Drug repurposing and adverse event prediction using high‐throughput literature analysis
| العنوان: | Drug repurposing and adverse event prediction using high‐throughput literature analysis |
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| المؤلفون: | Aris Persidis, Spyros Deftereos, Andreas Persidis, Ellen J. Friedla, Christos Andronis |
| المصدر: | WIREs Systems Biology and Medicine. 3:323-334 |
| بيانات النشر: | Wiley, 2011. |
| سنة النشر: | 2011 |
| مصطلحات موضوعية: | Drug, Drug-Related Side Effects and Adverse Reactions, Computer science, Process (engineering), Drug discovery, business.industry, media_common.quotation_subject, Drug Repositioning, Medicine (miscellaneous), Pharmacology, Models, Biological, Biochemistry, Genetics and Molecular Biology (miscellaneous), Drug repositioning, Pharmaceutical Preparations, Drug development, Risk analysis (engineering), Analytics, Drug Discovery, Animals, Humans, Adverse effect, business, ADME, media_common |
| الوصف: | Drug repurposing is the process of using existing drugs in indications other than the ones they were originally designed for. It is an area of significant recent activity due to the mounting costs of traditional drug development and scarcity of new chemical entities brought to the market by bio-pharmaceutical companies. By selecting drugs that already satisfy basic toxicity, ADME and related criteria, drug repurposing promises to deliver significant value at reduced cost and in dramatically shorter time frames than is normally the case for the drug development process. The same process that results in drug repurposing can also be used for the prediction of adverse events of known or novel drugs. The analytics method is based on the description of the mechanism of action of a drug, which is then compared to the molecular mechanisms underlying all known adverse events. This review will focus on those approaches to drug repurposing and adverse event prediction that are based on the biomedical literature. Such approaches typically begin with an analysis of the literature and aim to reveal indirect relationships among seemingly unconnected biomedical entities such as genes, signaling pathways, physiological processes, and diseases. Networks of associations of these entities allow the uncovering of the molecular mechanisms underlying a disease, better understanding of the biological effects of a drug and the evaluation of its benefit/risk profile. In silico results can be tested in relevant cellular and animal models and, eventually, in clinical trials. |
| تدمد: | 1939-005X 1939-5094 |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d988e13e19f7f47387755663c807792a https://doi.org/10.1002/wsbm.147 |
| حقوق: | CLOSED |
| رقم الأكسشن: | edsair.doi.dedup.....d988e13e19f7f47387755663c807792a |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 1939005X 19395094 |
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