Figueroa Navedo, Amanda M.

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    Cleaning validation applications using Mid-Infrared quantum cascade laser spectroscopy
    (2017) Figueroa Navedo, Amanda M.; Hernández Rivera, Samuel P.; College of Arts and Sciences - Sciences; Mina Camilde, Nairmen; Romañach Suárez, Rodolfo J.; Department of Chemistry; López del Puerto, Carla
    According to the Recall Root Cause Research (RRCR), an initiative governed by the U.S. Food and Drug Administration (FDA), the contamination of pharmaceutical products is an alarming cause of public concern. During 2015, four hundred and fifty reported recalls were listed for: foods, drugs, pet medicine, biological products, medical devices, cosmetics, and tobacco. Therefore, the importance of developing a quantification method for cleanliness validation of manufacturing devices and vessels using direct and indirect surface sampling is presented. The proposed methodology was established to detect the presence residues of chemicals left as residues after cleaning of surfaces a result of manufacturing processes as well as foraneous microorganisms in the form of biofilms. These contaminants have been detected in real manufacturing substrates with mid-infrared (MIR) spectroscopy. A quantum cascade laser (QCL) aimed at various substrates containing the target residues was employed for developing methodologies for cleaning validation purposes. Stainless steel, TeflonTM and swabs are real substrates that were considered for direct transition of the methodology into a manufacturing environment. The adsorbate residues selected included over-the-counter active ingredients (OTC-AI), microorganisms, detergents and mixtures of these to simulate substrates contamination. This work was directed to assess constraints experienced in process analytical technology at-line or in-line using spectroscopic tools coupled with chemometric statistical methods. Quantitative and qualitative analysis of four microorganisms were evaluated: Bacillus subtilis, Burkholderia cepacia, Staphylococcus aureus, Pseudomonas aeruginosa and Escherichia coli. Detection limits and quantification limits, before and after chemometric analysis, were calculated for Bacillus subtilis and Burkholderia cepacia. A significant improvement was found with chemometric analysis with a detection limit of 7 and 13 CFU/mL for Burkholderia cepacia and Bacillus subtilis, respectively. The results compare very well to many techniques to quantify microorganisms, including polymerase chain reaction analysis, with quantification limit values of 45 and 20 CFU/mL for Burkholderia cepacia and Bacillus subtilis, respectively.