A Risk-Management Approach to Cleaning-Assay Validation - Pharmaceutical Technology

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A Risk-Management Approach to Cleaning-Assay Validation
The authors recommend a strategy for classifying similar nonstainless-steel surfaces into three groups based upon the analytical recovery that was observed in this study.

Pharmaceutical Technology
Volume 6, Issue 34, pp. 48-55

Design of experiments

Several variables (i.e., roughness average, material of construction, active ingredient, and spiked amount) were evaluated in a randomized fashion to prevent systematic bias that could be introduced by going from the lowest to the highest acceptance limit, from the smoothest to the roughest surface, or from one material of construction to the next. The initial design of experiments included two active pharmaceutical ingredients (APIs), three spiked acceptance-limit levels (i.e., 0.5, 5.0, and 50 μg/swab), seven surface types, four target roughness averages (Ra < 25, 75, 125, and 150 μin.), and six replicates per surface. These Ras were targeted to evaluate whether surface recovery depended on the surface Ra. Coupons were divided into a group of polymers [i.e., Lexan (polycarbonate), acetal (Polyoxymethylene), and PTFE] and a group of metals (i.e., stainless steel 316L, bronze, Type III hard-anodized aluminum, and cast iron). These surfaces were chosen to represent a cross section of surfaces found in the CTM manufacturing and packaging areas and required 1008 swab determinations to complete the study. The remaining product-contact surfaces found in the clinical-trial manufacturing and packaging areas were evaluated according to the initial design of experiments. These surfaces included nickel, anodized aluminum, Rilsan (polyamide), Oilon (blended-oil nylon), and stainless steel 316L with a 4 4-in. area.

The authors chose two APIs for this evaluation on the basis of their solubility profiles to represent the most- and least-soluble compounds a company would likely manufacture. Compound A, the less soluble, is slightly soluble in methanol and insoluble across the pH range, but Compound B is soluble in all solvents. In addition, Eli Lilly (Indianapolis, IN) identified Compound A as one of the most difficult compounds to clean from equipment, based on its low solubility and staining properties. A control (i.e., stainless steel 316L, 0.5 μg/swab, Compound A) was run each day that data were generated.

Equipment and operating conditions

Table I: High-performance liquid chromatography (HPLC) operating conditions.
The authors used an Agilent 1100 high-performance liquid chromatography (HPLC) analyzer (Agilent, Santa Clara, CA) for all experiments. The HPLC operating conditions were validated according to ICH standards for precision, linearity, limit of detection (LOD), limit of quantitation (LOQ) and specificity (see Table I) (8). Precision was 1.85% and 3.13% for Compounds A and B, respectively, and was determined at 0.025 μg/mL (i.e., 25% of the lowest spike). The method was linear across the equivalent range of 0.5 μg/swab to 5 μg/swab (R = 0.999). The LOQ was calculated to be 0.005 μg/mL for Compound A and 0.008 μg/mL for Compound B. The LOD was calculated to be 0.001 μg/mL for Compound A and 0.0024 μg/mL for Compound B. Swabs and solvents did not result in interfering peaks. The authors performed swabbing consistently using Texwipe Alpha large swabs (ITW Texwipe, Kernersville, NC). First, 10 vertical swipes, then 10 horizontal swipes were performed for the 2 2-in. surfaces. For the 4 4-in. surfaces, 20 swipes were executed in each direction. Methanol was used as the swabbing solvent. Spike amounts were 0.5, 5, and 50 μg per surface and were extracted into 5 mL of mobile phase, which corresponded to 0.1-, 1.0-, and 10-μg/mL standard concentrations, respectively. The authors used a Quanta FEG 200F field-emission scanning electron microscope (SEM, FEI, Hillsboro, OR) to generate the surface images.


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