Numerical prediction of long-term stability of liquid formulations determined by visual observation and static multiple light scattering

Abstract

The demonstration of long-term stability is a key step when developing liquid formulation because it has a major impact on product shelf life, transport, and end-use properties. Long-term stability is often determined visually as the result is indisputable. However, this method is not compatible with product development cycle which requires rapid development and large screening of formulations. Static multiple light scattering (SMLS) technique has been widely used to detect instabilities at an early stage compared to visual observation. In this study, we developed a numerical predictive algorithm to evaluate the stability time determined by naked eye and measured by SMLS. This predictive algorithm was built on the analysis of several tens of liquid formulations with carefully controlled properties using a camera setup and the SMLS technique. The camera setup mimicked the human vision by recording images of the sample at a given frequency. Edge detection with criteria on contrast and size of instability zone was applied to a sequence of images to evaluate the stability objectively. The stability was also evaluated using SMLS measurements by imposing a monotone and minimal transmission or backscattered intensity evolution. In parallel, a numerical model was built to simulate the time and space resolved SMLS profiles. The predictive algorithm was developed by correlating the simulations of time and space resolved SMLS profiles to the stability time measured experimentally with the camera setup and the SMLS technique. Using the experimental results obtained with the camera setup and with the SMLS technique, this predictive algorithm was tested on non-controlled emulsions and solid dispersions proving its applicability to more realistic systems. This algorithm is a major step toward the rapid screening of long-term stability of liquid formulations.