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Artificial intelligence in pharmaceutical product formulation: Neural computing

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2009
1186.pdf (1.176Mb)
Authors
Ibrić, Svetlana
Đurić, Zorica
Parojčić, Jelena
Petrović, Jelena
Article (Published version)
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Abstract
The properties of a formulation are determined not only by the ratios in which the ingredients are combined but also by the processing conditions. Although the relationships between the ingredient levels, processing conditions, and product performance may be known anecdotally, they can rarely be quantified. In the past, formulators tended to use statistical techniques to model their formulations, relying on response surfaces to provide a mechanism for optimization. However, the optimization by such a method can be misleading, especially if the formulation is complex. More recently, advances in mathematics and computer science have led to the development of alternative modeling and data mining techniques which work with a wider range of data sources: neural networks (an attempt to mimic the processing of the human brain); genetic algorithms (an attempt to mimic the evolutionary process by which biological systems self-organize and adapt), and fuzzy logic (an attempt to mimic the ability... of the human brain to draw conclusions and generate responses based on incomplete or imprecise information). In this review the current technology will be examined, as well as its application in pharmaceutical formulation and processing. The challenges, benefits and future possibilities of neural computing will be discussed.

Keywords:
artificial neural networks / pharmaceutical formulation / genetic algorithms / fuzzy logic / optimization
Source:
CICEQ - Chemical Industry and Chemical Engineering Quarterly, 2009, 15, 4, 227-236
Publisher:
  • Savez hemijskih inženjera, Beograd

DOI: 10.2298/CICEQ0904227I

ISSN: 1451-9372

WoS: 000275477600005

Scopus: 2-s2.0-77149155363
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URI
http://farfar.pharmacy.bg.ac.rs/handle/123456789/1188
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  • Radovi istraživača / Researchers’ publications
Institution
Pharmacy

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