(27f) Analytical Qualification of Complex Media Raw Materials Using Multivariate Analysis Conference: AIChE Annual MeetingYear: 2010Proceeding: 2010 AIChE Annual MeetingGroup: Food, Pharmaceutical & Bioengineering DivisionSession: Industrial Forum: Recent Advances and Development in Biotech Industry Time: Monday, November 8, 2010 - 10:35am-11:00am Authors: Sterman, M. D., Abbott Laboratories In this study, multivariate analysis of complex raw material compositional data is used to identify distinctions among raw material lots and derive performance predictions. Cell Culture media frequently includes complex components, such as protein hydrolysates. These complex components are critical, but at times inconsistent, contributors to process performance. Specifically, lot to lot variability of complex components has been shown to affect cell culture productivity and product quality. Furthermore, raw material variability and its cell culture effect may be unique for each incoming lot. As a result, analysis designed to detect past problems may not be relevant to new lots. Combining metabolomic data with more traditional chemical analysis casts a wide net around the lot variability dilemma. However, one variable at a time analysis of large data sets is time consuming, and may not elucidate data groupings or inconsistencies. Multivariate analysis is a methodology for extracting meaningful information from large amounts of raw data.