Abstract
Formulation robustness is critical to product quality. A challenge in designing robustness into biologic formulations is the absence of one global parameter, which allows equitable comparison across formulations and quality measures. The new measure introduced here derived from accelerated testing data allows for the design of globally optimal robust formulations. The measure is easy to understand and also numerically and computationally stable when performing optimizations. The measure termed here as robustness index (RobX) score is a relative measure allowing for global optimization across multiple critical quality attributes. Described here are the calculation methods, a discussion of the measure characteristics, and a brief example of using RobX to find a global optimal formulation across multiple quality characteristics within the framework of a mixture experimental design. The data presented are actual stability data generated during a formulation experimental design for a monoclonal antibody. We anticipate this approach will provide a good general measure of drug stability and will help to accelerate the drug development process. We believe it will improve formulation robustness, long-term stability, and the delivery of quality drug products to the patient.
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