Contribution of the Physicochemical Properties of Active Pharmaceutical Ingredients to Tablet Properties Identified by Ensemble Artificial Neural Networks and Kohonen's Self-Organizing Maps

The aim of this study was to create a tablet database for use in designing tablet formulations. We focused on the contribution of active pharmaceutical ingredients (APIs) to tablet properties such as hardness and disintegration time (DT). Before we investigated the effects of the APIs, we optimized...

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Bibliographic Details
Published in:Journal of pharmaceutical sciences 2012-07, Vol.101 (7), p.2372-2381
Main Authors: Onuki, Yoshinori, Kawai, Shota, Arai, Hiroaki, Maeda, Jin, Takagaki, Keisuke, Takayama, Kozo
Format: Article
Language:English
Subjects:
Biological and medical sciences
dissolution
formulation
General pharmacology
Hardness
Medical sciences
Models, Chemical
Neural Networks (Computer)
Pharmaceutical Preparations - chemistry
Pharmaceutical technology. Pharmaceutical industry
Pharmacology. Drug treatments
physicochemical properties
Regression Analysis
Solubility
tablet
Tablets - chemistry
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Summary:The aim of this study was to create a tablet database for use in designing tablet formulations. We focused on the contribution of active pharmaceutical ingredients (APIs) to tablet properties such as hardness and disintegration time (DT). Before we investigated the effects of the APIs, we optimized the tablet base formulation (placebo tablet) according to an expanded simplex search. The optimal placebo tablet showed sufficient hardness and rapid disintegration. We then tested 14 kinds of compounds as the model APIs. The APIs were characterized in terms of their physicochemical properties using Kohonen's self-organizing maps. We also prepared model tablets by incorporating the APIs into the optimal placebo tablet, and then examined the tablet properties, including tensile strength and DT. On the basis of the experimental data, an ensemble artificial neural network incorporating general regression analysis was conducted. A reliable model of the correlation between the physicochemical properties of the APIs and the tablet properties was thus constructed. From the correlation model, we clarified the detailed contributions of each physicochemical property to the tablet attributes.
ISSN:0022-3549
1520-6017
DOI:10.1002/jps.23134