Computational Models to Predict Toxicological Endpoints in Drug Discovery and Strategies for Data Integration-Reference-Cited by-同舟云学术

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Computational Models to Predict Toxicological Endpoints in Drug Discovery and Strategies for Data Integration

Published:2017 Issue: Volume: Page:233-258
ISSN:
Container-title:Comprehensive Medicinal Chemistry III
language:
Short-container-title:

Author:

Brigo A.,Muster W.

Publisher

Elsevier

Reference100 articles.

1. Strategies for Using Computational Toxicology Methods in Pharmaceutical R&D;Muller,2008

2. Computational Toxicology in Drug Development;Muster;Drug Discovery Today,2008

3. The Use of In Silico Models Within a Large Pharmaceutical Company;Brigo,2016

4. Trial Watch: Phase III and Submission Failures: 2007–2010;Arrowsmith;Nature Reviews Drug Discovery,2011

5. Trial Watch: Phase II Failures: 2008–2010;Arrowsmith;Nature Reviews Drug Discovery,2011

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1. In Silico Toxicology;Drug Discovery and Evaluation: Safety and Pharmacokinetic Assays;2023

2. CSL-Tox: An open-source analytical framework for the comparison of short-term and long-term toxicity end points and exploring the opportunities for decreasing in-vivo studies conducted for drug development programs;2022-08-07

3. In silico approaches in organ toxicity hazard assessment: Current status and future needs in predicting liver toxicity;Computational Toxicology;2021-11

4. Predicting mammalian metabolism and toxicity of pesticides in silico;Pest Management Science;2018-06-09

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