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Rectifying Cancer Drug Discovery Through Network Pharmacology

Authors: Asfar S, Azmi; Ramzi M, Mohammad;

Rectifying Cancer Drug Discovery Through Network Pharmacology

Abstract

In spite of the expensive preclinical testing, the consistent failure to translate many promising targeted drugs from the laboratory bench to the clinic raises the question of whether the single-pathway drug-discovery strategies offer the correct perspective. As revealed by network biology, cancers harbor robust biological networks that are inherently resistant to changes, such as those induced by drugs with very narrow mechanisms of action. Therefore, network pharmacology strategies, the treatment of cancer by modulating more than one target, are needed. Different promiscuous approaches targeting multiple avenues within cancer-associated networks, such as the pleiotropic natural products, are emerging. Nevertheless, there is a long way before such 'proof-of-concept strategies' can be successfully applied in the clinical setting. This article provides a perspective on the current challenges in drug discovery, the reasons for high failure rates and how network pharmacology can aid the successful design of agents against cancer.

Keywords

Biological Products, Systems Biology, Drug Repositioning, Antineoplastic Agents, Doxorubicin, Drug Resistance, Neoplasm, Vincristine, Neoplasms, Antineoplastic Combined Chemotherapy Protocols, Drug Discovery, Humans, Prednisone, Protein Interaction Maps, Cyclophosphamide, Metabolic Networks and Pathways

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    popularity
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    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
17
Top 10%
Average
Top 10%
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