Paper Info
Title
Classification of pharmaceutical solid excipients using self-organizing maps
Abstract
In pharmaceutical technology the study of rheological behavior of powders is an important step in pre formulation of solid dosage forms. These studies, particularly the flow behavior of powders, is an exhausting and very time consuming task, which requires tools that render this process faster while maintaining accuracy. The self-organizing map (SOM) is tool in the exploratory phase of data mining. It projects data from input space to low-dimensional regular grid which may be effectively utilized to visualize and explore properties of the data. This paper applies self-organizing map and K-means in order to analyze rheological characteristics of pharmaceutical solid excipients and their binary mixtures e.q. attapulgite, a natural clay candidate to solid excipient. Self-organizing map was able to classify effectively the excipients in ordered and coherent groups and classified attapulgite as a characteristic grouping having properties far distinct from the other groups of excipients. SOM enabled a reduction of experiments via exploratory data analysis about the rheological behavior of these powders.
Year
DOI
Venue
2012
10.1007/978-3-642-32639-4_84
IDEAL
Keywords
Field
DocType
exploratory data analysis,data mining,flow behavior,self-organizing map,rheological characteristic,solid dosage form,classified attapulgite,pharmaceutical solid excipients,solid excipient,rheological behavior
k-means clustering,Biological system,Pattern recognition,Computer science,Simulation,Excipient,Self-organizing map,Artificial intelligence,Exploratory data analysis,Pharmaceutical technology,Dosage form
Conference
Citations 
PageRank 
References 
0
0.34
4
Authors
7
Name
Order
Citations
PageRank
Giovani Ângelo S. da Nóbrega100.34
Marco V. M. Navarro200.34
Túlio A. de Lima e Moura300.34
Daiane Soares400.34
José Alfredo F. Costa55210.11
Edilene P. Lavor600.34
Regivan H. N. Santiago79217.42