Computer-Based Prediction Models in Regulatory Toxicology

Author:

Steger-Hartmann Thomas,Boyer Scott

Publisher

Springer Berlin Heidelberg

Reference19 articles.

1. Alexander DLJ, Tropsha A, Winkler DA (2015) Beware of R2: simple, unambiguous assessment of the prediction accuracy of QSAR and QSPR models. J Chem Inf Model 55:1316–1322

2. Glowienke S, Hasselgren C (2010) Use of structure activity relationship (SAR) evaluations as a critical tool in the evaluation of the genotoxic potential of impurities. In: Teasdale A (ed) Genotoxic impurities: strategies for identification and control. Wiley, New York, pp 97–120

3. Hasselgren C, Muthas D, Ahlberg E, Andersson S, Carlsson L, Noeske T, Stålring J, Boyer S (2013) Chemoinformatics and beyond – moving from simple models to complex relationships in pharmaceutical computational toxicology. In: Bajorath J (ed) Chemoinformatics: case studies and pharmaceutical applications. Wiley, New York, pp 49–62

4. International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use (ICH) (2017) Assessment and control of DA reactive (mutagenic) impurities in pharmaceuticals to limit potential carcinogenic risk M7(R1). 31 March 2017

5. Kaltenhäuser J, Kneuer C, Marx-Stoelting P, Niemann L, Schubert J, Stein B, Solecki R (2017) Relevance and reliability of experimental data in human health risk assessment of pesticides. Regul Toxicol Pharmacol 88:227–237

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