Autonomous Carcinogenic Potency Categorization Approach for Nitrosamine Drug Substance-related Impurities

Nitrosamine drug substance-related impurities (NDSRIs), which are compounds that can form during certain drug manufacturing processes and have been shown to cause cancer, assessing and mitigating their formation has become an important public health issue as evidenced by recent guidelines from health authorities like the FDA and EMA that provide acceptable intake limits for various N-nitrosamines. We have developed a web-based application that can autonomously analyze the N-nitrosamine risk category of compounds from their SMILES notation, providing instant screening to identify high-risk formations of N-nitrosamines. The accuracy of the tool was validated using an FDA dataset of compounds with known N-nitrosamine risks, as this algorithm rapidly and accurately categorized over 6000 chemicals' risks and comparison to the dataset labels showed high agreement, indicating it can quickly and reliably analyze large datasets. Further analysis revealing high parent amine pKaH correlates to low N-nitrosamine risk and more correlations with other descriptors is being discussed. Overall, the application integrates computational and regulatory knowledge to advance both environmental and human health priorities.