کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
5856847 1131984 2013 9 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Validation of Toxtree and SciQSAR in silico predictive software using a publicly available benchmark mutagenicity database and their applicability for the qualification of impurities in pharmaceuticals
موضوعات مرتبط
علوم زیستی و بیوفناوری علوم محیط زیست بهداشت، سم شناسی و جهش زایی
پیش نمایش صفحه اول مقاله
Validation of Toxtree and SciQSAR in silico predictive software using a publicly available benchmark mutagenicity database and their applicability for the qualification of impurities in pharmaceuticals
چکیده انگلیسی


- Toxtree-Hansen external 6489 compound mutagenicity validation.
- Validation of a SciQSAR-Hansen benchmark mutagenicity model.
- The 503 compound external validation of the SciQSAR mutagenicity model.
- The applicability of SciQSAR and Toxtree for the qualification of drug impurities.
- The predictive performance of combined SciQSAR-Toxtree analysis.

The draft ICH M7 guidance (US FDA, 2013) recommends that the computational assessment of bacterial mutagenicity for the qualification of impurities in pharmaceuticals be performed using an expert rule-based method and a second statistically-based (Q)SAR method. The public nonproprietary 6489 compound Hansen benchmark mutagenicity data set was used as an external validation data set for Toxtree, a free expert rule-based SAR software. This is the largest known external validation of Toxtree. The Toxtree external validation specificity, sensitivity, concordance and false negative rate for this mutagenicity data set was 66%, 80%, 74% and 20%, respectively.This mutagenicity data set was also used to create a statistically-based SciQSAR-Hansen mutagenicity model. In a 10% leave-group-out internal cross validation study the specificity, sensitivity, concordance and false negative rate for the SciQSAR mutagenicity model was 71%, 83%, 77% and 17%, respectively. Combining Toxtree and SciQSAR predictions and scoring a positive finding in either software as a positive mutagenicity finding reduced the false negative rate to 7% and increased sensitivity to 93% at the expense of specificity which decreased to 53%.The results of this study support the applicability of Toxtree, and the SciQSAR-Hansen mutagenicity model for the qualification of impurities in pharmaceuticals.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Regulatory Toxicology and Pharmacology - Volume 67, Issue 2, November 2013, Pages 285-293
نویسندگان
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