Mathematical model of microbicidal flow dynamics and optimization of rheological properties for intra-vaginal drug delivery: Role of tissue mechanics and fluid rheology.

Topically applied microbicide gels can provide a self-administered and effective strategy to prevent sexually transmitted infections (STIs). We have investigated the interplay between vaginal tissue elasticity and the yield-stress of non-Newtonian fluids during microbicide deployment. We have developed a mathematical model of tissue deformation driven spreading of microbicidal gels based on thin film lubrication approximation and demonstrated the effect of tissue elasticity and fluid yield-stress on the spreading dynamics. Our results show that both elasticity of tissue and yield-stress rheology of gel are strong determinants of the coating behavior. An optimization framework has been demonstrated which leverages the flow dynamics of yield-stress fluid during deployment to maximize retention while reaching target coating length for a given tissue elasticity.

Protein aggregation and lyophilization: Protein structural descriptors as predictors of aggregation propensity.

Lyophilization can induce aggregation in therapeutic proteins, but the relative importance of protein structure, formulation and processing conditions are poorly understood. To evaluate the contribution of protein structure to lyophilization-induced aggregation, fifteen proteins were co-lyophilized with each of five excipients. Extent of aggregation following lyophilization, measured using size-exclusion chromatography, was correlated with computational and biophysical protein structural descriptors via multiple linear regression. Descriptor selection was performed using exhaustive search and forward selection. The results demonstrate that, for a given excipient, extent of aggregation is highly correlated by eight to twelve structural descriptors. Leave-one-out cross validation showed that the correlations were able to successfully predict the aggregation for a protein "left out" of the data set. Selected descriptors varied with excipient, indicating both protein structure and excipient type contribute to lyophilization-induced aggregation. The results show some descriptors used to predict protein aggregation in solution are useful in predicting lyophilized protein aggregation.

Use of glass transitions in carbohydrate excipient design for lyophilized protein formulations.

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.