Abstract

This work describes an effort to apply methods from process systems engineering to a pharmaceutical product design problem, with a novel application of statistical approaches to comparing solutions. A computational molecular design framework was employed to design carbohydrate molecules with high glass transition temperatures and low water content in the maximally freeze-concentrated matrix, with the objective of stabilizing lyophilized protein formulations. Quantitative structure–property relationships were developed for glass transition temperature of the anhydrous solute, glass transition temperature of the maximally concentrated solute, melting point of ice and Gordon–Taylor constant for carbohydrates. An optimization problem was formulated to design an excipient with optimal property values. Use of a stochastic optimization algorithm, Tabu search, provided several carbohydrate excipient candidates with statistically similar property values, as indicated by prediction intervals calculated for each property.

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