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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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 |
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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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1822270639627567104 |