Optimization of green spherical agglomeration process based on response surface methodology for preparation of high-performance spherical particles

Abstract

Spherical agglomeration (SA) is a processing technique that enhances the physical properties of particles, reduces the number of unit operations in pharmaceutical manufacturing, and improves process efficiency. However, one of the limitations of SA is its high nonlinearity, which makes scalability a challenge. This prospective study was designed to realize the optimization of SA process parameters of aspirin, the world’s first and most widely used nonsteroidal anti-inflammatory drug, by developing a green SA model through response surface methodology. First, Plackett-Burman experiments were conducted to identify the key operating variables affecting SA, and Sustainability Index (STI) was defined to evaluate the effects of these operating variables on the SA and the energy input to the environment during the post-processing process. Furthermore, the effects of three independent variables on mean size, yield, and STI were investigated based on Box-Behnken design. A second-order regression equation with response values was developed to optimize the above three objectives. As a result, the spherical products were obtained with excellent powder properties, including anti-caking property, filtration property, and tableting performance compared to the raw materials. This work provides an experimental and modelling basis for the further application of this environmentally-friendly SA technology.