Characterization of the 3D microstructure of Ibuprofen tablets by means of synchrotron tomography.

We present a methodology to characterize the 3D microstructure of Ibuprofen tablets, which strongly influences the strength and solubility kinetics of the final formulation, by means of synchrotron tomography. A physically coherent trinarization for greyscale images of Ibuprofen tablets consisting of the three phases microcrystalline cellulose, Ibuprofen and pores is presented. For this purpose, a hybrid approach is developed combining a trinarization by means of statistical learning with a trinarization based on a watershed algorithm. This hybrid approach allows us to compute microstructure characteristics of tablets using image analysis. A comparison with experimental results shows that there is a significant amount of pores which is below the resolution limit and results from image analysis let us conjecture that these pores make up the major part of the surface between pores and solid. Furthermore, we compute microstructure characteristics, which are experimentally not accessible such as local percolation probabilities and chord length distribution functions. Both characteristics are meaningful in order to quantify the influence of tablet compaction on its microstructure. The presented approach can be used to get better insights into the relationship between production parameters and microstructure characteristics based on 3D image data of Ibuprofen tablets manufactured under different conditions.