A framework for in-silico formulation design using multivariate latent variable regression methods

Abstract

A comprehensive Quality by Design development paradigm should consider the impact of raw materials and formulation on the final drug product. This work proposes a quantitative approach to simultaneously predict particle, powder, and compact mechanical properties of a pharmaceutical blend, based on that of the raw materials. A new, two-step, multivariate modeling method, referred to as the weighted scores PLS, was developed to address the challenge of predicting the properties of a powder blend while enabling process understanding. The model validation exercise is shown along with selected practical applications. It is shown how the proposed in-silico model exhibits sufficient predictive power to be an important tool in the pharmaceutical development decision making process while requiring minimal experimentation and material usage.