Grazing-Angle Fiber-Optic Fourier Transform Infrared Reflection−Absorption Spectroscopy for the in Situ Detection and Quantification of Two Active Pharmaceutical Ingredients on Glass

Estimation of the Number of Scans Required per Hard-to-Clean Location and Establishing the Limit of Quantification of a Partial Least Squares Calibration Model When the FTIR Is Used for Pharmaceutical Cleaning Verification

This study aims to identify two critical components required for pharmaceutical cleaning verification when an FTIR is used: (a) the number of scans required per hard-to-clean location, and (b) the limit of quantification (LOQ) of the FTIR instrument when measuring the surface contamination. The current practice in pharmaceutical manufacturing does not require multiple samples as it is standard practice to collect a single swab sample from a 25 × 25 cm area from a difficult-to-reach area of the manufacturing equipment. However, since the FTIR will only scan a tiny portion of the surface compared to the swab, a sufficient number of samples (data points) are required to provide enough confidence to ensure that the measurement results are close to the true value with a maximum degree of certainty. Similarly, calculating the LOQ for a linear regression could be straightforward. However, complexity arises when the experimental data are complex; in this case, the complexity arises due to the nature of the measurement and the lack of the defined peak in the pre-processed spectra. Therefore, this study uses the practical approach of calculating the sample size and the LOQ.

Investigation of an alternative approach for real-time cleaning verification in the pharmaceutical industry

Within the pharmaceutical industry, it is a regulatory requirement to ensure that pharmaceutical drug manufacturing equipment is clean prior to use. Cleaning processes of manufacturing equipment are performed using a "validated" process and subsequently verified since inadequate cleaning can result in a contaminated or adulterated product. Historically, cleanliness of equipment within Drug Substance/Product/Active Pharmaceutical Ingredient (API) manufacturing is validated and verified using direct swabbing of the equipment and subsequent analytical testing of the swab extract. In this study, a novel approach has been evaluated using a number of innovative technologies and techniques to develop and validate a methodology based on an in situ hand-held Process Analytical Technology (PAT) to verify manufacturing equipment cleanliness and eliminate swabbing and associated off-line laboratory testing. Specular reflectance Mid Infrared (Mid-IR) spectroscopy was used to detect and quantify surface residue. It is expected that this analytical technique will allow the elimination or reduction of the number of swabs and subsequent off-line analytical testing required during cleaning verification of manufacturing equipment in the pharmaceutical and biopharmaceutical industry. This study was focused on the development and validation of a Mid-IR based calibration model. The results indicate that surface a residue of 0.19 μg cm-2 for a specific molecule is detectable using a specular reflectance Mid-IR technique.

Fiber-optic infrared reflection absorption spectroscopy for trace analysis on surfaces of varying roughness. Part II: Acetaminophen on stainless steel

Investigations of the effects of surface roughness on the utility of grazing-angle Fourier transform infrared reflection absorption spectroscopy (IRRAS) as a method for quantifying trace contamination of metal surfaces have been extended to acetaminophen, a model active pharmaceutical agent, on 316 stainless steel. The effects are more complicated than for the surfactant sodium dodecyl sulfate (SDS) on stainless steel; they include a strong surface-finish dependence of sensitivity and nonlinear behavior at surface loadings above approximately 1-2 microg cm(-2). Using data from samples in the loading range 0-0.5 microg cm(-2), unbiased partial least squared calibrations can be readily achieved for individual surface finishes with detection limits of L(D) approximately 0.15 microg cm(-2). However, as found for SDS on stainless steel, models built using data from samples of mixed surface roughness are more problematic.