Poor Indoor Air Quality, Mold Exposure, and Upper Respiratory Tract Infections--Are We Placing Our Children at Risk?

Understanding how respiratory health risks are associated with poor housing is essential to designing effective strategies to improve children's quality of life. The objective of the study described in this article was to determine the relationship between respiratory health and housing conditions. A survey was completed by 3,424 parents of children in third and fourth grade in Winnipeg, Manitoba, Canada. An engineering audit and air samples were also taken in the homes of a subset of 715 homes. Results showed that a child's respiratory health is significantly associated with self-reported visible mold in the home and that a significant association existed between occupant-reported visible mold and tested airborne mold. Findings highlight the need for clearer standards of acceptable CFU/m3 limits for mold genera that are applicable to homes. In the absence of such guidelines, problems associated with indoor mold will continue to impact the health of residents, despite growing evidence of the adverse effects from mold exposure.

A Risk Index and Data Display for Process Performance in the Pharmaceutical Industry.

We propose a new index and graphical display for quantifying and visualizing process performance in the pharmaceutical industry. These tools can provide management a comprehensive, high level overview of the process performance of a global manufacturing network suitable for risk ranking, by which is meant: identifying those processes at greatest risk of failing to meet specifications, and prioritizing resources to drive continuous process improvement. Our index, like others currently in use, compares the observed variation of CQAs-critical quality attributes-to their specifications. However, instead of relying on traditional data summaries such as means and standard deviations to characterize process results, the proposed index uses sample quantiles. Quantiles are more accurate and reliable when data are skewed or short-tailed as is often observed for pharmaceutical processes. Perhaps just as important, we communicate the results with a new visual display that accurately compares processes and sites. The display identifies instances when the summaries may mislead and the subject matter expert needs to "drill down" into manufacturing data to assure correct understanding.LAY ABSTRACT: The proposed risk index and graphical display enables high-risk processes to be identified, process improvements to be prioritized, resources to be efficiently allocated, and strategic planning for continuous process improvement to be evidence-based.

Statistical characterization of therapeutic protein modifications.

Peptide mapping with liquid chromatography-tandem mass spectrometry (LC-MS/MS) is an important analytical method for characterization of post-translational and chemical modifications in therapeutic proteins. Despite its importance, there is currently no consensus on the statistical analysis of the resulting data. In this manuscript, we distinguish three statistical goals for therapeutic protein characterization: (1) estimation of site occupancy of modifications in one condition, (2) detection of differential site occupancy between conditions, and (3) estimation of combined site occupancy across multiple modification sites. We propose an approach, which addresses these goals in terms of summarizing the quantitative information from the mass spectra, statistical modeling, and model-based analysis of LC-MS/MS data. We illustrate the approach using an LC-MS/MS experiment from an antibody-drug conjugate and its monoclonal antibody intermediate. The performance was compared to a 'naïve' data analysis approach, by using computer simulation, evaluation of differential site occupancy in positive and negative controls, and comparisons of estimated site occupancy with orthogonal experimental measurements of N-linked glycoforms and total oxidation. The results demonstrated the importance of replicated studies of protein characterization, and of appropriate statistical modeling, for reproducible, accurate and efficient site occupancy estimation and differential analysis.