(71g) Development and Application of a Computer Simulation Package for Wet Bead Milling of Nanoscale Pharmaceutical Particles Using Population Balance and Fundamental Principles

Nanometer scale particles have found increased use in pharmaceutical formulations and wet bead milling is one way to make these particles. The purpose of this work is to develop a computer modeling package that can simulate the entire wet bead milling process of making a nanometer scale pharmaceutical formulation. Fundamental equations or principles describing relationships of various milling components were obtained through either external publications or in-house studies. Raw material properties, equipment specifications, process parameters, and final product quality parameters (mainly particle size) were linked together by the computer modeling package using fundamental equations and principles. Compound and equipment specific coefficients in the fundamental equations were obtained through either readily available existing data or computer simulation. The computer modeling package can be used to optimize milling process, determine scale-up parameters, and answer submission related questions by simulating the effects of material, process, and equipment parameter changes on final product quality.

The computer modeling package consisted of a set of modular programs each of which performs a specific task. For example, one module was used to calculate particle size distribution change using population balance equation, while another module was used to link to equipment details including mill chamber volume and geometry, bead size, etc.. The package was designed in a way that more modules can be added to expand its capability without significant change on existing modules. Existing data were needed for determining equation coefficients. However, only readily available data were needed, that is, no measurement needed specifically for the purpose of developing the model. The coefficients for the equations in the model need to be determined before using the model for predictions. Based on the availability of the data, the coefficients were determined in two ways. Some data, such as temperature, volume of the chamber, initial concentrations, were used directly as equation coefficients. The rest of the coefficients were determined using simulations while using other indirect measurements as constraints.

The modeling package was successfully used to predict some particle size distribution changes of design of experiment batches under extrapolation conditions, help explain particle size distribution shapes and milling mechanisms, and perform scale-up related simulations.