Determining recommended acceptable intake limits for N-nitrosamine impurities in pharmaceuticals: Development and application of the Carcinogenic Potency Categorization Approach (CPCA)
Naomi L. Kruhlak, Marianne Schmidt, Roland Froetschl, Stefan Gräber, Bodo Haas, Irene Horne, Stephen Horne, Sruthi Tallapragada King, Iryna A. Koval, Govindaraj Kumaran, Anja Langenkamp, Timothy J. McGovern, Tyler Peryea, Alan Sanh, Aline Siqueira Ferreira, Leon van Aerts, Alisa Vespa, Rhys Whomsley
Abstract
N-Nitrosamine impurities, including nitrosamine drug substance-related impurities (NDSRIs), have challenged pharmaceutical industry and regulators alike and affected the global drug supply over the past 5 years. Nitrosamines are a class of known carcinogens, but NDSRIs have posed additional challenges as many lack empirical data to establish acceptable intake (AI) limits. Read-across analysis from surrogates has been used to identify AI limits in some cases; however, this approach is limited by the availability of robustly-tested surrogates matching the structural features of NDSRIs, which usually contain a diverse array of functional groups. Furthermore, the absence of a surrogate has resulted in conservative AI limits in some cases, posing practical challenges for impurity control. Therefore, a new framework for determining recommended AI limits was urgently needed. Here, the Carcinogenic Potency Categorization Approach (CPCA) and its supporting scientific rationale are presented. The CPCA is a rapidly-applied structure-activity relationship-based method that assigns a nitrosamine to 1 of 5 categories, each with a corresponding AI limit, reflecting predicted carcinogenic potency. The CPCA considers the number and distribution of α-hydrogens at the N-nitroso center and other activating and deactivating structural features of a nitrosamine that affect the α-hydroxylation metabolic activation pathway of carcinogenesis. The CPCA has been adopted internationally by several drug regulatory authorities as a simplified approach and a starting point to determine recommended AI limits for nitrosamines without the need for compound-specific empirical data.