A substructure-based screening approach to uncover N-nitrosamines in drug substances

Authors

Yu-Ting Kao, School of Pharmacy, National Defense Medical Center, Taipei City, Taiwan, Republic of China
Shu-Fen Wang, Pharmaceutical Plant of Controlled Drugs, Food and Drug Adiministration, New Taipei City, Republic of China
Meng-Hsiu Wu, Pharmaceutical Plant of Controlled Drugs, Food and Drug Adiministration, New Taipei City, Republic of China
Shwu-Huey Her, Pharmaceutical Plant of Controlled Drugs, Food and Drug Adiministration, New Taipei City, Republic of China
Yi-Hsuan Yang, Pharmaceutical Plant of Controlled Drugs, Food and Drug Adiministration, New Taipei City, Republic of China
Chung-Hsien Lee, Taiwan Product Quality Research Institute, Taipei City, Taiwan, Republic of China
Hsiao-Feng Lee, Taiwan Product Quality Research Institute, Taipei City, Taiwan, Republic of China
An-Rong Lee, School of Pharmacy, National Defense Medical Center, Taipei City, Taiwan, Republic of China
Li-Chien Chang, School of Pharmacy, National Defense Medical Center, Taipei City, Taiwan, Republic of ChinaFollow
Li-Heng Pao, Taiwan Product Quality Research Institute, Taipei City, Taiwan, Republic of ChinaFollow

Keywords

cheminformatics, data mining, nitrosamines, risk assessment, total quality management

Abstract

Drug substances are at risk of contamination with N-nitrosamines (NAs), well-known carcinogenic agents, during synthesis processes and/or long-term storage. Therefore, in this study, we developed an efficient data-based screening approach to systemically assess marketed products and investigated its scalability for benefiting both regulatory agencies and pharmaceutical industries. A substructure-based screening method employing DataWarrior, an open-source software, was established to evaluate the risks of NA impurities in drug substances. Eight NA substructures containing susceptible amino sources for N-nitrosation have been identified as screening targets: dimethylamine (DMA), diethylamine, isopropylethylamine, diisopropylamine, N-methyl-2-pyrrolidone, dibutylamine, methylphenylamine, and tetrazoles. Our method detected 192 drug substances with a theoretical possibility of NA impurity, 141 of which had not been reported previously. In addition, the DMA moiety was significantly dominant among the eight NA substructures. The results were validated using data from the literature, and a high detection sensitivity of 0.944 was demonstrated. Furthermore, our approach has the advantage of scalability, owing to which 31 additional drugs with suspected NA-contaminated substructures were identified using the substructures of 1-methyl-4-piperazine in rifampin and 1-cyclopentyl-4-piperazine in rifapentine. In conclusion, the reported substructure-based approach provides an effective and scalable method for the screening and investigation of NA impurities in various pharmaceuticals and might be used as an ancillary technique in the field of pharmaceutical quality control for risk assessments of potential NA impurities.

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Recommended Citation

Kao, Yu-Ting; Wang, Shu-Fen; Wu, Meng-Hsiu; Her, Shwu-Huey; Yang, Yi-Hsuan; Lee, Chung-Hsien; Lee, Hsiao-Feng; Lee, An-Rong; Chang, Li-Chien; and Pao, Li-Heng (2022) "A substructure-based screening approach to uncover N-nitrosamines in drug substances," Journal of Food and Drug Analysis: Vol. 30 : Iss. 1 , Article 12.
Available at: https://doi.org/10.38212/2224-6614.3400

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