Beyond specification equivalence: A CMA-CQA framework for raw material change and lifecycle variability assessment

Raw material changes remain a frequent source of uncertainty, as specification equivalence does not necessarily ensure functional equivalence and the impact of material variability on a specific formulation-process system may be difficult to predict. Regulatory frameworks (ICH Q8-Q10) require risk assessments to be grounded in scientific understanding of how material attributes influence process performance and critical quality attributes (CQAs), yet practical approaches to systematically translate this understanding into change risk remain limited. This work introduces a critical material attribute (CMA)-critical quality attribute (CQA) framework for raw material change assessment integrating three independent dimensions: (i) strength of linkage between material attributes and process/product responses, (ii) magnitude of change in the material attributes (Δ), and (iii) intrinsic drug product process sensitivity. These dimensions are combined in a structured, semi-quantitative matrix that identifies where variability is introduced, where the system is sensitive, and where the process cannot absorb variation. The approach moves beyond static specification comparison by explicitly evaluating propagation pathways through which variability translates into impact. Application across representative case scenarios demonstrates that risk is not an intrinsic material property, but emerges from interaction with a specific formulation-process system. Subtle shifts in attributes can drive significant effects in capability-limited systems, whereas substantial compositional differences may remain inconsequential in robust processes. The framework also highlights the role of supplier-related variability and non-compendial attributes, reinforcing that equivalent specifications can mask meaningful functional differences. Overall, the proposed approach provides a structured basis for discriminating material change risk, prioritizing experimental effort, and guiding change control strategies in line with regulatory expectations. It supports a shift from specification-driven decisions to system-level risk evaluation. Beyond discrete material change events, the framework enables lifecycle-based management of raw material variability, including inherent system variability (e.g. inter- and intra-supplier, lot-to-lot), progressively refined through continued process verification.