Development of the Methodology for in Silico Reactivity-Based Purge Predictions: Making Mirabilis Think Like a Chemist

Abstract

Synthetic routes to drug substances can result in the introduction of potentially mutagenic impurities (PMIs). The ICH M7 guideline offers a range of control options that assures that the level of this impurity in the drug substance and drug product is below the acceptable limit. Control option 4 leverages the use of predicted purge and outlines the method of utilizing chemical knowledge, literature evidence, and process knowledge to predict the purge of a PMI during drug substance synthesis. If the predicted levels of an impurity in the API are sufficiently lower than the acceptable limit, there will be no requirement for routine analytical testing. Mirabilis is an in silico tool that offers a standardized and conservative approach for the purge calculation of PMIs. The recent developments to methodology for assessing reactivity-based purges within Mirabilis aim to make predictions in a manner more consistent with how a chemist would assess the same situation. The condition-based approach considers the reactants and reagents present and how they may interact, bringing about significant improvements to the specificity and applicability of predictions versus the previous transformation-based approach. Purge predictions for reactivity are now available for 30 impurity types, including N-nitroso compounds and secondary aliphatic amines. Three case studies demonstrate how the new approach provides purge calculations that better align with expert users due to the increased specificity of the predictions.