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Cleaning Validation: Factors
Affecting Recovery Data and
Material of Construction
Grouping
Richard J. Forsyth
ABSTRACT
Material of construction is a factor in recovery of residue for cleaning validation. Analysis of existing recovery data demonstrated that recovery factors for drug
products on different materials of construction could
be categorized into several groupings. The groupings
based on the recovery data were not aligned with the
material composition (e.g., metal, plastic, glass, etc.). An
examination of additional factors clarified the grouping
of materials versus recovery data.
Materials of construction used in laboratory studies to
represent commercial manufacturing equipment must be
representative of equipment. Materials of construction
that exhibit low recovery should be replaced wherever
practical for an alternative material with a higher recovery to avoid any potential cross-contamination due to
slow release of residue from the material of construction.
If problematic materials cannot be released, equipment
should be dedicated or restricted for use to the active
pharmaceutical ingredient with low recovery.
INTRODUCTION
Residue assays are a critical requirement in establishing a validated cleaning program. They are essential to
accurately determine amounts of residual active pharmaceutical ingredient (API) remaining on equipment
after cleaning. This determination is then compared to
the acceptable residue limit (ARL) for a given process or
equipment train (1).
For more Author
information,
go to
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The residue assay methods are typically validated for
the following parameters:
• Linearity
• Precision
• Sensitivity
• Specificity
• Recovery.
From an analytical standpoint, recovery is from the
cleaning test sample, usually from a swab. For the cleaning program, the concern is the recovery of the residue
from the manufacturing equipment (1, 2). Recoveries
are determined through experiments in which sample
equipment materials spiked with known amounts of the
substance of interest are swabbed and tested. The swab
and the swabbing solvent must be capable of recovering
a sufficient amount of material to allow an accurate and
precise measurement of the spiked component.
The most important aspects for product recovery
factors are that the data are consistent, reproducible,
and provide an adjusted ARL that is above the limit of
quantitation of the analytical method. The ARL must
be achievable and practical. If recoveries are too low,
either the methods need to be optimized or the manufacturing equipment must be dedicated or restricted for
manufacturing only the specific API.
A recent study (3) gathered and statistically analyzed all
available historical data and achieved the following:
• Grouped materials of construction according to recov-
[
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ABOUT THE AUTHOR
Richard Forsyth is a pharmaceutical consultant with a background in cleaning validation and analytical
chemistry. He may be reached by e-mail at [email protected].
Journal
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ery performance. This resulted in five distinct groupings with statistically different recovery levels. These
groupings, however, could not be correlated to material properties. For example, different types of plastics
were noted in all five groups. Most metals, including
stainless steel, were categorized into the two groups
with the highest recovery levels; however, aluminum
was in the second lowest recovery group.
• Selected representative materials from each grouping
for potential testing if appropriate.
The end result of the analysis was a reduction in the
number of studies required for new substances in a cleaning validation program. The analysis concluded that a
recovery study conducted at one site using stainless steel
would serve as a representative material of construction
for most materials used in drug product manufacturing,
and is applicable across multiple sites.
The study was not able to identify the physical characteristics of the materials and parameters that influence recovery data results. There was no obvious correlation between
the recovery data and the similarity in composition (e.g.,
metals, plastics, glass) of the materials of construction.
Different metals, rubbers, and plastics occupied different
groups across the range of residue recoveries. Because the
data set was generated at numerous sites worldwide over
several years, it was not practical to assemble representative
samples of all of the materials of construction.
The following are a number of additional parameters
that could affect the recovery of residue from equipment
surfaces (4):
• Residue solubility
• Swab material
• Solvent type
• Recovery technique by sampling technician
• Residue cleanability (5), which in turn may be related
to its solubility.
These parameters are interrelated. The cleanability of
the residue impacts the choice of cleaning procedure; the
harder a residue is to clean, the higher the anticipated
amount of residue to be swabbed. The amount of anticipated residue affects the choice of swab and solvent as well
as the validation of the analytical testing method.
The materials used to recover the residue also affect
recovery. The swab material must be able to absorb sufficient residue and solvent to remove the residue from
the equipment material surface. The type and amount
of recovery solvent must dissolve the residue sufficiently
for removal without leaving residue or solvent behind.
The swabbing technique should be standardized and
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adequately controlled to minimize subjectivity and
should consistently recover enough residue so that a precise measurement is assured. The combination of swab
material and recovery solvent should not interfere with
the subsequent sample assay.
Although the composition of the materials of construction provided no correlation with the recovery data, the
physical properties of the materials could affect recoveries. There have been studies that have examined surface
roughness and how it affects the ability to clean surfaces
(6). The hardness of the individual materials might also
help explain certain residue recoveries. The porosity of
certain materials could account for several of the low
recovery data sets.
The objective of this study was to gather historical data,
generate necessary additional data, and statistically analyze the data relating to these parameters. The end result
of this analysis identified the physical characteristics of the
materials of construction and parameters that influence
recovery data results. An understanding of the relationship
between the recovery data and the materials of construction was achieved.
EXPERIMENTAL
The solubility of the recovered materials was considered
as a factor affecting swab recovery. The solubility of a
number of APIs was tabulated and analyzed in comparison to the respective recovery data. The swab technique
was also examined as a factor in recoveries. The swab
techniques from the different sites were reviewed and the
swab materials were examined for possible correlation
to low recoveries. The recovery solvent and extraction
procedure were examined for several low recovery APIs
to determine if recoveries could be raised.
The cleanability data for a number of APIs and formulations were tabulated, statistically analyzed, and compared
to the recovery data. The gravimetric-based cleanability
method consisted of placing a wet slurry consisting of a
set amount of water and formulation and API onto a preweighed coupon (23 mm x 20 mm). The coupon was 316L
SS foil. In a single run, five soiled coupons were made
along with three control coupons, and were placed into a
humidity-controlled box (RH = 30%) for a set amount of
time (dirty hold time, usually 24 hrs). The coupons were
then weighed and photographed and then placed into a
modified cuvette holder.
The coupons were then exposed to a cleaning cycle that
usually consisted of three process steps including pre-rinse,
detergent wash, and final rinse. The typical cycle consisted
of a 10-second dip in 80°C USP water; a 10-second dip in
80°C clean-in-place (CIP) solution (0-3%), and a last 10iv thome.com
R ICH A R D J. FORSY T H
seceond dip in 80°C USP water. The coupons were then
returned to the glove box for an additional 24 hours. After
which, the coupons were weighed and photographed. The
cleanability was then calculated based on weight.
Recovery experiments were conducted with representative materials of construction that had provided both
high and low recoveries. Earlier recovery data (3) defined
groups of material of construction inclusive of variability
due to individual compounds. Therefore, the groupings
were independent of the compound recovered. For this
study, two compounds were tested to provide adequate
data points for each material of construction. Stainless
steel and a smooth Neoprene rubber coupons not only
represented the high and low recoveries (3), they also
represented a hard and soft material, respectively. Stainless steel coupons machined to different roughness factors
provided data. A Surtonic Duo surface finish analysis
instrument (Taylor-Hobson, ID C-5524) was used to measure surface roughness of the coupons. Coupons with
relatively smooth surfaces presented a uniform roughness.
Rough surface coupons had grains resulting in different
roughness measurements in perpendicular directions.
In these cases, unidirectional swab samples attempted to
discern recovery differences between the two roughness
measurements. A rough Neoprene rubber and anodized
aluminum coupons provided data to address porosity.
Residue spots were prepared in triplicate and individual,
single swabs taken for recovery. The swab samples were
assayed with a validated high performance liquid chromatography (HPLC) method specific for the API and an
average recovery factor was determined.
Table I: Solubility and recovery data comparison.
Compound
Recovery
Water solubility
Clinoril
73
1000
Invanz
98
500
Singulair
90
240
Crixivan
76
100
Tryptanol
75
100
Prinivil
99
97
Fosamax
87
40
Fosamax Plus D3
75
40
Cpd D
82
25
Niacin
87
4.25
Sinemet
81
1
Pepcid
77
0.74
Compound C
83
0.722
Compound A
84
0.19
Moduretic 5/50 mg
87
0.1
Proscar/Propecia
91
0.1
Compound B
98
0.1
Decadron
89
0.1
Noroxin
86
0.091
Arcoxia
83
0.06
Compound E
91
0.03
Zocor
81
0.03
Stocrin
78
0.01
Mevacor 40 mg
81
0.004
RESULTS AND DISCUSSION
Results are discussed for API aqueous solubility and recovery; recovery, aqueous solubility, and cleanability; material
hardness; surface roughness; and porosity.
API Aqueous Solubility and Recovery
The initial analysis compared the previously determined
recovery data (3) with the solubility data for the respective
compounds (see Table I). Solubilities ranged from 1000
mg/mL to 0.004 mg/mL. Recoveries for the compounds
examined ranged from 89% to 73%. There was no direct
relationship between the water solubility of the compound
and its respective recovery. In fact, the compound with
the lowest recovery (73%) also had the highest solubility
(1000 mg/ml). This was not unexpected for this data set.
Although water is the first choice as a recovery solvent, if
water solubility is low an alternate organic solvent (e.g.,
ethanol, methanol, acetonitrile) is employed. Part of
the recovery assessment is to assure the compound has
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adequate solubility in the chosen recovery solvent. The
relatively high recovery data demonstrated that acceptable
laboratory methods using appropriate recovery solvents
had been developed. Depending on recovery data, recovery solvents may use combinations of polar, semipolar,
and non-polar solvents.
The recovery factors including swab technique, swab
material, recovery solvent, and extraction procedure were
examined as part of the earlier study (3). These four factors
were combined and considered as the site-to-site variability for the recovery data. The additional variability
among sites was not significant relative to the variability
for repeated measurements due to differences in product
and material of construction. Ninety-seven percent of
the variability was attributable to different recovery factor (RF) means for each material and product, while only
3% additional variance was attributable to the swab, solvent, and technique factors across sites. This meant that
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Table II: Cleanability and recovery data comparison.
Cleanability
Compound
Recovery
Water solubility
Water
CIP 100
Fosamax Plus D3
75
40
100
100
Mevacor 40 mg
81
0.004
99
100
Stocrin
78
<0.010
99
100
Compound E
91
<0.03
73
90
Arcoxia
83
0.06
68
96
78
Pepcid
77
0.74
61
69
91
Compound A
84
0.19
44
45
50
Zocor
81
<0.03
40
42
37
Table III: Recovery, solubility, and cleanability
comparison in descending order.
Recovery
Water solubility
Cleanability
Compound E
Fosamax Plus D3
Fosamax Plus D3
Compound A
Pepcid
Mevacor 40 mg
Arcoxia
Compound A
Stocrin
Mevacor 40 mg
Arcoxia
Compound E
Zocor
Compound E
Arcoxia
Stocrin
Zocor
Pepcid
Pepcid
Stocrin
Compound A
Fosamax Plus D3
Mevacor 40 mg
Zocor
across-site and within-site variability could be combined,
and comparisons of materials and products across sites
had essentially the same precision as comparisons made
within a single site. This was a very useful finding, since
it allowed RF results to be leveraged among different sites
without accounting for site-to-site differences.
Recovery, Aqueous Solubility, and
Cleanability
A similar analysis compared the recovery data with
cleanability data for several of the compounds generated
in both water and detergents in an independent study
(see Table II). For this data set, the cleanability ranged
from 100% to 37%. The respective recovery data ranged
between 91% and 75%. Again there was no direct relationship drawn from the data. Although cleanability is
a good indicator of the ability to clean a compound from
manufacturing equipment, it does not necessarily indicate
the ability to recover residue for testing. Table II data demonstrates general consistency in rank order cleanability
for the three cleaning liquids (water, CIP 100, CIP 300).
This may be expected because all cleaning liquids were
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Journal
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CIP 300
aqueous and differed only in proprietary formulation.
CIP 100 is an alkaline cleaning liquid; CIP 300 is a neutral
phosphate-free cleaning liquid.
Table III more clearly demonstrates the lack of correlation among the data. Recovery, water solubility, and
cleanability are listed in descending rank order for the eight
compounds with data in all three categories. There is no
correlation among the data and there is no obvious relation
between the solubility and cleanability data, which might
be reasonably expected. The only conclusion is that there
is no discernable connection or trend among the data.
An analysis of the HPLC recovery data led to a number
of conclusions. An initial comparison in Table IV of the
recovery data to the previously determined recovery data
(3) demonstrated similar recovery data for all materials
except the Neoprene samples. The Neoprene samples
for this study had been sourced from a different vendor
than the samples for the original (3) work. The Neoprene
in the original work was not designated as smooth or
rough. This demonstrates the importance of performing
recoveries on the same material as used in manufacturing
whenever possible.
Material Hardness
Comparison of the percentage of recovery data for stainless steel and smooth Neoprene in Table IV indicates that
the hardness or softness of the material had no impact on
recovery. The average recoveries from the mill finish stainless steel and the smooth neoprene were equivalent.
Surface Roughness
Table V provides recovery data from different surface roughness materials. Data from stainless steel were equivalent
across the entire roughness range tested. The smoothest
coupons (0.01 µm) were mirror finish stainless and the
0.83 µm were mill finish or 316 finish stainless steel. The
rougher stainless steel finishes (1.1 – 4.5 µm) were specifiiv thome.com
R ICH A R D J. FORSY T H
cally machined for these experiments. The glass, brass,
polytetrafluoroethylene (PTFE), and smooth Neoprene,
which were comparatively smooth, had recovery numbers in the same range as the stainless steel. The rubber
with a 4.94 µm roughness also demonstrated equivalent
recovery data. Recoveries from the rough Neoprene were
much lower, indicating that surface roughness is a factor
in the ability to recover residue from equipment surfaces.
However, recoveries from the aluminum sample were
also low even though the roughness was comparable to
stainless steel and rubber. This indicated that another
factor was the cause of the low recoveries.
Porosity
The rough Neoprene was also very porous and this physical
characteristic certainly contributed to the low recoveries.
The spotted residue clearly entered the pores of the material as soon as it was spotted. A background check of the
aluminum sample revealed that it was anodized aluminum, which is also a porous material (7, 8). Anodized
aluminum can have pore diameters from 10–500 nm and
with different layer thicknesses.
Other materials demonstrating lowest recoveries were
plastics containing methacrylate or butadiene-acrylonitrile
(3). RF for these materials ranged from 31-44. Understanding the recovery factors for cleaning validation of elastomers
(rubbers) and plastics, both uncrosslinked and crosslinked,
may be complex. Material contamination during the
manufacturing process and during the cleaning process
are affected by the transport properties for the pairing of
the particular compound and material of construction
being considered, including the time of contact between
the compound and material of construction, and the time
of recovery used for the cleaning validation. The transport
properties include permeability, the diffusion coefficient,
and the solubility coefficient of the compound into the
material of construction. The permeability is essentially
the product of the diffusion coefficient and the solubility
coefficient, and these three properties are temperature
dependent. A higher diffusion coefficient indicates that
a compound will diffuse further into the material of construction, and a higher solubility coefficient means that
more compound can equilibrate within the material of
construction at a given concentration of exposure. Another
factor that can influence the recovery is the solvent chosen
for the cleaning validation, as the solvent can affect the
transport properties of the material of construction. If the
material of construction has a high affinity for the solvent,
the material could swell and the compound under test
could further diffuse into the material along with some of
the cleaning solvent, thereby reducing the recovery.
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Table IV: Material % recovery.
Material
Average % recovery
Average % recovery
reference 3
Stainless steel
81.8
83.8
Glass
81.1
85.5
Brass
80.9
80.6
PTFE
85.5
83.9
Neoprene (smooth)
79.4
31-44
Aluminum #7
55.3
53-56
Rubber #5
88.6
81.9
Neoprene (rough)
11.7
31-44
Table V: HPLC recovery data.
Material
Surface
roughness
(µm)
Amount
spotted
(µg)
Average %
recovery
Stainless steel
0.01
100
86.6
Stainless steel
0.4
100
77.6
Stainless steel
0.83
100
83.4
Stainless steel
1.1
100
83.7
Stainless steel
1.3
100
79.2
Stainless steel
3.7
100
84.1
Stainless steel
4.5
100
78.3
Glass
0.03
100
81.1
Brass
0.16
100
80.9
PTFE
1.11
100
85.5
Neoprene
(smooth)
1.57
100
79.4
Aluminum #7
2.3
100
56.4
Rubber #5
4.94
100
88.6
Aluminum #7
5.34
100
54.1
Neoprene (rough)
12.8
100
13.5
Neoprene (rough)
18.9
100
9.9
Transport of compounds through materials generally
occurs more rapidly in elastomers such as Neoprene,
EDPM, latex, or silicone. Material transport is relatively
less in glassy thermoplastics such as Lexan. The degree
of crystallinity, the degree of crosslinking, and the proportion of fillers will also affect the transport properties.
The longer period of time a material is exposed to a compound, the further into the material the compound will
diffuse, thereby making full recovery of the compound
more difficult for a fixed cleaning period of time. Glassy
polymers with glass transition temperatures above room
temperature tend to allow materials to diffuse more slowly
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than rubbery polymers with glass transition temperatures
below room temperature. However, rubbery polymers are
usually crosslinked and filled, which tends to decrease
diffusion rates within the given rubbery material.
Overall, transport properties are very specific. Complex interactions dependent upon the solvent, material
of construction, and the compound under test cannot
be generalized in a manner that will allow prediction of
recovery during cleaning validation tests. Explanation
of the relative performance of one compound against
another for a given material of construction or the relative performance of one material of construction against
another for a given compound cannot be predicted. In
order to better understand particular outcomes, specific
measurements of fundamental transport properties for
the solvents, compounds, and materials of construction
would be necessary.
These measurements are unnecessary for the established
materials of construction for which average recoveries
have been determined, regardless of the compound recovered and the solvent employed (3). If a new material of
construction is introduced, an alternative to the specific
measurements above is to conduct recovery studies with
one to three different API and experimentally determine
into which recovery group the new material of construction falls.
CONCLUSIONS
Material of construction is a factor in recovery of residue
for cleaning validation. More specifically, the ability of
the residue to permeate into the surface of the material
lowers recovery. Although the solubility of the residue
in the recovery solvent, the ability of the swab to recover
the residue, and the sampling technician swab technique
also contribute to recovery data, these factors have been
standardized to demonstrate recoveries of >75% for many
materials of construction.
The use of new materials of construction for pharmaceutical manufacturing should be evaluated on an individual
basis to determine the ability to recover pharmaceutical
residue from its surface. Materials of construction coupons
used in laboratory studies to determine recovery data must
be exact replicas of materials used to fabricate equipment.
The data of this paper demonstrated that all Neoprene was
not the same—there were significant recovery differences
between “smooth” and “rough” Neoprene. High surface
roughness materials as exemplified by rough Neoprene
had the lowest % recovery data. Materials of construction
that exhibit low recovery should be replaced wherever
practical. Replacement materials should be evaluated to
ensure a higher recovery of the API of interest to avoid
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Journal
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any potential cross-contamination due to slow release of
residue from the material of construction. If replacement is
not possible, equipment should be dedicated or restricted
for use to the API that had low recovery.
REFERENCES
1.FDA, Guide to Inspection of Validation of Cleaning Processes,
Division of Field Investigations, Office of Regional Operations, Office of Regulatory Affairs, Washington, D.C. July
1993.
2.R. J. Forsyth and D. Haynes, “Cleaning Validation in a Pharmaceutical Research Facility,” Pharm. Technol. 22 (9), 104
– 112, 1998.
3.R. J. Forsyth, J. C. O’Neill, and Jeffrey L. Hartman, “Cleaning
Validation: Grouping Materials of Construction Based on
Recovery Data,” Pharm. Technol., 31 (9), 104 – 112, 2007).
4.G. M. Chudzik, “General Guide to Recovery Studies Using
Swab Sampling Methods for Cleaning Validation,” J. Val.
Technol., 5 (1), 77 – 81, 1999.
5.R. Sharnez, J. Lathia, et al., “In Situ Monitoring of Soil Dissolution Dynamics: A Rapid and Simple Method for Determining Worst-case Soils for Cleaning Validation,” PDA J
Pharm. Sci. and Technol, 58 (4), Jul-Aug 2004.
6.F. Riedewald, “Bacterial Adhesion to Surfaces: the Influence
of Surface Roughness,” PDA J Pharm. Sci. and Technol, 60 (3)
164 – 171, May-June 2006.
7. V. Sokol, I. Vrublevsky, et al., “Investigation of Mechanical Properties of anodized Aluminum using Dilatometric
Measurements,” Anal. Bioanal. Chem. 375 968 – 973, March
2003.
8.E. S. Koolj, H. Wormeester, et al., “Optical Anistropy and
Porosity of Anodic Aluminum Oxide Characterized by
Spectroscopic Ellipsometry,” Electrochem.Solid-State Lett. 6
(11) B52 – B54, 2003. JVT
ARTICLE ACRONYM LISTING
API
Active Pharmaceutical Ingredient
ARL
Acceptable Residue Limit
CIPClean-in-Place
HPLC High Performance Liquid Chromatography
RF
Recovery Factor
USP
United States Pharmacopeia
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