PT - JOURNAL ARTICLE AU - Bert Gunter AU - Daniel Coleman AU - Aaron Goerke AU - Theodoro Koulis AU - Jens Lamerz AU - Yiming Peng TI - A Risk Index and Data Display for Process Performance in the Pharmaceutical Industry AID - 10.5731/pdajpst.2017.008177 DP - 2017 Jan 01 TA - PDA Journal of Pharmaceutical Science and Technology PG - pdajpst.2017.008177 4099 - http://journal.pda.org/content/early/2017/12/13/pdajpst.2017.008177.short 4100 - http://journal.pda.org/content/early/2017/12/13/pdajpst.2017.008177.full AB - 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.