility of microbial proliferation because the
product is unpreserved and neutral, then that should be
addressed in setting limits.
8

Three methods to set microbial limits will be
addressed. The first (Case I) involve limits where the
subsequent product does not allow microbial prolif
eration and is not subject to any further sterilization
process. The second (Case II) involves subsequently
manufactured products that are terminally sterilized.
The third (Case III) involves subsequently manufac
tured products that are processed aseptically.
Case I Limits
If the subsequently manufactured product does not
allow microbial proliferation, then the determination
of acceptable microbial limits in the cleaned equip
ment can be calculated using the same principles used
for chemical residues with one important exception.
This process involves first determining the accep
tance limit in the subsequently manufactured product.
This limit is typically given in Colony Forming Units
(CFU) per gram of product. Once this is determined,
then the limit per surface area of equipment (assum
ing uniform contamination) can be calculated based
on the batch size of the subsequently manufactured
product and the equipment surface area.
How is the limit in the subsequently manufactured
product determined? For chemical residues, it is based
on dosing information for actives or toxicity information
for cleaning agents. Such concepts cannot be directly
applied to microbes. Fortunately, there are two good
sources of information relating to levels of microorgan
isms in products. One is the manufacturer’s own Quality
Control (QC) specifications for the product, that may
include a limit for bioburden in the product. A second
source is information given in the proposed United
States Pharmacopeia (USP) <1111> relating to
“Microbial Attributes of Nonsterile Pharmacopeial
Articles.”8
Examples of those limits are given below:
Solid oral: ≤1000 CFU/g
Liquid oral; ≤100 CFU/g
Topicals: ≤100 CFU/g
Note: Although these limits were discussed and
proposed in the Pharmacopeial Forum, these spe
cific recommendations were not adopted officially
as part of the 24th
edition of the USP.
Unfortunately, this is where the one exception to
the conventional treatment arises. When one looks at
the bioburden in a finished drug product, the equip
ment surfaces are not the only source of bioburden.
One must also consider the raw materials themselves,
as well as the primary packaging, as potential sources
of microorganisms. The best way to deal with this
issue is to develop information on the bioburden of the
raw materials and the primary packaging, and factor
these into the limits calculation. For example, if one
were dealing with an oral liquid, one might calculate
the contribution from the raw materials (assuming
the upper limit bioburden for each raw material) as a
maximum of 27 CFU/g. At the same time the contribu
tion from the primary packaging is determined to be 3
CFU/g. Therefore, the amount allowed from equipment
surfaces would be 70 CFU/g (100 minus 27 minus 3).
An additional safety factor should be used to account
for the significant variability in microbiological enu
meration. An appropriate factor may be on the order
of 5. Therefore, in this case, the limit (in CFU/g) that
would be allowed solely due to the cleaned equipment
surfaces would be 14 CFU/g (obtained by dividing 70
by 5). Higher safety factors also could be considered.
These numbers are given for illustration purposes only.
It should be realized that the contribution percentage
allowed from cleaned equipment would vary depend
ing on the contributions from the raw materials and the
primary packaging.
Once the limit in the subsequently manufactured
product allowed from the cleaned equipment sur
faces is determined, the next step is to determine the
limit per surface area (CFU/cm2
). This is calculated
exactly as it would be for chemical residues:
Limit per surface area = LSP x MBS
SA
where
LSP = Limit in the subsequent product
MBS = Minimum batch size
SA = Product contact surface area
In the example above, if the batch size is 200 kg
and the product contact surface area is 260,000 cm2
,
then the microbial surface limit of the cleaned equip
ment is:
Limit per surface area = (70 CFU/g)(200,000g) = 54 CFU/ cm2
(260,000 cm2
)
9

If sampling were done with a typical contact plate
of 25 cm2
, this would correspond to a limit of over
1300 CFU per contact plate. Since it is reasonable
to count a maximum of only 250 CFU on a typical
contact plate, this would clearly be in the TNTC (too
numerous to count) category. Needless to say, this will
vary with the limit in the subsequently manufactured
product, the portion allowed from cleaned surfaces, the
safety factor used, batch size, and the shared surface
area. However, under most reasonable scenarios, the
calculated limit due to microorganisms on the cleaned
equipment surfaces will be significantly above what
should be (and can be) achieved by proper cleaning.
As a general rule, a good cleaning process should
produce surfaces that contain no more than 25 CFU
per contact plate (1 CFU/cm2
). When failures occur,
generally they will be gross failures, with counts gen
erally above 100 CFU per-plate.
Case II Limits
This involves setting limits for cleaned equipment
when the product subsequently manufactured in that
equipment is to be sterilized. In this case, the microbial
limit in the subsequently manufactured product can be
established based on the assumed bioburden of that
product at the time of sterilization. In other words, any
validated sterilization process depends on an assumed
bioburden of the item being sterilized. That assumed
bioburden then becomes the limit in the subsequently
manufactured product. Once that limit in the subse
quently manufactured product is established, then the
calculations are the same as for Case I – a certain por
tion of that total limit is allowed from cleaned equip
ment surfaces, a safety factor is applied, and then the
limit per surface area is calculated using the minimum
subsequent product batch size and the product contact
surface area. It is significant that this issue is actually
addressed in the FDA’s cleaning validation guidance
document; that states:
“…it is important to note that control of bio
burden through adequate cleaning and storage of
equipment is important to ensure that subsequent
sterilization or sanitization procedures achieve
the necessary assurance of sterility.”9
Case III Limits
This third case involves setting limits on equip
ment surfaces where the subsequently manufactured
product is aseptically produced. This case is slightly
different from Case II in that it is the equipment itself,
and not the product, which is subsequently sterilized.
This case is relatively straightforward, because the
microbial limits on the surfaces of cleaned equipment
are established based on the assumed bioburden of the
equipment surfaces for sterilization validation of that
equipment. No information on batch sizes or surface
areas is necessary. The assumed bioburden for the
sterilization validation can be used directly for limit
purposes. The only adjustment may be the incorpora
tion of a safety factor (to accommodate normal varia
tion in microbiological enumeration).
Measurement Techniques
Conventional tools used for microbial enumeration
from surfaces can be used. These include rinse water
sampling (usually with membrane filtration), swab
bing (with desorption of the swab into a sterile solu
tion and then a pour plate count), and use of a contact
plate. The choice of recovery medium and incubation
conditions is usually dictated by the expected organ
isms. As a general rule, the initial focus is on aerobic
bacteria. However, if anaerobic bacteria or molds/
yeasts are suspected problems, these should be also
evaluated.
One issue that does not translate directly from
chemical residue measurements is the idea of deter
mining percent recovery using the sampling method.
In the measurement of chemical residues, the target
residue is spiked onto a model surface and the quan
titative percent recovery is determined. The amount
recovered as a percent of the amount spiked is consid
ered the sampling method percent recovery. Percent
recoveries in chemical sampling measurement are
generally above 50 percent. This percent recovery is
then used to convert an analyzed sample value; for
example, if a chemical residue measured by a swab
bing technique gives 0.6 µg of residue, then with a 50
percent recovery, this actually represents the possibil
ity of 1.2 µg being on that surface. This concept can
not be applied directly to microbiological sampling.
The reason for this is partly the inherent variability in
microbiological testing. If one measured 10 CFU in
one test and 5 CFU in a duplicate test (a 50 percent
difference), one would be hard pressed to say that
10

those numbers are significantly different. In addition,
how would one actually measure the percent recovery
in a microbiological test? If a model surface is spiked
with a specific number of a certain bacterium, and
then that surface is allowed to dry and is sampled,
just the process of drying might cause a low recovery
of bacteria (due to the dying of vegetative bacteria by
drying). In addition, what species of bacteria would
be used for the recovery study?
It is recognized that microbiological sampling
methods may understate the number of microbes on
a surface (indeed the concept of a CFU, that may
contain any number of bacteria, also clouds the issue).
There are two ways to view such an issue. One is to
make it clear that whatever variation exists in measur
ing microorganisms on surfaces is probably equally an
issue when one sets limits based on product limits or
sterilization bioburden limits. Therefore, the variabili
ty issue becomes a “wash.” The other perspective is to
account for such variation by choosing extremely high
safety factors. In the calculation example for Case I,
a factor of 5 was used as a safety factor. Even if that
safety factor were increased to 10 or 20, the calculated
acceptance limits would have still been extremely
high, and still beyond what one should achieve with a
well-designed cleaning program.
Documentation Strategies
How these issues will be addressed will depend on
the stage of the cleaning process development. For a
new process being designed, the best strategy is to pre
pare a calculation of microbial limits, and then design
the cleaning process to meet those acceptance criteria.
Included in that evaluation should be any change in
bioburden (in particular, any increase or proliferation)
on storage of the equipment. The microbial acceptance
limits should be included in the validation protocol,
and measured as part of the three PQ trials. One
should also include the absence of “objectionable”
organisms as part of the acceptance criteria.
To deal with processes for which cleaning valida
tion has already been completed, but for which no
microbial evaluation has been done, there are two
strategies available. The objective of each is to devel
op documentation that the cleaning process consis
tently provides equipment surfaces with acceptable
bioburden. One option is to perform a cleaning
validation PQ, measuring only bioburden on sur
faces for comparison to calculated
acceptance limits. The other option
is to initiate a routine microbiologi
cal monitoring program as part of
the monitoring of cleaning. This
may involve something as simple
as monitoring the bioburden in the
final rinse water to demonstrate con
sistency. This data, combined with
product QC data on bioburden, may
satisfy the need for adequate docu
mentation.
One should also consider one’s motivation for
wanting to obtain assurance that the bioburden is
acceptably low after cleaning. If the impetus for action
is due to lack of data, one should resist the impulse to
immediately add a sanitizer into the cleaning program.
The focus should be on developing data to demonstrate
the sufficiency of the current cleaning process. Adding
a separate sanitizing step only complicates matters by
adding additional residue concerns. If the impetus for
action is due to observed high microbial counts on
equipment surfaces or (more likely) in manufactured
product, then it is important to determine by careful
investigation whether that unacceptable contamination
is due to issues with the cleaning process, with stor
age, or to both. In such a case, a separate sanitizing
step should only be added if the data fully support it.
Conclusion
Bioburden on cleaned equipment is an impor
tant concern in the cleaning process. Fortunately,
most aqueous cleaning processes, properly designed,
should provide low and acceptable bioburden levels
onequipmentsurfacesfollowingthecleaningprocess.
11
}One issue that does not translate
directly from chemical residue
measurements is the idea of
determining percent recovery
using the sampling method.~

Proper drying and storage should provide assurance
that microbial proliferation does not occur before
the manufacture of the subsequently manufactured
product in that equipment. Any scientifically justi
fied determination of acceptable bioburden levels,
particularly for non-sterile products, is generally far
higher than what should be achieved in conventional
practice. This is becoming more of a regulatory and
compliance issue, not because microbial contami
nation is a widespread problem, but rather because
pharmaceutical manufacturers may lack appropriate
documentation to support their practices. This can
easily be remedied by a separate validation protocol
to address microbial issues, or by routine monitoring
to demonstrate consistency. o
About the Author
Destin A. LeBlanc, M.A., is with Cleaning Validation
Technologies, providing consulting in the area of
pharmaceutical cleaning validation. He has 25
years experience with cleaning and microbial con-
trol technologies. He is a graduate of the University
of Michigan and the University of Iowa. He can be
reached by phone at 210-481-7865, and by e-mail
at destin@cleaningvalidation.com.
References
1. FDA. “Guide to Inspections of Validation of Cleaning Pro
cesses.” 1993.
2. Pharmaceutical Inspection Cooperation Scheme. Recommen
dations on Cleaning Validation. Document PR 1/99-2. Geneva,
Switzerland. April 1, 2000.
3. A.M. Cundell. Microbial Monitoring. Presented at the 4th IIR
Cleaning Validation Conference, October 20-22, 1997. (http://
microbiol.org/files/PMFList/clean.ppt, accessed May 29, 2001).
4. S.E. Docherty. “Establishing Microbial Cleaning Limits for Non-
sterile Manufacturing Equipment.” Pharmaceutical Engineering.
Vol. 19 No. 3. May/June 1999. Pp. 36-40.
5. G.L. Fourmen and M.V. Mullen. “Determining Cleaning
Validation Acceptance Limits for Pharmaceutical Manufacturing
Operations.” Pharmaceutical Technology. Vol. 17 No. 4. 1993.
Pp. 54-60.
6. D.A. LeBlanc. “Establishing Scientifically Justified Acceptance
Criteria of Finished Drug Products.” Pharmaceutical Technology.
Vol. 19 No. 5. October 1998. Pp. 136-148.
7. R.R. Friedel. “The Application of Water Activity Measurements
to Microbiological Attributes Testing of Raw Materials Used
in the Manufacture of Nonsterile Pharmaceutical Products.”
Pharmacopoeial Forum. Vol. 25 No. 5. September-October
1999. pp. 8974-8981.
8. 1111 Microbial Attributes of Nonsterile Pharmacopoeial
Articles (proposed). Pharmacopoeial Forum. Vol. 25 No. 2.
March-April 1999. Pp. 77857791.
9. FDA. “Guide to Inspections of Validation of Cleaning Pro
cesses.” 1993.
12
CFU: Colony Forming Units
FDA: Food and Drug Administration
PQ: Performance Qualification
QC: Quality Control
USP: United States Pharmacopeia
WFI: Water-For-Injection
Article Acronym Listing

W
e are involved in the pro
duction of soft gelatin
capsules and tablets in
our newly built facility. Our prod
ucts consist of at least 17 minerals
and multivitamins in a single pro
duct, while other products consist of
the same ingredients having some
quantity (in MG) varying with the
previous one. In some products,
some vitamins are not present. I want
to know how to conduct a cleaning
validation study of each product.
Again, I want to know which ingre
dients I have to check after cleaning
of the equipment to determine the
residues?
• Whatwillthelimitbeforthemicro
bial contamination for the cleaning
validation studies, and what will be
the rationale for the same?
• If I’m using some cleaning agent,
then what rationale is used for
keeping the limit the same?
A:Thank you for your question. It is a very good
one because it represents cleaning from the
point of view of a manufacturer of vitamins and min
erals, which in some countries, are considered drugs,
and in other countries, are considered as “nutraceuti
cals,” an important and emerging part of our business.
The first specific question you asked related to
how to conduct a cleaning validation for each prod
uct, and how to select which ingredient to check
after cleaning to verify that the cleaning is adequate.
The choice of which ingredient in
a multi-ingredient product should
serve as the focus of the cleaning
validation is often a difficult one for
vitamin and mineral products. For
classical pharmaceutical products,
the choice is usually based on choos
ing the most potent ingredient, or the
least water soluble ingredient, or a
combination of these two factors.
For vitamins and minerals the choice
may be more difficult because of
the many ingredients present in the
formulation and the relatively small
amounts present. Coupled with these
difficulties is often the difficulty in
assaying the very small amounts of
active residues that might be pres
ent after cleaning. My suggestion
would be to identify an ingredient for
which there is a good sensitive assay
available. For example, if one of the
ingredients happens to show good
detectable levels of fluorescence
(e.g., riboflavin, folic acid, and certain B vitamins
show good fluorescence) in water, then this material
could be selected as the “marker” material, and could
serve as the ingredient to focus on during the analysis
of the rinse samples. In the case of vitamins and min
erals, it may be necessary, and even highly desirable,
to take this approach because of the extremely low
levels of residues present after cleaning. It may also
be possible to examine equipment in a dark room with
the use of an ultraviolet light to identify areas of equip
ment that are not cleaned sufficiently (an enhanced
visual examination), again utilizing the known fluo
Cleaning Validation:
Maximum Allowable Residue
Question and Answer
}…sometimes
the many
possible
combinations
of products and
equipment would
result in so many
studies that the
company would
never be able to
complete them
during a
reasonable
period of time.~

William E. Hall, Ph.D.
rescent behavior of certain vitamins. A brief study will
need to be carried out to determine if this approach is
appropriate and adequate for your particular situation.
I would suggest that you not try to conduct cleaning
validation for every product. The reason I say that
is because sometimes the many possible combina
tions of products and equipment would result in so
many studies that the company would never be able
to complete them during a reasonable period of time.
If, for example, you have 50 products, and each could
be run on ten (10) different pieces of equipment, then
you would need 500 studies to cover all the possible
combinations and permutations. That is simply too
much of a resource and cost issue for the average
company to face. It would be much better to divide
your products into groups or families, and choose one
or two representatives from each group to conduct full
cleaning validation. The assumption is that you can
pick some “worst-case,” most difficult to clean, potent
products from each group. The first step is to divide
the products into groups. I don’t know the names and
ingredients of the products your company manufactur
ers; however, you did mention that some products are
vitamin products and others are mineral products. So I
think there would be two major groups – vitamins and
minerals. Then each of these groups might be further
divided, if necessary. For example, in the vitamin cat
egory you may have some products that contain water
soluble vitamins, and some that contain fat soluble
vitamins. So now we have three (3) major groups
(water soluble vitamins, fat soluble vitamins, and
mineral products). So you begin to see our approach.
It might be that if you have vastly different types of
mineral products you might want to also further divide
that group into smaller groups. In any event, you want
to have probably four (4) to ten (10) products in each
group, and then pick a worst-case representative from
each group. So by choosing this “grouping approach,”
you have reduced the work from a very large resource
requirement to a doable or achievable project.
The choice of the worst-case representative should
be based on a combination of aqueous solubility and
potency. The potency can be determined for some
products by determining the amount present in the
product from the label or package insert. Sometimes
this may be a little confusing for vitamin products
because the amounts are listed in units instead of
quantitative amounts, such as milligrams. In these
cases, I would suggest that you refer to the Internet,
and conduct a search on the toxicity or potency of these
materials. You may be surprised to find that a vita
min, such as folic acid, is quite potent in terms of its
medical effect and dosage.
The limits for these products can be calculated
by allowing a certain small fraction of vitamins or
minerals to carry over to each dose of the following
product. Again, you will need basic information, such
as the medical dosage of the initial product, the batch
size and dosage of the next or subsequently manufac
tured product. In terms of the safety factor, i.e., the
factor that is used to reduce the allowable dosage, I
suggest that you use a factor of 1/100th
for vitamin
and mineral products. A factor of 1/1000th
is often
used for pharmaceuticals, but I feel a more generous
factor of 1/100th
is appropriate for vitamin and min
eral products. You could refer to some of the articles
published in the Journal of Validation Technology for
the details of how to calculate specific limits.
Your last question related to what rationale should
be used for the cleaning agent itself. The basic
requirement is that you be able to provide data that
demonstrates that the cleaning agent itself is removed
during the cleaning process, usually by the final rinse.
You will need to go through the same rationale for
the product residue limits, i.e., establish a scientific
basis or justification that shows that the most potent
ingredient in the cleaning agent is reduced to a medi
cally insignificant level. It is beyond the scope of this
answer to go into the mathematical details of how to
calculate this data, but again the details can be found
in the various articles published in the Journal of
Validation Technology. You will need to know about
the ingredients in your cleaning agent, as they are
typically multi-ingredient formulations, just like our
pharmaceutical products, and you will need to get that
information from your supplier of cleaning agents.
The good news is that if you use the same cleaning
agent and cleaning procedure for many products, then
you only have to do a single cleaning validation study
(three runs) for the cleaning agent. o
This answer was provided by an Editorial Advisory
Board Member, William E. Hall, Ph.D. Dr. Hall be
reached by phone at 910-458-5068, or by fax at 910-
458-1087, and by e-mail at cleandoct@aol.com.
14

T
he 1993 FDA Guideline for
cleaning validation states
that the removal of deter
gent residues should be evaluated
and there should be no or very low
detergent levels left after cleaning.1
Currently,thepharmaceuticalindus
try employs varieties of detergents
for cleaning and different cleaning
validation programs. Many com
panies have not included detergent
residue evaluation as part of their
cleaning validation programs main
ly due to unavailability of effective
methodologies or lack of awareness
of the requirement by management.
In the late 1970s, Total Organic
Carbon (TOC) analysis had been
used for monitoring water quality in
pharmaceuticals and environmental
controls. More recently, the biotech
nology and pharmaceutical industry
has become increasingly interested
in the use of TOC as an analytical
tool in cleaning validation programs. TOC analy
sis has been used as an analytical tool for cleaning
validation in the biotechnology industry for years.2,3
Westman and Karlson recently conducted a compari
son study for different analytical methods – visual
detection of foam, pH, conductivity measurements,
and TOC for detergent residue evaluation. They
concluded that the visual detection
of foam was the best method for the
detergents they tested.4
The method
of visual detection of foam is only
effective for foaming detergents,
but is invalid for low foaming deter
gents. From a user’s point of view,
this paper documents that TOC is an
effective and quantitative method
for detergent residue verification.
Total Organic Carbon
Methodology
TOC is a non-specific method for
the compound analyzed. However,
TOC analysis is sensitive to very
low levels of 0.002-0.8 ppm carbon,
depending on whether the sample is
a water sample or a swab sample.
Currently, two major oxidation tech
nologies dominate the TOC market:
combustion and Ultra Violet (UV)/
persulfate. There has been debate
about which technique is better suited for TOC testing
since the late 1980s. The major differences for each
technique5
are described in Figure 1, and give the user
appropriate information to make an informed deci
sion as to which technique better serves their needs.
The best TOC oxidation technology is the one
that meets the application and analytical needs of the
Development of Total Organic Carbon
(TOC) Analysis for Detergent
Residue Verification
By James G. Jin
and Cheryl Woodward
Boehringer Ingelheim Pharmaceuticals, Inc.
v
}…the
biotechnology and
pharmaceuti-
cal industry has
become
increasingly
interested in
the use of
TOC [Total
Organic Carbon]
as an analytical
tool in cleaning
validation
programs.~

James G. Jin
user’s situation. The UV/Persulfate method meets
precision and accuracy requirements for low-level
calibration check standards such as 0.5 ppm carbon
in detergent residue evaluation. However, if captur
ing the particulate organic matter in the TOC value
is important, then combustion would be the better
oxidation technology. The instrument we chose is a
Tekmar-Dohrmann Phoenix 8000 with the UV/Per
sulfate oxidation technique.
Chemistry of Oxidation and Total Organic
Carbon Analysis of UV/Persulfate
Wet chemistry oxidation of carbon compounds
utilizes two chemical reactions to complete the
analysis. A 21 percent solution of phosphoric acid
is utilized in converting inorganic carbon species.
Acidification of the sample allows for attack on inor
ganic species such as carbonates and bicarbonates
to convert them to carbon dioxide. This, along with
any dissolved carbon dioxide in the sample is then
sparged out, and either exhausted to vent or routed
to the Non-Dispersive Infrared detection (NDIR) for
quantification when analyzing for Inorganic Carbon
(IC) or TOC by difference (TC-IC).
H+
+ CO3
-2
→ H2
O + CO2
Persulfate is used to do the rest of the oxidation
chemistry that is required for analysis. Sodium persul
fate, at a concentration of 10 percent, and phosphoric
acid, five percent are added to the UV chamber for
analysis. The persulfate species in the presence of
UV light breaks down at a weak oxygen-oxygen
bond yielding two radicals per molecule. These radi
cals start chain reactions that ultimately lead to the
degradation of all carbon species to carbon dioxide,
water, and other oxides of heteroelements. The UV
light alone induces breakdown of many carbon spe
cies with the persulfate providing additional help to
attack compounds difficult to oxidize. The radical
reactions are aggressive and indiscriminate in their
attack.
S2
O8
-2
→ SO4
-1
+ R → H2
O + CO2
The NDIR is constructed in such a way as to be
sensitive and selective for carbon dioxide present
in the gas flow. An infrared beam from the source
is passed through a chopper and down the sample
chamber to a dual chamber detector. Each chamber is
filled with carbon dioxide and is separated by a thin
membrane. Varying intensity of the light hitting the
cell causes fluctuation in temperature and thus the
pressure of the gas inside the detector. This causes
the membrane to deflect, which is ultimately read as
a millivolt output signal from the detector.
Detergent Evaluation
Three detergents (CIP-100, CIP-200, and Sparquat
256) were tested both in-house using the Tekmar
Dohrmann Phoenix 8000 TOC Analyzer and at a
contract lab, Quantitative Technologies Inc. (QTI),
to verify the total amount of organic carbon in each
detergent at its original concentration. The method
and instrument used at QTI was a Perkin-Elmer CHN
Analyzer 2400. This experiment was performed to
make a comparison between our instrument and the
instrument in a qualified contract laboratory for infor
mation purposes only. One detergent (Chlor-Mate)
was tested in-house and compared with the available
16
Figure 1
Types of Total Organic Carbon Techniques
Oxidation Detection Technique Analytical Range (TOC) Official Methods
Combustion Thermal Conductivity Detector (TCD) 0.5 – 100% AOAC 955.07
Combustion Coulometric 1 – 100% ASTM D4129
UV/Persulfate Non-Dispersive Infrared Detector (NDIR) 0.002 – 10,000 mg/L USP 643
Heated Persulfate NDIR 0.002 to 1,000 mg/L USP 643
Combustion NDIR 0.004 – 25,000 mg/L USP 643
UV/Persulfate Membrane/Conductivity 0.0005 – 50 mg/L USP 643
UV Conductivity or NDIR 0.0005 – 0.5 mg/L USP 643

James G. Jin
vendor’s specification. The TOC results for all the
detergents are shown in Figure 2.
The differences between the in-house and QTI
results with respect to the TOC assay for CIP-100 and
CIP-200 are 5.0 percent and 9.6 percent, respectively.
These differences are relatively low compared to the
20 percent recovery criteria during recovery studies.
The difference between the in-house and QTI results
with respect to the TOC assay for Sparquat 256 is
28.4 percent. The in-house result was reviewed and
no error was noted in the performance of the test
ing procedure. The major differences may be due to
instrument and testing method variations. The result
for Chlor-Mate is within the vendor’s specification.
Swab Selection
It has been known for years that polyester is a
suitable material for TOC swabbing analysis. Over
20 different kinds of polyester swab samples were
received from The Texwipe Company LLC. Five
of them were chosen for TOC evaluation based on
sample design and the convenience for use. The
purpose of this experiment was to select a type of
swab that has little TOC background interference and
with consistent TOC results over time. Ultra purified
water with 0.05 to 0.08 ppm carbon was used for
swab analysis. The TOC results obtained from our
TOC analyzer are shown in Figure 3.
Swabs TX761 and TX741A showed increasing
TOC results from 0.0813 to 0.9692 ppm carbon and
from 0.1724 to 1.1246 ppm carbon over five days,
respectively. Swab TX700 showed an unacceptably
high TOC result of 46.1991 ppm carbon at the begin
ning of the experiment, and was therefore not tested
further. None of these swabs are suitable for our
TOC analysis.
Both polyester wipers AlphaSorb®
HC TX2412
and TX2418 show acceptable results with respect to
result consistency. The average of the seven TOC
results from TX2412 and TX2418 found in Figure
3 is 0.8327 ± 0.1860 ppm carbon. The variation is
acceptable compared to the acceptance criterion of
three ppm carbon. These two swabs with the same
material were selected to be our TOC swabs (cut to
5x5 cm2
) for detergent residue verification.
The TX3340 TOC cleaning validation kit including
Eagle EP Picher 03464-40mL clear vials, Texwipe®
TX714L-large SnapSwabsTM
, and blank vial labels
may be chosen since it is specially designed for TOC
swabbing purposes.
Detergent Recovery Evaluation from Stainless
Steel Surface
Ten stainless steel templates were spiked with
detergent solution and swabbed using the polyester
wipers AlphaSorb®
HC TX2418 (5x5 cm2
) for the
detergent recovery study. The spiking and swabbing
procedures were the same as those used for drug
substance recovery studies. Forty mL of ultra puri
fied water was added to each test tube as the extrac
tion solution, vortexed about one minute, and then
sonicated for five minutes for testing. The results are
shown in Figure 4.
The recoveries for CIP-100, CIP-200, and Chlor-
Mate are over 80 percent and no correction factor is
necessary.
For Sparquat 256, a correction factor of 0.61 will
be used. For example, if a result of 0.5 ppm carbon
is obtained from the TOC analyzer, the final reported
result would be 0.82 (0.5 ÷ 0.61) ppm carbon.
Detergent Recovery Evaluation from Non-Stain
less Steel Surfaces
The aforementioned study was repeated using
non-stainless steel templates. Two or three non-stain
17
Figure 2
Total Organic Carbon Results for Detergent Evaluation
Detergent Manufacturer/Lot Total Organic Carbon Result TOC Results
Identification From BIPI* From QTI/Vendor
CIP-100 Vestal Convac lot 211097 4.0208 ± 0.0139% 4.22%
CIP-200 Convac lot 213915 2.4986 ± 0.0114% 2.26%
Sparquat 256 ISSA (lot: n/a) 14.0232 ± 0.9336% 18.0%
Chlor-Mate WestAgro®
lot J8G0489AR 1.29% ± 0.0086% 1 – 1.5%
*Boehringer Ingelheim Pharmaceuticals, Inc.

James G. Jin
less steel templates were spiked with each detergent
solution and swabbed using the polyester wipers
AlphaSorb®
HC TX2418 (5x5 cm2
). The results are
shown in Figure 5.
For CIP-100 and CIP-200, the recoveries from
each non-metal surface are over 80 percent. There
fore, no correction factor is needed with respect to
the TOC recovery. For Sparquat 256, the recoveries
vary with different surfaces. The correction factors
are as follows:
For Delrin surface: correction factor = 0.74
For Glass surface: correction factor = 0.75
For Nylon surface: correction factor = 0.43
For Lexan surface: correction factor = 1.0
Evaluation of Detergent Residue After Rinsing
The purpose of this experiment was to evaluate:
∂ The suitability of the Acceptance Criterion
(AC) of three ppm carbon
∑ The effect of detergent concentration on deter
gent residue after rinsing
∏ Recovery of detergent from different surfaces
with and without rinsing
π Rinsing efficiency and rinse time
Four detergents (CIP-100, CIP-200, Sparquat
256, and Chlor-Mate) were used in both a concen
trated form and at a working concentration of 0.5
oz/gal. Approximately one mL of detergent solution
was pipetted and spiked onto the templates with
different materials of construction and dried with
ventilation under a hood in the research and devel
18
Figure 3
Total Organic Carbon Results (ppm C) for Swab Selection
Swab TOC/Two Hours TOC/Four Hours TOC/One Day TOC/Two Days TOC/Five Days
Description in H2
O in H2
O in H2
O in H2
O in H2
O
Polyester Alpha 0.0813 0.3221 0.3926 0.9410 0.9692
swab TX761 ± 0.0041 ± 0.0853 ± 0.0166 ± 0.0288 ± 0.0299
Polyester Alpha 0.1724 0.2509 0.5330 0.8091 1.1246
swab TX741 A ± 0.0144 ± 0.0068 ± 0.0250 ± 0.0200 ± 0.0394
Polyester wipers 1.1665 0.6091 0.8602 0.7535 0.9723
AlphaSorb®
± 0.0406 ± 0.0490 ± 0.0264 ± 0.0328 ± 0.0668
HC TX2412
Polyester wipers 0.7406 0.7269 N/A(1)
N/A(1)
N/A(1)
AlphaSorb®
± 0.0056 ± 0.0297
HC TX2418
Polyester Alpha 46.1991 N/A N/A N/A N/A
swab TX700 ± 8.0761
1. Polyester wipers AlphaSorb®
HC TX2412 and polyester wipers AlphaSorb®
HC. TX2418 is same material cut to different sizes.
Figure 4
Total Organic Carbon Recovery
Results from a Stainless
Steel Surface
Detergent Percent Number Percent
Recovery of Relative
Samples Standard
Deviation
CIP-100 111.7 30 5.92
CIP-200 92.4 10 4.10
Sparquat 256 61.0 20 8.47
Chlor-Mate 99.1 10 2.76
Note: Results were automatically corrected for the
instrument blank effect.
Figure 5
Total Organic Carbon Recovery
Results from a Non-Stainless
Steel Surface
Detergent Lexan Delrin Glass Nylon
Surface Percent Percent Percent Percent
Recovery Recovery Recovery Recovery
CIP-100 106.9 113.8 107.6 127.0
CIP-200 90.3 92.3 97.4 93.2
Sparquat 83.3 74.0 75.1 42.5
256

James G. Jin
opment manufacturing area for a minimum of four
hours. The templates were swabbed per standard
swabbing procedure either before or after rinsing,
using the polyester wipers AlphaSorb®
HC TX2412
cut to 5x5 cm2
. The rinse was first conducted using
tap water and then purified water United States
Pharmacopoeia (USP), both at room temperature
and with a slow flow rate of approximately 2.7 L/
min. Two different rinse times (30 seconds and 60
seconds) were evaluated for different detergents on
different templates to simulate the final rinse step in
our manual cleaning process. The recovery results
are reported in Figure 6.
The Tekmar Dohrmann Phoenix 8000 TOC ana
lyzer was easily able to detect the non-rinse samples
with the results of 3.911 ppm carbon, 2.0928 ppm
carbon, and 10.0868 ppm carbon for CIP-100, CIP-
200, and Sparquat 256, respectively. The results
indicate that the AC of three ppm carbon is still high
for detergents CIP-100, CIP-200, and Sparquat 256.
The AC of one ppm carbon is acceptable. There
were no differences in detectable residue for all four
detergents (both concentrated and at 0.5 oz/gal) on
stainless steel after a 30-second tap water rinse fol
lowed by a 30-second purified water, USP rinse.
Delrin was chosen for a typical material of construc
19
Figure 6
Total Organic Carbon Results on Detergent Residue by Rinsing
Sample Concentration Templates Rinse Time Area TOC Results
Identification Swabbed (ppm C)d
CIP-100 0.5 oz/gal SS a
No rinse 100 cm2
3.9111
30”/30” b
100 cm2
Less than blank
CIP-100 Concentrated SS a
30”/30” b
100 cm2
Less than blank
CIP-100 0.5 oz/gal Delrin 30”/30” b
100 cm2
Less than blank
100 cm2
Less than blank
CIP-100 0.5 oz/gal Nylon 30”/30” b
100 cm2
0.6682
CIP-100 0.5 oz/gal Glass 30”/30” b
100 cm2
0.0001
CIP-100 0.5 oz/gal Lexan 30”/30” b
100 cm2
Less than blank
No rinse 100 cm2
2.0928
30”/30” b
100 cm2
Less than blank
CIP-200 Concentrated SS a
30”/30” b
100 cm2
Less than blank
100 cm2
Less than blank
100 cm2
Less than blank
CIP-200 0.5 oz/gal Nylon 30”/30” b
100 cm2
0.7720
CIP-200 0.5 oz/gal Glass 30”/30” b
100 cm2
0.0133
CIP-200 0.5 oz/gal Lexan 30”/30” b
100 cm2
Less than blank
Sparquat 256 0.5 oz/gal SS a
No rinse 100 cm2
10.0868 c
Sparquat 256 0.5 oz/gal SS a
30”/30” b
100 cm2
0.2693 c
Sparquat 256 Concentrated SS a
30”/30” b
100 cm2
Less than blank
Sparquat 256 0.5 oz/gal Delrin 30”/30” b
100 cm2
Less than blank
Sparquat 256 0.5 oz/gal Delrin 60”/60” b
100 cm2
Less than blank
Sparquat 256 0.5 oz/gal Nylon 30”/30” b
100 cm2
0.3866 c
Sparquat 256 0.5 oz/gal Glass 30”/30” b
100 cm2
Less than blank
Sparquat 256 0.5 oz/gal Lexan 30”/30” b
100 cm2
Less than blank
Chlor-Mate 0.5 oz/gal SS a
30”/30” b
100 cm2
Less than blank
Chlor-Mate Concentrated SS a
30”/30” b
100 cm2
Less than blank
Notes: a. Stainless steel.
b. 30”/30” or 60”/60” – rinse time in seconds, tap water/purified water United States Pharmacopoeia (USP).
c. Result without correction factor.

James G. Jin
tion and 30/60 seconds were chosen for evaluation of
the rinse time. There was no difference in detectable
residue for CIP-100, CIP-200, and Sparquat 256 on
the Delrin surface after 30-second and 60-second
rinse times. The results also show that it is more dif
ficult to remove residues of CIP-100, CIP-200, and
Sparquat 256 from a Nylon surface than from other
materials.
Acceptance Criterion for Detergent Residue
There is no universal AC for detergent residue
allowed to be left on GMP equipment surfaces. In
our detergent residue verification program, the AC
for each detergent residue left on equipment surfaces
depends on the sensitivity of the instrument used for
analysis. This means we must set a low AC that is still
quantifiable and applicable. Toxicity of the detergent
is not a concern at these trace amounts detergent
level. Effects on human health from residue left on
equipment surfaces should be insignificant at a low
concentration such as 0.5 oz/gal and with a routine
rinse procedure. Our objective in this program is to
demonstrate that we are able to verify whether or not
the detergent residues are removed to an acceptable
low-level we can achieve.
Therefore, the AC should be established as close
to the instrument’s level of detection as possible. We
tighten the initial limit of three ppm carbon to AC =
1.0 ppm carbon (net reading automatically corrected
with blank by the instrument in a 40 mL solution),
which is less than two times the blank baseline. The
AC can also be expressed as AC ≤ 10 ppb carbon/
cm2
. This AC is practical and verifiable.
The significance of the 1.0 ppm carbon AC for
each detergent can be explained in Figure 7.
We can see from the above calculations that AC
= 1.0 ppm carbon means, for all detergents at 0.5
oz/gal, that we allow the maximum of 1 ÷ 3.92 =
0.26 mL of CIP-100, 1 ÷ 2.44 = 0.41 mL of CIP-200,
1 ÷ 13.68 = 0.07 mL of Sparquat 256, and 1 ÷ 1.26
= 0.79 mL of Chlor-Mate to be left on 100 cm2
of
equipment surface after cleaning, respectively.
Detergent Residue Verification Program
Our detergent verification program is designed
to be a one-time verification for each detergent
used. This was based on the rinse experiment and
the assumption that our routine rinsing procedures
performed by well trained operators are sufficient to
remove detergent residues to the level of less than
the AC. This assumption has been verified from the
results shown in Figure 6 that all the residues are eas
ily removed by a 30-second tap water rinse followed
by a 30-second purified water, USP rinse with very
low spray rate. Verification rather than validation is
currently required by the 1993 FDA, Guide to Inspec
tions of Validation of Cleaning Procedures due to
the fact that detergent residue is less significant than
drug substance residue left after cleaning.
Summary
The detergent residue verification program has
been successfully established using the Tekmar
Dohrmann Phoenix 8000 TOC analyzer. This paper
has shown the program development, and presents
critical data to support the detergent verification
reports for each detergent used.
The instrument Installation Qualification (IQ),
Operational Qualification (OQ), system calibration,
and the TOC analysis method development were
performed but not discussed in this paper. The poly
ester wipers AlphaSorb®
HC TX2412 and TX2418
cut to 5x5 cm2
have been selected as the swabs for
sampling detergent residue from equipment surface
for TOC analysis. The AC for the detergents CIP-
100, CIP-200, Sparquat 256, and Chlor-Mate with
respect to TOC has been established as AC ≤ 10 ppb
carbon/cm2
. Two different rinse times, 30 seconds
and 60 seconds, were evaluated. The results show
20
Figure 7
Significance of Total Organic Carbon Results for Detergent at 0.5 oz/gal
CIP-100 CIP-200 Sparquat 256 Chlor-mate
1 mL at 0.5 oz/gal 3.92 ppm 2.44 ppm 13.68 ppm 1.26 ppm
diluted to 40 mL
1.0 ppm C per 100 cm2
0.26 mL 0.41 mL 0.07 mL 0.79 mL
corresponding to

James G. Jin
that 30-second/30-second rinse time (30-second rinse
with tap water and then 30-second rinse with puri
fied water, USP) is sufficient to remove the detergent
residues from different material templates including
stainless steel, Delrin, Glass, Nylon, and Lexan to a
level below the AC. The correction factors were deter
mined based on the results of the recovery studies and
will be used by analytical sciences to report the final
TOC results for the detergent residue verification. o
About the Authors
James G. Jin is Chairman of the Cleaning Validation
Committee for Boehringer Ingelheim Pharmaceuti
cals, Inc., which is responsible for cleaning valida-
tion program development and implementation. He
has more than ten years experience in pharmaceuti-
cal science and business arenas. He can be reach
ed by phone at 203-798-5309.
Cheryl Woodward is Associate Director of Research
and Development (RD) Manufacturing, for Boeh
ringer Ingelheim Pharmaceuticals, Inc. She is
responsible for all aspects of GMP manufacturing
for clinical supplies and has over 18 years experi-
ence in the pharmaceutical and related industries.
She can be reached by phone at 203-798-5367.
References
1. FDA. Guide to Inspections of Validation of Cleaning Proce
dures. July, 1993.
2. Jenkins K.M., Vanderwielen A.J, Armstrong J.A, Leonard L.M,
Murphy G.P, Piros N.A. 1996. “Application of Total Organic
Carbon Analysis to Cleaning Validation.” PDA. Journal of
Pharmaceutical Science and Technology. 50. Pp 6-15.
3. Guazzaroni M., Yiin B., Yu J., 1998. “Application of Total
Organic Carbon Analysis for Cleaning Validation in Pharmaceuti
cal Manufacturing.” American Biotechnology Laboratory. Septem
ber. Pp. 66-67.
4. Westman L., Karlsson G., 2000. “Methods for Detecting Resi
dues of Cleaning Agents During Cleaning Validation.” Research
Article, Vol. 54, No. 5. September/October.
5. Furlong J., Booth B., Wallace B. 1999. “Selection of a TOC
Analyzer: Analytical Considerations.” Tekmar-Dohrmann
Application Note. Vol. 9.20.
21

I
n the pharmaceutical industry,
Good Manufacturing Practice
(GMP) requires that the clean
ing of drug manufacturing equip
ment be validated.1
Many different
validation techniques can demon
strate that the manufacturing equip
ment is cleaned and essentially free
from residual active drug substanc
es and all cleaning agents.
Common analytical techniques
in the validation process include
High Performance Liquid Chrom
atography (HPLC), spectrophotom
etry Ultraviolet/Visible (UV/Vis)
and Total Organic Carbon (TOC).
HPLC and UV/Vis are classified as
specific methods that identify and measure appropri
ate active substances. TOC is classified as a non-
specific method and is ideal for detecting all carbon-
containing compounds, including active species,
excipients, and cleaning agent(s).2,3,4,5
The disadvantage of specific methods, particular
ly HPLC, is that a new procedure must be developed
for every manufactured active drug substance. This
development process can be very time consuming
and tedious, plus important sampling issues must
also be considered. In addition, HPLC analyses must
be performed in a relatively short time period after
sampling to avoid any chemical deterioration of the
active substance. Finally, the sensitivity of HPLC
methods can be limited by the presence of degrada
tion products. Of course the disadvantage to non-
specific methods like TOC is that
they cannot identify exactly what
the residue material is. Depending
on the chosen cleaning process and
established acceptance limits, a
non-specific method may be all that
is needed to validate the process.
TOC analysis can be adapted
to any drug compound or clean
ing agent that contains carbon and
is “adequately” soluble in water.
Studies have been conducted to
demonstrate that TOC methods can
also be applied to carbon containing
compounds that have limited water
solubility, and recovery results are
equal to those achieved by HPLC.6
TOC methods are sensitive to the parts per billion
(ppb) range and are less time consuming than HPLC
or UV/Vis. United States Pharmacopoeia (USP)
TOC methods are standard for Water-for-Injection
and Purified Water,7
and simple modifications of
these methods can be used for cleaning validation.
Methodology
TOC analysis involves the oxidation of carbon and
the detection of the resulting carbon dioxide. A num
ber of different oxidation techniques exist, including
photocatalytic oxidation, chemical oxidation, and
high-temperature combustion. In this study, an Anatel
A-2000 Wide-Range TOC Analyzer, equipped with
an autosampler, was used. The Anatel A-2000 Wide-
Total Organic Carbon Analysis
for Cleaning Validation in
Pharmaceutical Manufacturing
By Karen A. Clark
Anatel Corporation
v
}TOC analysis
can be adapted
to any drug
compound or
cleaning agent
that contains
carbon and is
‘adequately’
soluble in water.~

Karen A. Clark
Range Analyzer measures TOC in accordance with
American Society for Testing and Materials (ASTM)
methods D 4779-88 and D 4839-88. It measures
TOC directly by adding phosphoric acid to the water
sample to reduce the pH from approximately two to
three. At this low pH any inorganic carbon that is
present is liberated as CO2
into a nitrogen carrier gas
and is directly measured by a non-dispersive infrared
(NDIR) detector. Any remaining carbon in the sample
is assumed to be TOC. A sodium persulfate oxidant is
then added to the sample, and in the presence of UV
radiation, the remaining carbon is oxidized to CO2
.
The amount of CO2
generated is then measured by
the NDIR to determine the amount of TOC originally
present in the water.
For equipment cleaning validation there are two
types of TOC sampling techniques. One is the direct
surface sampling of the equipment using a swab.
The second consists of a final rinse of the equipment
with high-purity water (typically 500 ppb TOC)
and collecting a sample of the rinse for analysis. In
general, direct surface sampling indicates how clean
the actual surface is. This study demonstrates how
to develop and validate a TOC method to measure
a variety of different organic residues on stain
less steel surfaces. Performance parameters tested
include linearity, method detection limit (MDL),
limit of quantitation (LOQ), accuracy, precision, and
swab recovery.
Linearity
TOC analysis should provide a linear relationship
between the measured compound concentration and
the TOC response of the analyzer. We evaluated
four different types of cleaning agents for linearity:
∂ CIP-100®
(alkaline)
∑ CIP-200®
(acidic)
∏ Alconox®
(emulsifier)
π Triton-X 100 (wetting agent)
Results are shown in Figures 1-4. Correlation
coefficients ranged from 0.9787 to 0.9998. Alconox
and Triton-X 100 have a tendency to foam, depend
ing on the concentrations that are analyzed and this
foaming phenomena can have a negative effect on
the accuracy of the TOC result (reduced R2
). Three
23
Figure 1
Linearity of CIP-100
9000
8000
7000
6000
5000
4000
3000
2000
1000
0
MeasuredTOC(ppb)
CIP 100 Concentration (ppm)
0 50 100 150 200 250
y=39.254x + 1.462
R2
=0.9997
Figure 2
Linearity of CIP- 200
9000
8000
7000
6000
5000
4000
3000
2000
1000
0
MeasuredTOC(ppb)
CIP 200 Concentration (ppm)
0 100 200 300 400 500
y=19.132x + 51.042
R2
=0.9998
Figure 3
Linearity of Alconox
45
40
35
30
25
20
15
10
5
0
MeasuredTOC(ppm)
Alconox Concentration (ppm)
0 200 400 600 800 1000
y=0.0355x + 1.1983
R2
=0.9787

Karen A. Clark
representative examples of active substances were
also tested for linearity: an excipient (sucrose), an
antibiotic (vancomycin), and endotoxin. Results
are shown in Figures 5-7. All three compounds
demonstrated excellent linearity with correlation
coefficients (R2
) ranging from 0.9996 to 0.9998.
Method Detection Limit and
Limit of Quantitation
We determined the Method Detection Limit
(MDL) by measuring the TOC response of the meth
od blank.
A method blank consists of the sampling vial,
swab, and recovery solution. In this study, the
recovery solution was low TOC ( 25 ppb) water.
Ten pre-cleaned vials were filled with the low TOC
water. One swab was placed in each vial (Texwipe
Alpha Swab TX761; tips cut off). Solutions were
vortexed and allowed to stand for one hour prior to
analysis. Four replicates from each vial were ana
lyzed. The four replicates from each of the ten blank
vials were averaged. These ten values were averaged
again and a standard deviation was calculated. The
standard deviation was multiplied by the Student t
number for n-1 degrees of freedom (3.25 for n=10),
at 99% confidence levels to determine the method
detection limit. The MDL was calculated to be 50
ppb. The Limit of Quantitation (LOQ) was calcu
lated by multiplying the MDL by three. A value of
150 ppb was obtained (see Figure 8).
Precision and Accuracy
24
Figure 4
Linearity of Triton-X 100
12500
10000
7500
5000
2500
0
MeasuredTOC(ppb)
Triton-X 100 Concentration (ppm)
0 5 10 15 20 25
y=415.76x + 16.997
R2
=0.9982
Figure 6
Linearity of Vancomycin
8000
6000
4000
2000
0
MeasuredTOC(ppb)
Vancomycin Concentration (ppb)
0 2000 4000 6000 8000
y=0.8758x + 62.133
R2
=0.9998
Figure 5
Linearity of Sucrose
12000
10000
8000
6000
4000
2000
0
MeasuredTOC(ppb)
Sucrose Concentration (ppb)
0 2000 4000 6000 8000 10000 12000
y=1.003x + 45.185
R2
=0.9996
Figure 7
Linearity of Endotoxin
8000
7000
6000
5000
4000
3000
2000
1000
0
MeasuredTOC(ppb)
Endotoxin Concentration (ppb)
0 2000 4000 6000 8000
y=0.9287x + 30.8
R2
=0.9998

Karen A. Clark
To demonstrate the precision and accuracy for this
TOC method, a representative solution of CIP-100 as
1000 ppb, or one ppm as carbon, was analyzed sequen
tially ten times. This carbon concentration was chosen
to evaluate these method parameters because, in gen
eral, TOC residual limits are typically around one ppm.
Results are listed in Figure 9. At this TOC level, the
precision was ± 1% and the accuracy was ± 5%.
Swab Recovery
Stainless steel plates were used in the swab recov
ery test to simulate manufacturing equipment. One
side of each plate was spiked with a solution of active
substance or cleaning agent. The plates were allowed
to completely dry overnight at room temperature. A
Texwipe alpha swab TX761 was moistened with low
TOC ( 25 ppb) water and the spiked plate surface was
swabbed both vertically and horizontally. The swab
end was cut off, placed into a vial to which we added
40-mL of low TOC water. The vial was capped tight,
vortexed, and allowed to stand for one hour prior to
analysis. The same volume of each solution that was
spiked onto the plates was separately spiked directly
into 40-mL of low TOC water and analyzed. The per
cent recoveries of the different substances are listed in
Figure 10. Reported values are the average of three
individual swab samples for each substance. The swab
recoveries varied between 79.3% to 95.9%
Conclusion
This study demonstrates that TOC analysis is
suitable for measuring organic residues on stain
less steel surfaces, and that it is a reliable method
for cleaning validation as demonstrated by surface
residue recoveries of 79%-96%. This methodology
25
Figure 8
Calculated TOC Averages
from 10 Blank Vials
Vial Number Average TOC (ppb)
1 58
2 72
3 75
4 93
5 79
6 102
7 60
8 83
9 67
10 54
Average 74.3
Standard Deviation 15.5
MDL (Student t, n=10) 50 ppb
LOQ 151 ppb
Figure 9
Calculated Accuracy and Precision
from 10 Replicates of a 1ppm CIP-
100 Solution as Carbon
Vial Number Measured TOC (ppb)
1 1041
1 1025
1 1039
1 1057
1 1054
2 1034
2 1042
2 1048
2 1054
2 1055
Average 1045
Standard Deviation 10.5
% CV (precision) 1.0%
% Recovery based on 105%
1 ppm C (accuracy)
Figure 10
Representative Examples of Swab Recoveries from Cleaning Agents
and Active Substances
Substance ppm C of Spike ppm C of Spiked % Recovery % RSD
Standard Solution Plate
CIP-100 1810 1710 94.5 1.8
Sucrose 2663 2112 79.3 4.9
Vancomycin 661 634 95.9 3.0
Endotoxin 902 736 80.0 2.8

Karen A. Clark
shows that low limits of detection, excellent linear
ity, precision, and accuracy can be obtained. All of
these TOC results, with the exception of Alconox
and Triton-X 100, were generated using the same
TOC method, making TOC analysis a low cost and
less time consuming alternative for cleaning valida
tion. o
About the Author
Karen A. Clark is a Product Manager at Anatel
Corporation. She has over 15 years experience in
the pharmaceutical/biotechnology industry focus-
ing on drug formulations, analytical methods devel-
opment and validation, and GLP/GMP laboratory
management. Clark holds a B.S. in Biochemistry
from Millersville University and an M.S. in Chemical
Engineering from the University of Colorado. She
can be reached by e-mail at kclark@anatel.com or at
Anatel Corporation, 2200 Central Avenue, Boulder,
CO 80301.
References
1. FDA. Current Good Manufacturing Practice Regulations, 21
CFR 211.220.
2. Baffi, R. et al. 1991. “A Total Organic Carbon Analysis Method
for Validating Cleaning Between Products in Biopharmaceutical
Manufacturing.” Journal of Parenteral Science and Technology
45, no. 1: 13-9.
3. Jenkins, K. M. et al. 1996. “Application of Total Organic Carbon
Analysis to Cleaning Validation.” PDA Journal of Pharm
aceutical Science and Technology 50, no. 1: 6-15.
4. Strege, M. A. et al. 1996. “Total Organic Carbon Analysis of Swab
Samples for the Cleaning Validation of Bioprocess Fermentation
Equipment.” BioPharm (April).
5. Guazzaroni, M. et al. 1998. “Application of Total Organic Car
bon Analysis for Cleaning Validation in Pharmaceutical Man
ufacturing.” American Biotechnology Laboratory 16, no. 10
(September).
6. Walsh, A. 1999. “Using TOC Analysis for Cleaning Validation.”
Presented at The Validation Council’s Conference on Cleaning
Validation, 27 October, Princeton, New Jersey.
7. USP 23, Fifth Supplement, 15 November 1996.
26

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T
he FDA recognizes the
importance of effective
cleaning and sanitizing pro
tocols as a proactive measure in
preventing cross-contamination in
the pharmaceutical and cosmetic
industries:
21CFR 211.67: “Equipment
and utensils shall be cleaned, main
tained, and sanitized at appropriate
intervals to prevent malfunctions
or contamination that would alter
the safety, identity, strength, qual
ity, or purity of the drug product
beyond the official or other estab
lished requirements.”
In order to comply with this reg
ulatory requirement, sound clean
ing and sanitizing protocols must
be developed and followed. One
of the most critical components of
any cleaning program is detergent
selection. Different processes and
potential contaminants may require
different detergents that are appro
priate for the application. In certain
cleaning applications, a neutral foaming detergent
might be appropriate, whereas in others, a non-foam
ing alkaline detergent is desirable. The choice of
detergent for a given application
should be based on sound, scientific
reasoning.
A sound rationale for detergent
selection begins at the manufactur
ing site, where the process and
cleaning program will take place. A
full evaluation of the process, clean
ing strategies, potential contaminant
levels, and available utilities is a
good first step. Following this step,
laboratory testing is required to
determine the exact nature of the
potential contaminant. Next, ident
ification and testing of various clean
ing chemistries against the potential
contaminant is performed to deter
mine which detergent type is best
suited for contaminant removal. The
next step is to return to the manufac
turing site, test the cleaning chem
istry, and optimize the program.
This approach provides a sound,
scientific rationale for the detergent
selection and lays a firm foundation
to the formal cleaning protocol, once
developed.
This article will discuss the key
factors that must be addressed when selecting a
detergent. Each factor will be discussed in detail
and examples are given when appropriate. The roles
Detergent Selection – A First
Critical Step in Developing a
Validated Cleaning Program
By Mark Altier
Ecolab, Inc.
v
}This article will
discuss the key
factors that
must be
addressed when
selecting a
detergent. Each
factor will be
discussed in
detail and
examples are
given when
appropriate.
The roles of
laboratory testing
and plant
optimization are
also addressed.~

Mark Altier
of laboratory testing and plant optimization are also
addressed.
The Five Factors for Determining
Detergent Suitability
There are five key factors that must be addressed
when determining which detergent is most suitable
for a cleaning application. These are:
∂ Nature of the residue (or potential contami
nant)
∑ Surface to be cleaned
∏ Method of application
π Role of water
∫ Environmental factors
All five of these factors must be addressed when
developing a cleaning program. Failure to address
any of these issues in sufficient detail can result in a
less than desirable cleaning program and could place
the successful completion of the cleaning validation
at serious risk.
The Nature of the Residue
A residue can be defined as any unwanted matter
or potential contaminant on the surface of the object
or equipment being cleaned. Oftentimes, what is
referred to as a “residue,” is in fact a finished prod
uct, drug active, or other component that is produced
using the process equipment that is being cleaned.
The terms “residue,” “contaminant,” and “potential
contaminant” will be used interchangeably through
out this article.
Determination of the nature of a residue is a funda
mental component in the development of any cleaning
program. In some cases, the exact nature and com
position of a residue is known. For example, if the
residue is a finished product, the exact composition
and physical properties are almost always known.
However, the identity and nature of the residue may
be completely unknown if the residue is composed
of an intermediate, byproduct, or result of thermal,
chemical, or other degradation of a previously known
substance.
The nature of the potential contaminant plays a
central role in determining what type of detergent
is most appropriate for the application. Individual
residues require different detergent chemistries. All
residue types will fall into one of the following three
categories: organic, inorganic, or a combination of
these. Most potential contaminants are a combina
tion of organic and inorganic components. Common
residue types in the pharmaceutical industry are
given in Figure 1.
A number of powerful analytical instruments are
available that can provide tremendous insight into
the nature and composition of almost any unknown
potential contaminant type. Some of the more useful
tools include:
• Fourier Transform Infrared Spectroscopy
(FTIR)
• Energy Dispersive X-Ray Spectroscopy (EDS)
• Scanning Electron Microscopy (SEM)
• Compound microscopic imaging
• Nuclear Magnetic Resonance imaging (NMR)
• Inductively Coupled Plasma detector (ICP)
• Atomic Absorption Analyzer (AA)
Often, a combination of two or more of these tools
is required to provide a full picture of a potential
contaminant in question. For example, Figure 2 and
Figure 3 are typical images generated to help char
acterize unknown potential contaminant samples.
This type of analysis is invaluable in determining the
exact residue type and breakdown of the organic and
inorganic portions of a residue.
Figure 2 is an FTIR image of an unknown residue.
This characterizes and gives a general breakdown of
29
Figure 1
Common Residue Types in the
Pharmaceutical Industry
Organic Residues Inorganic Residues
Eudragit Titanium Dioxide
Acetaminophen Zinc Oxide
Carbopols Iron Oxide
Albuterol Sulfate Calcium Carbonate
Neomycin Sulfate Inorganic Salts
Water/Oil – Oil/Water Silicon Dioxide
Emulsions
Glyburide

Mark Altier
30
Figure 2
FTIR Scan of Unknown Sample. This Analysis Indicates the Presence of
Alkyl and Amide Protein Components and Possible Inorganic Content
3933.71
2958.86
2926.38
2854.86
2287.55
2257.66
2211.86
2165.99
2155.88
2033.97
2013.07
1631.22
1545.75
1454.66
1396.07
1311.04
1251.26
1077.51
1044.64
980.456
870.204
694.924
3500 3000 2500 2000 1500 1000
Wave Number (cm-1)
.35
.30
.25
.20
.15
.10
.05
0
Absorbance
Figure 3
EDS Scan of Unknown Sample
This Analysis Confirms the Presence of Inorganic Components Such as Silicon,
Aluminum, and Iron, in Addition to Organic Compounds
0.000 1.000 2.000 3.000 4.000 5.000 6.000 7.000 8.000
Key
600
580
560
540
520
500
480
460
440
420
400
380
360
340
320
300
280
260
240
220
200
180
160
140
120
100
80
60
40
20
0
Counts
C
O
Fe
Mg
Al
Si
Fe
Fe

Mark Altier
the organic portion of the residue. FTIR imaging
gives valuable insight into the functional groups that
may be present in the organic component of a residue.
Figure 3 confirms the presence of inorganic material
and identifies the specific inorganic components pres
ent in an unknown sample. This information is useful
when determining which chelant or surfactant family
is most suitable for removing or tying up the free
metal ions and other inorganic material.
Combined, FTIR and EDS imaging can give a
complete picture of most unknown residues. These
analyses provide the information needed to select a
group of detergent chemistries that are formulated
and known to be effective against the residue type.
Surfaces To Be Cleaned
Different substrates (i.e., product contact surfaces,
such as stainless steel, glass, or plastic) will interact
differently with the contaminant and the detergent
system. Some materials, such as glass, and aluminum,
are not tolerant to high pH systems. Other substrates
may tolerate high pH, but may not tolerate chlorine or
chlorides. It is important to have a clear understand
ing of how the substrate being cleaned will interact
with the detergent system, otherwise serious dam
age to equipment surfaces can result. A SEM image,
shown in Figure 4, is a stainless steel surface that has
been pitted by using an incompatible detergent. The
prospective customer in this case felt that the residue
was becoming more tenacious with time and was
using higher detergent concentrations to remove the
residue.
A close look at the surface revealed that the surface
was actually being pitted by the detergent, providing
microscopic crevices where the residue was able to
harbor during the cleaning cycle. This problem was
aggravated by the fact that the customer continued to
increase the detergent concentration, which acceler
ated the rate and degree of corrosion, and provided
the residue with even more locations to harbor during
the cleaning cycle.
These images clearly demonstrate the problems
31
Figure 4
Microscopic Corrosion of a Stainless Steel Surface Caused by Improper
Detergent Selection. Inset Shows Boxed Region at 1000 Times Magnification

Mark Altier
that can be caused by improper detergent selection.
In this case, the customer was advised to discontinue
the use of the incompatible detergent, and a compat
ible detergent chemistry was identified and tested.
The customer was also required to replace or repair
damaged equipment.
When developing a cleaning protocol, it is neces
sary to identify all components of the process that will
be exposed to the cleaning chemical(s). This includes
equipment surfaces, gasket materials, nozzles, piping,
pumps, etc. It is also important to consider surfaces
that will be exposed to the vapor phase of the cleaning
solution, such as overhead spaces in enclosed vessels
and pipes. A common mistake is to concentrate only
on items that will have direct contact with the liquid
solution, neglecting the vapor phase.
Method of Application
There are several common methods of applying
a detergent to equipment surfaces. Some are more
common than others in the pharmaceutical industry.
Some of the more common methods of application
in the pharmaceutical industry include:
• Clean-in-Place (CIP)
• Clean Out-of-Place (COP)
• Manual scrubbing/wiping
• High and low pressure spray
• Soaking/immersion
Each of these application methods dictate cer
tain desirable or undesirable detergent properties.
For example, a high pH detergent is ideal in a CIP
application where little, or no direct contact is made
between the detergent and the operator. In a manual
application, however, a high pH detergent creates
a significant safety risk to an operator handling the
detergent concentrate and use solutions. In a manual
application, a neutral or mildly alkaline detergent
(pH 7.0 – 10.0) is much more desirable as it sig
nificantly reduces the risk for accidental chemical
burn to the operator’s eyes, skin, and mucous mem
branes.
Other detergent characteristics, such as foam
properties, are important considerations in light of the
method by which the cleaning solution will be applied
to a surface. A moderate-to-high foaming detergent is
not desirable when used in an agitated immersion or
CIP application, as both create high-shear and thus
are prone to foam formation. The result of this is a
detergent solution that foams out-of-process or CIP
vessels, cavitates pumps, and provides inefficient
surface coverage when sprayed on the inside of a ves
sel through a spray ball. Conversely, a high foaming
detergent is desirable in a manual application, as this
gives the operator a visual indication of where the
detergent solution has been applied to the surface.
Some cleaning application technologies exist
that are widely used in other industries, but have
not taken hold in the pharmaceutical industry. These
application methods include:
• Thin film cleaning
• Stabilized foam generators
• Built, solvated detergents (Generally Recog
nized As Safe [GRAS])
Discussion regarding these application methods
are outside of this article and will not be addressed.
The Role of Water
In general, 95-99% of a cleaning solution is
composed of water. It is important to know the
purity level of the water being used for cleaning and
sanitizing. In many pharmaceutical applications, the
water being used for cleaning and sanitizing is high
purity water. However, this is not the case in every
application and in these cases, knowing and under
standing how the purity level of the process water
affects the cleaning process is critical. Some of the
factors that can affect the cleaning process include
water hardness, pH, metals, salts, and microbial con
tamination. Refer to Figure 5.
Of the factors listed above, water hardness has the
most significant impact on cleaning and sanitizing
solutions. Water hardness can be classified as tem
porary or permanent hardness. Temporary hardness
indicates the presence of bicarbonates of magnesium
or calcium. Both of these compounds are readily
water soluble and can be present at high levels. When
heated, these compounds react to form the carbonate
salts, which are water insoluble. Permanent hardness
refers to a condition where the chloride or sulfate
salts of magnesium and/or calcium are present in the
water. These compounds are also very water soluble,
but are unaffected by temperature.
32

Mark Altier
Both temporary and permanent hardness cause
problems in alkaline solutions, as they both pre
cipitate in high pH solutions and cause scaling on
equipment surfaces. Water hardness is responsible
for scaling, film formation, excessive detergent con
sumption, and formation of precipitate. Water hard
ness can be addressed by installing a water softening
system, or by using a detergent that is formulated to
handle hard water.
Environmental Factors
Many pharmaceutical plants have some type of
effluent restrictions mandated by local municipalities,
or by the plant’s internal effluent treatment facility.
Common factors that must be considered are pH,
phosphate levels, Biological Oxygen Demand (BOD)
or Chemical Oxygen Demand (COD) loading, Total
Organic Carbon (TOC) levels, and solids levels. In
many cases, the correct choice of detergent can help
reduce the impact on components of the effluent
stream that are a concern. For example, if phosphates
are a concern, a detergent that contains low levels of
phosphate can be used. Another example is a situation
where the pH of the effluent must not exceed 10 and
must not fall below four. If a strong acid or alkaline
detergent is used, the pH restrictions could be violated.
In this case, choosing a neutral, mildly alkaline or
mildly acidic detergent may be the solution. However,
in some cases, a strongly acidic or alkaline detergent
might be required to effectively remove the potential
contaminant from equipment surfaces. If a strong
alkaline detergent is required, the cleaning cycle could
be designed to include an acid rinse. The acid rinse
will help reduce the amount of rinse water required to
neutralize residual alkalinity in the system, will help
remove any inorganic residues, and can be captured
and mixed with the alkaline wash water to neutralize.
In general, detergents will have the greatest
impact on pH and phosphate levels. Relative to the
residue load, detergents generally have little impact
on BOD, COD, TOC, or solids levels.
If effluent restrictions exist, these should be
addressed in the early stages of the development of
a cleaning program to avoid compounded problems
later on when the cleaning protocol is implemented.
At this point, five key factors that should be
considered when selecting a detergent to be used
as a part of a validated cleaning program have been
discussed. Once these factors are addressed and an
appropriate detergent chemistry is identified, labora
tory testing should be done to verify that the chem
istry is effective against the potential contaminant.
Other cleaning parameters such as cleaning time,
temperature, and concentration can be evaluated in
the laboratory as well.
Laboratory Testing
Cleaning studies conducted in the laboratory can
be designed to closely mimic the actual applica
tion method, such as a CIP system, or they can be
33
Figure 5
Typical Water Impurities That Can
Impact a Cleaning Process
Component Chemical Problem
Formula Caused
Barium Sulfate BaSO4
Scale
Carbon Dioxide CO2
Corrosion
Calcium Bicarbonate Ca(HCO3
)2
Scale and
Corrosion
Calcium Sulfate CaSO4
Scale and
Corrosion
Iron Fe Scale
Manganese Mn Scale
Magnesium Bicarbonate Mg(HCO3
)2
Scale
Magnesium Chloride MgCl2
Scale and
Corrosion
Magnesium Sulfate MgSO4
Scale and
Corrosion
Oxygen O2
Corrosion
Sodium Chloride NaCl Corrosion
Silica Si Scale
Suspended Solids r Deposit and
Corrosion
Figure 6
Water Hardness
(Reported as CaCO3
) Rating
Hardness Grains Parts Per
Per Gallon Million (PPM)
Soft 0 – 3.5 0 – 60
Moderately Hard 3.5 – 7.0 60 – 120
Hard 7.0 – 10.5 120 – 180
Very Hard 10.5 180

Mark Altier
designed to stress the system to differentiate between
similar cleaning chemistries. An example of the lat
ter is a designed study that removes all mechanical
action from the system, forcing the chemistry type
and concentration, thermal energy, and contact
time to act on the residue. This approach is espe
cially effective in differentiating between similar
chemistries that appear to be equally effective when
applied using some type of mechanical action.
An important component of designed clean
ing studies is the preparation of the residue being
tested.
Typically, the residue is applied to a 304 or 316
stainless steel coupon and the treated coupon is then
subjected to the cleaning solution. The application of
the residue to the coupon is critical to obtain results
that can be directly applied to the actual system in
the plant. For example, a manufacturing process
may involve a heating step that causes some of the
finished product to “bake” onto a vessel side wall.
To obtain results that are applicable to this situation,
the residue should be applied to the coupon surface,
heated, and then allowed to bake for an equivalent
amount of time as is experienced in the actual pro
cess. If this is not done, the results of the study will
have little relevance to the development of a cleaning
program aimed at removing a baked on residue from
equipment surfaces.
Prior to implementing any cleaning studies, a
set of success criteria must be established. Once the
cleaning studies have been completed, quantitative
measurements against the success criteria should be
made. Based on the results of this work, a final deter
gent chemistry recommendation is derived. Ideally,
the detergent chemistry should meet or exceed all
established success criteria.
The end result of the laboratory work will be a
scientifically sound recommendation of detergent
chemistry and other important cleaning parameters
such as cleaning time, temperature, and concentra
tion. This is the basis for the overall cleaning pro
gram that will be tested at the production facility.
The importance of performing preliminary labora
tory testing is that it provides a sound, scientific
rationale of why the selected chemistry is appropri
ate for the cleaning application.
Plant Optimization
Once a cleaning chemistry has been identified
and verified in the laboratory and other cleaning
parameters such as cleaning time, temperature and
concentration have been established, testing and
optimization must be carried out at the production
plant. Initial optimization and testing is usually done
on a pilot scale, prior to scaling up. The results of the
laboratory cleaning studies should be used as a guide
or a starting point for the optimization process at the
plant site.
Conclusion
Process cleaning is an integral component of any
pharmaceutical process. The five key factors that
must be addressed to help identify a detergent when
developing a cleaning program have been defined
and discussed. The interaction of these factors with
each other and with the development of a cleaning
program must be understood. Laboratory testing
is critical for documenting the appropriateness of
the detergent selection for the cleaning applica
tion. Plant optimization is a final critical step prior
to starting the validation process at the production
facility. When these steps are taken, a complete,
scientifically sound approach to the development of
a cleaning program can be documented. o
About the Author
Mark Altier is a Principal Chemical Engineer for
Ecolab Inc., where he manages their pharmaceu-
tical and cosmetic programs. Mark has worked
for Ecolab for seven years and has held positions
in quality assurance, process engineering, and
research and development. He can be reached at
651-306-5876, by fax at 651-552-4899, or by e-mail
at mark.altier@ecolab.com.
34

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