Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
2506097 | International Journal of Pharmaceutics | 2007 | 14 Pages |
High efficiency in polymorph screening and crystallization optimization can be gained by judicious selection of solvents for the study design. Examination of all 57 (classes 2 and 3) pharmaceutical solvents may enable a complete study design but is costly in terms of time and resources. Based on a 17 descriptor dataset specifically constructed for all the classes 2 and 3 pharmaceutical solvents recognized by the International Conference of Harmonization (ICH), an optimal two-stage cluster analysis was carried out together with principal component analysis as a dimensionality and colinearity reduction pre-processor. Both hierarchical average linkage cluster analysis and non-hierarchical K-means cluster analysis converged on a 20-cluster solution with strong statistical criteria support and excellent agreement in cluster memberships, which can be reasonably interpreted from a chemical perspective. This 20-cluster solution is offered as an option for design of more efficient solid state screening studies. Rather than designing a polymorph screen to include all 57 solvents, the inclusion of a single member from each of the 20 clusters would be expected to adequately represent the full range of solvent properties exhibited by the entire 57 member solvent set.