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Cleaning Validation: Factors Affecting Recovery Data and Material of Construction GroupingRichard J. Forsyth

ABSTRACTMaterial of construction is a factor in recovery of resi-due for cleaning validation. Analysis of existing recov-ery 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 recov-ery 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.

INTRODUCTIONResidue assays are a critical requirement in establish-ing a validated cleaning program. They are essential to accurately determine amounts of residual active phar-maceutical 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).

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 clean-ing 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 manu-facturing 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-

ABOUT THE AUTHORRichard Forsyth is a pharmaceutical consultant with a background in cleaning validation and analytical chemistry. He may be reached by e-mail at mr.rich.forsyth@gmail.com.

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ery performance. This resulted in five distinct group-ings with statistically different recovery levels. These groupings, however, could not be correlated to mate-rial 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 clean-ing 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 character-istics of the materials and parameters that influence recov-ery 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 antici-pated 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 suf-ficient 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

adequately controlled to minimize subjectivity and should consistently recover enough residue so that a pre-cise 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 construc-tion provided no correlation with the recovery data, the physical properties of the materials could affect recover-ies. 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 ana-lyze 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 construc-tion was achieved.

EXPERIMENTALThe 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 compari-son 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 formula-tions 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 pre-weighed 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 10-

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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 represen-tative 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. Stain-less steel coupons machined to different roughness factors provided data. A Surtonic Duo surface finish analysis instrument (Taylor-Hobson, ID C-5524) was used to mea-sure 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 chro-matography (HPLC) method specific for the API and an average recovery factor was determined.

RESULTS AND DISCUSSIONResults are discussed for API aqueous solubility and recov-ery; 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

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, recov-ery 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 vari-ability 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 fac-tor (RF) means for each material and product, while only 3% additional variance was attributable to the swab, sol-vent, and technique factors across sites. This meant that

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

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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 rela-tionship 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 dem-onstrates 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

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 corre-lation 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 stain-less 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 stain-less steel and the smooth neoprene were equivalent.

Surface Roughness Table V provides recovery data from different surface rough-ness 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 specifi-

Table II: Cleanability and recovery data comparison.

Compound Recovery Water solubility

Cleanability

Water CIP 100 CIP 300

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

Table lines are tinted down to 30% (like past issues).

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cally machined for these experiments. The glass, brass, polytetrafluoroethylene (PTFE), and smooth Neoprene, which were comparatively smooth, had recovery num-bers 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 mate-rial as soon as it was spotted. A background check of the aluminum sample revealed that it was anodized alumi-num, 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. Understand-ing 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 con-struction, 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.

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 pro-portion of fillers will also affect the transport properties. The longer period of time a material is exposed to a com-pound, 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

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

Table lines are tinted down to 30% (like past issues).

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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. Com-plex 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 rela-tive 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 recov-ered 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 construc-tion falls.

CONCLUSIONSMaterial 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 pharmaceu-tical 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

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.

REFERENCES1. FDA, Guide to Inspection of Validation of Cleaning Processes,

Division of Field Investigations, Office of Regional Opera-tions, Office of Regulatory Affairs, Washington, D.C. July 1993.

2. R. J. Forsyth and D. Haynes, “Cleaning Validation in a Phar-maceutical 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 Dis-solution Dynamics: A Rapid and Simple Method for De-termining 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 Mechani-cal 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 LISTINGAPI Active Pharmaceutical IngredientARL Acceptable Residue LimitCIP Clean-in-PlaceHPLC High Performance Liquid ChromatographyRF Recovery FactorUSP United States Pharmacopeia

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