PREDIKSI TOKSISITAS SENYAWA MIGRASI DARI KEMASAN PANGAN BERBAHAN KERTAS DAN KARTON MENGGUNAKAN METODE TOKSIKOLOGI KOMPUTASI

Computational toxicology is one of the alternative methods that have been widely recognized and recommended as one of the methods to identify and characterize the hazard of chemical substances. The aim of this research was to obtain hazard characterization data of non-evaluated 17 substances as p...

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Main Author: Mutakin, Ayi
Format: Final Project
Language:Indonesia
Online Access:https://digilib.itb.ac.id/gdl/view/44312
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Institution: Institut Teknologi Bandung
Language: Indonesia
id id-itb.:44312
spelling id-itb.:443122019-10-10T09:08:06ZPREDIKSI TOKSISITAS SENYAWA MIGRASI DARI KEMASAN PANGAN BERBAHAN KERTAS DAN KARTON MENGGUNAKAN METODE TOKSIKOLOGI KOMPUTASI Mutakin, Ayi Indonesia Final Project migrating substance, contaminant, food packaging material, computational toxicology. INSTITUT TEKNOLOGI BANDUNG https://digilib.itb.ac.id/gdl/view/44312 Computational toxicology is one of the alternative methods that have been widely recognized and recommended as one of the methods to identify and characterize the hazard of chemical substances. The aim of this research was to obtain hazard characterization data of non-evaluated 17 substances as potential migrating contaminant from paper and board packaging materials into the food products. The hazard characteristics was predicted by means of in silico methods using QSAR Toolbox 3.4, T.E.S.T 4.2.1, TOXTREE 2.6.13 and VEGA 1.1.3 softwares, including carcinogenicity, mutagenicity, reprotoxicity, acute toxicity and chronic toxicity properties. Prior hazard characteristic prediction, all softwares were validated using a set of positive and negative control substances including sensitivity, specificity, accuracy, positive predictivity, negative predictivity, false positive rate, and false negative rate aspects as acceptance criteria. Validation results showed that all softwares could provide good predictions, except QSAR Toolbox (RA) and T.E.S.T for prediction of repretoxicity. Among the 17 substances, 2 substances were predicted as carcinogenic, 1 substance as mutagenic, 2 substances as carcinogenic and mutagenic, and 12 substances as non-carcinogenic, non-mutagenic, and non-reprotoxic. 5 substances predicted to be carcinogenic and or mutagenic were further estimated for their metabolic transformation by Cytochrome P450, the result revealed that their metabolites generally showed the same carcinogenic and or mutagenic potential. In the case of acute toxicity stated as LD50, 1 substance was predicted to be highly toxic, 13 substances were moderately toxic, and 3 substances were slightly toxic, with the lowest LD50 value was 381,77 mg/kg for 3,5-dimethylpyrazole and the highest one was 7.353,03 mg/kg for oxydipropyl dibenzoate. Chronic toxicity was predicted based on NOEL values and their corresponding derived TDI values. The lowest TDI value was 0,00394 mg/kg/day for 2,4,6-trichloro-1,3,5-triazine and the highest one was 0,36 mg/kg/day for oxydiethylene dibenzoate. Based on overall results, it can be concluded that the hazard characterization data of non-evaluated 17 substances as potential migrating contaminant was successfully obtained. text
institution Institut Teknologi Bandung
building Institut Teknologi Bandung Library
continent Asia
country Indonesia
Indonesia
content_provider Institut Teknologi Bandung
collection Digital ITB
language Indonesia
description Computational toxicology is one of the alternative methods that have been widely recognized and recommended as one of the methods to identify and characterize the hazard of chemical substances. The aim of this research was to obtain hazard characterization data of non-evaluated 17 substances as potential migrating contaminant from paper and board packaging materials into the food products. The hazard characteristics was predicted by means of in silico methods using QSAR Toolbox 3.4, T.E.S.T 4.2.1, TOXTREE 2.6.13 and VEGA 1.1.3 softwares, including carcinogenicity, mutagenicity, reprotoxicity, acute toxicity and chronic toxicity properties. Prior hazard characteristic prediction, all softwares were validated using a set of positive and negative control substances including sensitivity, specificity, accuracy, positive predictivity, negative predictivity, false positive rate, and false negative rate aspects as acceptance criteria. Validation results showed that all softwares could provide good predictions, except QSAR Toolbox (RA) and T.E.S.T for prediction of repretoxicity. Among the 17 substances, 2 substances were predicted as carcinogenic, 1 substance as mutagenic, 2 substances as carcinogenic and mutagenic, and 12 substances as non-carcinogenic, non-mutagenic, and non-reprotoxic. 5 substances predicted to be carcinogenic and or mutagenic were further estimated for their metabolic transformation by Cytochrome P450, the result revealed that their metabolites generally showed the same carcinogenic and or mutagenic potential. In the case of acute toxicity stated as LD50, 1 substance was predicted to be highly toxic, 13 substances were moderately toxic, and 3 substances were slightly toxic, with the lowest LD50 value was 381,77 mg/kg for 3,5-dimethylpyrazole and the highest one was 7.353,03 mg/kg for oxydipropyl dibenzoate. Chronic toxicity was predicted based on NOEL values and their corresponding derived TDI values. The lowest TDI value was 0,00394 mg/kg/day for 2,4,6-trichloro-1,3,5-triazine and the highest one was 0,36 mg/kg/day for oxydiethylene dibenzoate. Based on overall results, it can be concluded that the hazard characterization data of non-evaluated 17 substances as potential migrating contaminant was successfully obtained.
format Final Project
author Mutakin, Ayi
spellingShingle Mutakin, Ayi
PREDIKSI TOKSISITAS SENYAWA MIGRASI DARI KEMASAN PANGAN BERBAHAN KERTAS DAN KARTON MENGGUNAKAN METODE TOKSIKOLOGI KOMPUTASI
author_facet Mutakin, Ayi
author_sort Mutakin, Ayi
title PREDIKSI TOKSISITAS SENYAWA MIGRASI DARI KEMASAN PANGAN BERBAHAN KERTAS DAN KARTON MENGGUNAKAN METODE TOKSIKOLOGI KOMPUTASI
title_short PREDIKSI TOKSISITAS SENYAWA MIGRASI DARI KEMASAN PANGAN BERBAHAN KERTAS DAN KARTON MENGGUNAKAN METODE TOKSIKOLOGI KOMPUTASI
title_full PREDIKSI TOKSISITAS SENYAWA MIGRASI DARI KEMASAN PANGAN BERBAHAN KERTAS DAN KARTON MENGGUNAKAN METODE TOKSIKOLOGI KOMPUTASI
title_fullStr PREDIKSI TOKSISITAS SENYAWA MIGRASI DARI KEMASAN PANGAN BERBAHAN KERTAS DAN KARTON MENGGUNAKAN METODE TOKSIKOLOGI KOMPUTASI
title_full_unstemmed PREDIKSI TOKSISITAS SENYAWA MIGRASI DARI KEMASAN PANGAN BERBAHAN KERTAS DAN KARTON MENGGUNAKAN METODE TOKSIKOLOGI KOMPUTASI
title_sort prediksi toksisitas senyawa migrasi dari kemasan pangan berbahan kertas dan karton menggunakan metode toksikologi komputasi
url https://digilib.itb.ac.id/gdl/view/44312
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