Traditionally, the design and scale-up of granulation processes has involved expensive
and laborious experimentation, due to a lack of knowledge and predictive tools for
process design. Process models are increasingly being developed and used for these
processes. This is an exciting and welcome development for the field, however the
outputs of these models are typically limited to one or two particle attributes, and do
not describe the performance of the products being produced. Product performance
models have received less attention than process models, and there is a clear need to
develop improved performance models for granular products, and to link these with
product models to enable performance driven process design. The aim of this project to
address this need.
This report provides a summary of the progress of the project Model Assisted Design
of Granular Products. Focus has been placed in this first year of the project on a critical
survey of the literature on granule, tablet and compact disintegration and dissolution
behaviour, culminating in the literature review presented in this report. This literature
review incorporates the current state of knowledge on the mechanisms of compact
disintegration and dissolution, and also includes a review of the mathematical models
available to describe these mechanisms. This review has informed the development of
two potential product models presented here for use in this project. The first is a granule
dispersion model, and the second a model for drug dissolution from granules in the
absence of disintegration.
Also presented within this report is preliminary experimental methodology
development for granulation and granule dissolution. Full methodology development
will take place after critical decisions are made on choices of product and process
models, however this initial experimentation has emphasised the need for careful
characterisation of feed materials and granular products.
A research plan for the remaining three years of the project is presented. This plan
incorporates the development, validation and integration of process and product models
for granulation, and the application of inverse methods to create a product performance
driven model for granulation.