Open AccessPredictive and correlative techniques for the design, optimisation and manufacture of solid dosage forms
Author(s) -
Hardy Ian J.,
Cook Walter G.
Publication year - 2003
Publication title -
journal of pharmacy and pharmacology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.745
H-Index - 118
eISSN - 2042-7158
pISSN - 0022-3573
DOI - 10.1111/j.2042-7158.2003.tb02428.x
Subject(s) - correlative , computer science , process (computing) , dosage form , multivariate statistics , variety (cybernetics) , scale (ratio) , biochemical engineering , process engineering , machine learning , artificial intelligence , engineering , chemistry , philosophy , linguistics , physics , chromatography , quantum mechanics , operating system
There is much interest in predicting the properties of pharmaceutical dosage forms from the properties of the raw materials they contain. Achieving this with reasonable accuracy would aid the faster development and manufacture of dosage forms. A variety of approaches to prediction or correlation of properties are reviewed. These approaches have variable accuracy, with no single technique yet able to provide an accurate prediction of the overall properties of the dosage form. However, there have been some successes in predicting trends within a formulation series based on the physicochemical and mechanical properties of raw materials, predicting process scale‐up through mechanical characterisation of materials and predicting product characteristics by process monitoring. Advances in information technology have increased predictive capability and accuracy by facilitating the analysis of complex multivariate data, mapping formulation characteristics and capturing past knowledge and experience.