TY - JOUR T1 - Identifying and Mitigating Errors in Screening for Organic Extractables and Leachables: Part I; Introduction to Errors in Chromatographic Screening for Organic Extractables & Leachables and Discussion of the Error of Omission JF - PDA Journal of Pharmaceutical Science and Technology JO - PDA J Pharm Sci Technol DO - 10.5731/pdajpst.2018.009761 SP - pdajpst.2018.009761 AU - Dennis Jenke AU - Piet Christiaens AU - Jean-Marie Beusen AU - Phillipe Verlinde AU - Jan Baeten Y1 - 2019/01/01 UR - http://journal.pda.org/content/early/2019/06/03/pdajpst.2018.009761.abstract N2 - Substances leached from materials used in pharmaceutical manufacturing systems, packages and /or medical devices can be administered to a patient as part of a clinical therapy. These leachables can have an undesirable effect on the effectiveness of the therapy and/or patient safety. Thus, relevant samples such as material extracts or drug products are chromatographically screened for foreign organic impurities, where screening is the analytical process of discovering, identifying and quantifying these unspecified foreign impurities. Although screening methods for organic extractables and leachables have achieved a high degree of technical and practical sophistication, they are not without issues with respect to their ability to accomplish these three functions. In this first part of a series of three manuscripts, the process of screening is examined, limitations in screening are identified and the concept of using an internally-developed analytical database to identify, mitigate or correct these errors is introduced. Furthermore, errors of omission are described, where an error of omission occurs when a screening method fails to produce a recognizable response to an analyte present in the test sample. The error may be that no response is produced (″falling through the cracks″) or that a produced response is not recognizable (″failing to see the tree for the forest″). In either case, proper use of a robust internal extractables/leachables data database can decrease the frequency with which errors of omission occur. Examples of omission errors, their causes and their possible resolution are discussed. ER -