If your Drug Manufacturing Process involves the use of highly reactive reagents, their reactivity can lead to the formation of mutagenic process impurities, if they are not removed efficiently. We can support the assessment efficient removal of such material using computer-assisted tools. The tool can be used for de-risking the formation of Nitrosamine.
The M7 guideline defines the approach for the control strategy of process-related impurities and also recommends understanding the process parameter and impact on residual impurities. This includes fate and purge with sufficient confidence that the level of impurity in the final drug substance will be below the acceptable level so that analytical testing is not required. Likewise, the FDA guidance document recommends a similar mitigation strategy for the presence of nitrosamine impurities in API.
The fate and purge assessments involve applying an understanding of the physicochemical properties of an impurity in relation to the reaction and subsequent purification conditions it is exposed to.
A computer-assisted tool allows for a rapid, reproducible semi-quantitative measure of this risk assessment for mutagenic impurities, including Nitrosamine.
Computational Toxicology Evaluation of Impurity Services
We offer services on Computational Toxicology evaluation in line with the requirements of ICH M7 guidelines – (structure-based assessments).
We only need the structure of the impurities to perform the assessment and the report generated will be acceptable to USFDA as well as other regulatory agencies across the world.
Contact us for services on Genotoxic Impurities and Nitrosamine Assessment
Please submit our contact form if you are interested in availing such services. Our experienced scientists will handle your project requirements. You can reach them directly via phone or email to get further details and clarification on these services.
Computational Toxicology Assessment to fulfill the requirement of ICH M7
The ICH M7 guideline provides the internationally harmonized framework for the identification, classification, and control of mutagenic impurities (DNA reactive substances).
To fulfill the requirement of the guideline, structure-based assessments are useful for predicting bacterial mutagenicity.
ICH M7 provides a classification of mutagenic impurities as follows:
- Class 1: Known mutagenic carcinogens.
- Class 2: Known mutagens with unknown carcinogenic potential (bacterial mutagenicity positive, no rodent carcinogenicity data).
- Class 3: Alerting structure, unrelated to the structure of the drug substance; no mutagenicity data.
- Class 4: Alerting structure, same alert in drug substance or compounds related to the drug substance (e.g., process intermediates) which have been tested and are non-mutagenic.
- Class 5: No structural alerts, or alerting structure with sufficient data to demonstrate lack of mutagenicity or carcinogenicity.
The guideline outlines how a hazard assessment should be performed for the assignment of each impurity to one of five classes. If data for such a classification is not available, an assessment of Structure-Activity Relationships (SAR), that focuses on bacterial mutagenicity predictions, should be performed.
A computational toxicology assessment should be performed using (Q)SAR methodologies that predict the outcome of a bacterial mutagenicity assay.
Below is the process flow for performing an assessment.
The approach of pharmaceutical companies to assess the mutagenicity of impurities
Assessments are typically performed in drug substances for impurities at levels above 0.05% weight/ weight (reporting threshold) or relative peak area using standard detection techniques (ICH Q3A). Both, actual and potential impurities should be considered for evaluation. Recommended threshold levels of mutagenic impurities are determined based on daily intake and dose duration.
VEEPRHO has extended its support.
With our service, you can:
- Ensure the appropriate classification of Genotoxic and Non-Genotoxic Impurities.
- Avoid Regulatory Observations on Specification Limits of Impurities
