Integrating safety and health indexes in computer-aided molecular design under property prediction uncertainty

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Main Authors: Joon, Yoon Ten, Lik, Yin Ng, Mimi, H. Hassim, Denny, Ng K.S., G. Chemmangattuvalappil, Nishanth
Format: Article
Language:English
Published: The Institution of Engineers, Malaysia (IEM) 2017
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Online Access:http://dspace.unimap.edu.my:80/xmlui/handle/123456789/50808
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Institution: Universiti Malaysia Perlis
Language: English
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spelling my.unimap-508082017-12-19T12:42:10Z Integrating safety and health indexes in computer-aided molecular design under property prediction uncertainty Joon, Yoon Ten Lik, Yin Ng Mimi, H. Hassim Denny, Ng K.S. G. Chemmangattuvalappil, Nishanth Carotenoids extraction Computer-aided molecular design Property prediction model Safety and Health Index Uncertainty Link to publisher’s homepage at http://www.myiem.org Computer-Aided Molecular Design (CAMD) is a powerful tool for designing promising molecules with the targeted properties. Besides properties, the safety and health aspects must also be considered during design stage to ensure the synthesized molecules do not cause much harm. The molecules are assessed by several safety and health parameters, which are measured using physicochemical properties that can be estimated via property prediction methods. Each parameter/sub-index is allocated with a penalty score based on the property to represent the hazard level of molecules. However, uncertainty in the prediction models can adversely affect the accuracy of scores. The main highlight of this paper is to manage the effect of uncertainty on the safety and health sub-indexes, by improving the scores at the uncertain region for enhanced measurement of molecular hazards. A case study on solvent design for carotenoids extraction from Palm Pressed Fiber (PPF) has been considered with the proposed methodology. 2017-12-19T12:42:10Z 2017-12-19T12:42:10Z 2017-06 Article The Journal of the Institution of Engineers, Malaysia, Vol. 78(1), 2017, pages 7-12 0126-513x http://dspace.unimap.edu.my:80/xmlui/handle/123456789/50808 http://www.myiem.org en The Institution of Engineers, Malaysia (IEM)
institution Universiti Malaysia Perlis
building UniMAP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Perlis
content_source UniMAP Library Digital Repository
url_provider http://dspace.unimap.edu.my/
language English
topic Carotenoids extraction
Computer-aided molecular design
Property prediction model
Safety and Health Index
Uncertainty
spellingShingle Carotenoids extraction
Computer-aided molecular design
Property prediction model
Safety and Health Index
Uncertainty
Joon, Yoon Ten
Lik, Yin Ng
Mimi, H. Hassim
Denny, Ng K.S.
G. Chemmangattuvalappil, Nishanth
Integrating safety and health indexes in computer-aided molecular design under property prediction uncertainty
description Link to publisher’s homepage at http://www.myiem.org
format Article
author Joon, Yoon Ten
Lik, Yin Ng
Mimi, H. Hassim
Denny, Ng K.S.
G. Chemmangattuvalappil, Nishanth
author_facet Joon, Yoon Ten
Lik, Yin Ng
Mimi, H. Hassim
Denny, Ng K.S.
G. Chemmangattuvalappil, Nishanth
author_sort Joon, Yoon Ten
title Integrating safety and health indexes in computer-aided molecular design under property prediction uncertainty
title_short Integrating safety and health indexes in computer-aided molecular design under property prediction uncertainty
title_full Integrating safety and health indexes in computer-aided molecular design under property prediction uncertainty
title_fullStr Integrating safety and health indexes in computer-aided molecular design under property prediction uncertainty
title_full_unstemmed Integrating safety and health indexes in computer-aided molecular design under property prediction uncertainty
title_sort integrating safety and health indexes in computer-aided molecular design under property prediction uncertainty
publisher The Institution of Engineers, Malaysia (IEM)
publishDate 2017
url http://dspace.unimap.edu.my:80/xmlui/handle/123456789/50808
_version_ 1643802991237529600