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A Rational Hierarchy to Capture Raw Material Attribute Variability in the Pharmaceutical Drug Product Development and
Stephen L Conway1, Kenneth J Rosenberg2, Sutthilug Sotthivirat3
1Center for Materials Science and Engineering, MMD, Merck & Co., Inc., Rahway, NJ, USA; Current affiliation Packaging Commercialization, MMD Merck & Co., Inc., Rahway, NJ, USA.
Abstract:
Assessing the robustness of a drug product formulation and manufacturing process to variations in raw material (RM) properties is an essential aspect of pharmaceutical product development. Motivated by the need to demonstrate understanding of attribute-performance relationships at the time of new product registration and for subsequent process maintenance, we review practices to explore RM variations. We describe limitations that can arise when active ingredients and excipients invariably undergo changes during a drug product lifecycle. Historical approaches, such as Quality-by-Design (QbD) experiments, are useful for initial evaluations but can be inefficient and cumbersome to maintain once commercial manufacturing commences. The relatively miniscule data sets accessible in product development - used to predict response to a hypothetical risk of variation - become less relevant as real-world experience of actual variability in the commercial landscape grows. Based on our observations of development and manufacturing, we instead propose a holistic framework exploiting a hierarchy of RM variability, and challenge this with common failure modes. By explicitly incorporating higher ranking RM variations as perturbations, material-conserving experiments are shown to provide powerful and enduring robustness data. Case studies illustrate how correctly contextualizing such data in formulation and process development can avoid the traps of historical QbD approaches and become valuable for evaluating changes occurring later in the drug product lifecycle.
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