PT - JOURNAL ARTICLE AU - Piet Christiaens AU - Jean-Marie Beusen AU - Philippe Verlinde AU - Jan Baeten AU - Dennis Jenke TI - Identifying and Mitigating Errors in Screening for Organic Extractables and Leachables: Part 2—Errors of Inexact Identification and Inaccurate Quantitation AID - 10.5731/pdajpst.2018.009779 DP - 2020 Jan 01 TA - PDA Journal of Pharmaceutical Science and Technology PG - 108--133 VI - 74 IP - 1 4099 - http://journal.pda.org/content/74/1/108.short 4100 - http://journal.pda.org/content/74/1/108.full SO - PDA J Pharm Sci Technol2020 Jan 01; 74 AB - Patients can be exposed to leachables derived from pharmaceutical manufacturing systems, packages, and/or medical devices during a clinical therapy. These leachables can adversely decrease the therapy's effectiveness and/or adversely impact patient safety. Thus, extracts or drug products are chromatographically screened to discover, identify, and quantify organic extractables or leachables. Although screening methods have achieved a high degree of technical and practical sophistication, they are not without issues in terms of accomplishing these three functions. In this Part 2 of our three-part series, errors of inexact identification and inaccurate quantitation are addressed. An error of inexact identification occurs when a screening method fails to produce an analyte response that can be used to secure the analyte's identity. The error may be that the response contains insufficient information to interpret, in which case the analyte cannot be identified or that the interpretation of the response produces an incorrect identity. In either case, proper use of an internal extractables and leachables database can decrease the frequency of encountering unidentifiable analytes and increase the confidence that identities that are secured are correct. Cases of identification errors are provided, illustrating the use of multidimensional analysis to increase confidence in procured identities. An error of inaccurate quantitation occurs when an analyte's concentration is estimated by correlating the responses of the analyte and an internal standard and arises because of response differences between analytes and internal standards. The use of a database containing relative response factors or relative response functions to secure more accurate analyte quantities is discussed and demonstrated.