In the development of pharmaceutical agents the use of highly reactive reagents, though beneficial in synthesis, also results in an increased probability of the reagents leading to mutagenicity if they persist as an impurity. Controlling these potentially mutagenic impurities (PMIs) is a critical part of the development of any pharmaceutical product. The ICH M7 guidance outlines a series of control options that are aligned with risk-based principles. One control strategy, proposed by Teasdale et al, is explicitly referenced in ICH M7 and allows for the application of scientific understanding of the physicochemical properties of a PMI and the processes involved to justify its removal via a semi-quantitative scoring system. The approach relies on the expert knowledge of the risk assessor, however the approach can be further enhanced by the application of a standardised in silico system, namely Mirabilis, and the adherence to a consortium-driven framework. The Mirabilis software has been developed as a standardised in silico tool for the prediction of purge factors of impurities according to the Teasdale approach, led by a cross-industry consortium. Herein we present a theoretical case study to highlight the process involved when performing a risk assessment aligned to control option 4 for regulatory disclosure using Mirabilis. When performed ahead of other control options, the approach can facilitate the identification and subsequent solution to problems associated with quantification of PMI levels in the final product.

Application of an in silico tool for the risk assessment of an industrial process compliant to ICH M7 guidelines

256th National Meeting (2018)

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