Predicting drug behavior to optimize manufacturing and delivery
Drug development is challenged in many ways. Physical testing is limited due to the very small amount of new active pharmaceutical ingredient (API) that is created initially. The FDA demands require maximum knowledge of drug behavior – referred to as “Quality-by-Design.” And late failure further downstream in clinical development and manufacturing is costly.
Molecular modelling can be used to maximize understanding of how an API will behave once it has been handed off from Discovery, thereby reducing the amount of API required for testing. Application areas for biologic therapeutics are potential aggregation, viscosity and solubility characteristics, for small molecule drugs growth morphologies and mechanical properties, for crystal and amorphous solid forms. Using downstream manufacturing data and specifications provide an understanding of the behavior of the therapeutic and thus satisfies Quality-by-Design criteria.
The prediction of critical manufacturability characteristics enables the design of optimal physical experiment parameter ranges and the parallel use of in silico experiments with physical experimentation forms an integrated, comprehensive rational drug development approach accelerating the development of novel drug candidates.