Computational Intelligence Modeling of Pharmaceutical Properties

Zawbaa, Hossam M.

Publication:
Computational Intelligence Modeling of Pharmaceutical Properties

dc.affiliation.dpto	UC3M. Departamento de Informática	es
dc.affiliation.grupoinv	UC3M. Grupo de Investigación: Arquitectura de Computadores, Comunicaciones y Sistemas	es
dc.contributor.author	Zawbaa, Hossam M.
dc.contributor.editor	Carretero Pérez, Jesús
dc.contributor.editor	García Blas, Javier
dc.contributor.editor	Petcu, Dana
dc.date.accessioned	2016-04-29T08:39:11Z
dc.date.available	2016-04-29T08:39:11Z
dc.date.issued	2016-02
dc.description	Proceedings of the First PhD Symposium on Sustainable Ultrascale Computing Systems (NESUS PhD 2016) Timisoara, Romania. February 8-11, 2016.	en
dc.description.abstract	In the pharmaceutical industry, a good understanding of the casual relationship between product quality and attributes of formulations is very useful in developing new products, and optimizing manufacturing processes. Feature selection is mandatory due to the abundance of noisy, irrelevant, or misleading features. The selected features will improve the performance of the prediction model and will provide a faster and more cost effective prediction than using all the features. With the big data captured in the pharmaceutical product development practice, computational intelligence (CI) models and machine learning algorithms could potentially be used to identify the process parameters of formulations and manufacturing processes. That needs a deep investigation of roller compaction process parameters of pharmaceutical formulations that affect the ribbons production. In this work, we are using the bio-inspired optimization algorithms for feature selection such as (grey wolf, Bat, flower pollination, social spider, antlion, moth-flame, genetic algorithms, and particle swarm) to predict the different pharmaceutical properties.	en
dc.description.sponsorship	European Cooperation in Science and Technology. COST	en
dc.description.sponsorship	This work was supported by the IPROCOM Marie Curie initial training network, funded through the People Programme (Marie Curie Actions) of the European Union’s Seventh Framework Programme FP7/2007-2013/ under REA grant agreement No. 316555. In addition, this work was partially supported by NESUS.	en
dc.format.extent	4
dc.format.mimetype	application/pdf
dc.identifier.bibliographicCitation	Carretero Pérez, Jesús; et.al. (eds.). (2016). Proceedings of the First PhD Symposium on Sustainable Ultrascale Computing Systems (NESUS PhD 2016). Timisoara, Romania. Universidad Carlos III de Madrid, ARCOS. Pp. 1-4.	es
dc.identifier.isbn	978-84-608-6309-0
dc.identifier.publicationfirstpage	1
dc.identifier.publicationlastpage	4
dc.identifier.publicationtitle	Proceedings of the First PhD Symposium on Sustainable UltrascaleComputing Systems (NESUS PhD 2016)	en
dc.identifier.uri	https://hdl.handle.net/10016/22890
dc.language.iso	eng	en
dc.relation.eventdate	February 8-11, 2016
dc.relation.eventnumber	1
dc.relation.eventplace	Timisoara, Romania	en
dc.relation.eventtitle	PhD Symposium on Sustainable Ultrascale Computing Systems (NESUS PhD 2016)	en
dc.relation.projectID	info:eu-repo/grantAgreement/EC/FP7/316555
dc.rights	Atribución-NoComercial-SinDerivadas 3.0 España	*
dc.rights.accessRights	open access
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/3.0/es/	*
dc.subject.eciencia	Informática	es
dc.subject.other	Computational Intelligence	en
dc.subject.other	Pharmaceutical Roll Compaction	en
dc.subject.other	Bio-inspired Optimization	en
dc.subject.other	Feature Selection	en
dc.title	Computational Intelligence Modeling of Pharmaceutical Properties	en
dc.type	conference paper	*
dc.type.hasVersion	VoR	*
dspace.entity.type	Publication