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Due to the toxicity of polychlorinated dibenzo- p-dioxins and polychlorinated dibenzofurans (PCDD/F), efforts are made to quantify their emission into the environment. Typically, this quantification is done using gas chromatography-high-resolution mass spectrometry (GC-HRMS). However, GC-HRMS is extremely expensive and time consuming, and GC-HRMS facilities are overly requested. In order to decrease the workload on GC-HRMS, another alternative is to use an enzyme-linked immunosorbent assay (ELISA) as a semi-quantitative screening tool. One problem of this solution is that ELISA measures the total PCDD/F content of a sample differently than GC-HRMS; a disparity exists between the two techniques. This paper introduces a congener correction factor that adjusts ELISA results for this incompatibility. The importance of the correction factor is explored by examining the congener profiles of 27 different dioxin sources. The congener profiles for many of these sources are such that large incompatibilities in predicted PCDD/F content would likely exist between uncorrected ELISA and GC-HRMS. The effect that the correction factor has on the correlation between ELISA and GC-HRMS for samples from a test site with dioxin-contaminated soils was also examined. The congener profile at this site was such that the inconsistencies between uncorrected ELISA and GC-HRMS results were relatively small. However, application of the congener correction factor still improved the correlation between ELISA and GC-HRMS by 11% when using sample-specific correction factors and by 5% when using an average site-wide correction factor. The findings of this paper suggest that application of the correction factor is necessary to remove incompatibilities between ELISA and GC-HRMS-particularly when the congener profile at a site would lead to incompatibilities that are large. [Figure not available: see fulltext.] [ABSTRACT FROM AUTHOR]

The “Pharmaceutical Current Good Manufacturing Practices (CGMPs) for the 21st Century—A Risk Based Approach” initiative announced by the FDA in August 2002 to improve and modernize pharmaceutical manufacturing facilitated adoption of process analytical technology (PAT) by the pharmaceutical industry. The potential for improved operational control and compliance resulting from continuous real-time quality assurance was highlighted as a likely benefit that would result from PAT implementation. A considerable amount of work has been done on this topic by academic and industrial contributors in the last decade. In this paper, we will start with a brief overview of evolution of PAT concepts and a review of their application in the wider pharmaceutical industry. The rest of the paper focuses on PAT applications for biotech processes with emphasis on developments in the last five years. It is our observation that while significant advances have been accomplished with regard to our ability to analyze/monitor key process and quality attributes in the biotech industry, much more needs to be done with regard to utilizing the collected data for subsequent control of the process, to achieve optimum yield and product quality. The latter is necessary to achieve the benefits that will result from PAT implementation. [Figure not available: see fulltext.] [ABSTRACT FROM AUTHOR]