PERCOLATION THEORY AND ROBUST FORMULATIONS IN POWDER TECHNOLOGY

摘要

Pharmaceutical solid dosage forms (tablets, dragees, capsules) represent the majority of all dosage forms on the market. To guarantee a high quality of these dosage forms robust formulations are a prerequisite. Thus, a formulation which describes the composition and the process needs to be validated. Due to the complexity of a pharmaceutical formulation, the high number of factors, which may affect the quality of the dosage form, most of the knowledge concerning the use of pharmaceutical powder mixtures is based on empirical findings. Percolation theory seems to offer a key for a more rational design of formulations consisting of particulate material. Two typical applications will be presented: a fast-disintegrating water-soluble tablet formulation and a non-swellable matrix-type controlled release system which does not disintegrate. The application of the concepts of percolation theory, which is useful in very different areas, such as phase transitions in solids, diffusion in disordered media, etc., leads to an important insight in the behaviour of the fast-disintegrating and the non-disintegrating solid dosage forms. The fundamental equation of percolation theory can be applied in both cases. The equation is a power law which describes the relevant property X of the system studied close to the percolation theshold p_c as follows X = S/p-p_c/q (1) with S = Scaling factor, p = occupation probability and q = critical exponent The occupation probability in a particulate system corresponds in general to the concentration of the relevant component, such as the disintegrant in the fast-disintegrating tablet or the drug load in the non-disintegrating matrix-type controlled release system. It is an important task to evaluate the possible presence of a critical concentration, i.e. percolation threshold where the relevant component percolates the system. Thus, only formulations with concentration p, which are not too close to the pecolation threshold p_c, represent robust formulations.