[HTML][HTML] Computational approaches in preclinical studies on drug discovery and development

F Wu, Y Zhou, L Li, X Shen, G Chen, X Wang… - Frontiers in …, 2020 - frontiersin.org
Because undesirable pharmacokinetics and toxicity are significant reasons for the failure of
drug development in the costly late stage, it has been widely recognized that drug ADMET …

An overview of machine learning and big data for drug toxicity evaluation

AH Vo, TR Van Vleet, RR Gupta… - Chemical research in …, 2019 - ACS Publications
Drug toxicity evaluation is an essential process of drug development as it is reportedly
responsible for the attrition of approximately 30% of drug candidates. The rapid increase in …

The Taverna workflow suite: designing and executing workflows of Web Services on the desktop, web or in the cloud

K Wolstencroft, R Haines, D Fellows… - Nucleic acids …, 2013 - academic.oup.com
The Taverna workflow tool suite (http://www. taverna. org. uk) is designed to combine
distributed Web Services and/or local tools into complex analysis pipelines. These pipelines …

[HTML][HTML] Open PHACTS: semantic interoperability for drug discovery

AJ Williams, L Harland, P Groth, S Pettifer… - Drug discovery today, 2012 - Elsevier
Open PHACTS is a public–private partnership between academia, publishers, small and
medium sized enterprises and pharmaceutical companies. The goal of the project is to …

A European perspective on alternatives to animal testing for environmental hazard identification and risk assessment

S Scholz, E Sela, L Blaha, T Braunbeck… - Regulatory toxicology …, 2013 - Elsevier
Tests with vertebrates are an integral part of environmental hazard identification and risk
assessment of chemicals, plant protection products, pharmaceuticals, biocides, feed …

Chemo-and bioinformatics resources for in silico drug discovery from medicinal plants beyond their traditional use: a critical review

AA Lagunin, RK Goel, DY Gawande, P Pahwa… - Natural product …, 2014 - pubs.rsc.org
Covering: up to 2014 In silico approaches have been widely recognised to be useful for drug
discovery. Here, we consider the significance of available databases of medicinal plants and …

[HTML][HTML] Linked open drug data for pharmaceutical research and development

M Samwald, A Jentzsch, C Bouton, CS Kallesøe… - Journal of …, 2011 - Springer
There is an abundance of information about drugs available on the Web. Data sources
range from medicinal chemistry results, over the impact of drugs on gene expression, to the …

[HTML][HTML] Lazar: a modular predictive toxicology framework

A Maunz, M Gütlein, M Rautenberg… - Frontiers in …, 2013 - frontiersin.org
lazar (lazy structure–activity relationships) is a modular framework for predictive toxicology.
Similar to the read across procedure in toxicological risk assessment, lazar creates local …

Artificial intelligence in drug design: algorithms, applications, challenges and ethics

AA Arabi - Future Drug Discovery, 2021 - Taylor & Francis
The discovery paradigm of drugs is rapidly growing due to advances in machine learning
(ML) and artificial intelligence (AI). This review covers myriad faces of AI and ML in drug …

Progress in computational toxicology

S Ekins - Journal of pharmacological and toxicological methods, 2014 - Elsevier
Introduction: Computational methods have been widely applied to toxicology across
pharmaceutical, consumer product and environmental fields over the past decade. Progress …