Nitrosamine Contamination in Pharmaceuticals: Regulatory Perspectives and Control Strategies of USFDA, EMA & HC
Bibliographic record
Abstract
Various regulatory authorities were notified the presence of nitrosamine impurities in human medicines including angiotensin II receptor blockers (ARBs), ranitidine, nizatidine and metformin in 2018. The presence of nitrosamines led manufacturers to assessed their products by any means that might inadvertently lead to nitrosamine content and taking steps to mitigate these risks after issuance of safety alerts, recall and withdraw certain batches of these drugs. Importantly, global cooperation by regulatory authorities triggered the investigation of synthetic route, rapid development of analytical procedures and publication of guidelines. This article highlights mainly on risk assessment and control strategies adopted by United States Food and Drug Administration (USFDA) and the European Medicines Agency (EMA), and Health Canada (HC) regulatory bodies. Additionally, compare the acceptable intake (AI) values recommended by these regulatory authorities which will help the manufacturer to either limit or eliminate nitrosamines impurities in their medicines because nitrosamines are probable or possible human carcinogens, hence, it is recommended that the potential causes of nitrosamine formation as well as any other pathways observed and evaluate the risk for nitrosamine contamination or formation in their APIs and drug products. Manufacturers should prioritize evaluation of APIs and drug products based on factors such as maximum daily dose, duration of treatment, therapeutic indication, and number of patients treated for the products which are under pre approval stage and already marketed products. Conclusion: As nitrosamine contamination affects patients worldwide, in case the levels of nitrosamines exceed acceptable limits, or more than one nitrosamine is observed, such products should not be commercialized. All the international regulatory agencies continuing to work with to propose various analytical methodologies to determining nitrosamine content in the API or FPP, risk assessment evaluation and control strategies, extrapolation of toxicological data and various confirmatory test for mutagenicity detection. Due to this rapid action taken by global authorities will help manufacturer to design their manufacturing process to be more robust so that they will timely register their products and reduce the additional cost require for its complete analysis by taking care of consumer’s safety as well.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".