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Expert Opin Drug Discov. 2018 Feb;13(2):179-192. doi: 10.1080/17460441.2018.1413089. Epub 2017 Dec 12.

Improving the efficacy-safety balance of polypharmacology in multi-target drug discovery.

Author information

1
a Institute for Molecular Medicine Finland , FIMM, University of Helsinki , Helsinki , Finland.
2
b Department of Mathematics and Statistics , University of Turku , Turku , Finland.

Abstract

Polypharmacology has emerged as an essential paradigm for modern drug discovery process. Multiple lines of evidence suggest that agents capable of modulating multiple targets in a selective manner may offer also improved balance between therapeutic efficacy and safety compared to single-targeted agents. Areas covered: Herein, the authors review the recent progress made in experimental and computational strategies for addressing the critical challenges with rational discovery of selective multi-targeted agents within the context of polypharmacological modelling. Specific focus is placed on multi-targeted mono-therapies, although examples of combinatorial polytherapies are also covered as an important part of the polypharmacology paradigm. The authors focus mainly on anti-cancer treatment applications, where polypharmacology is playing a key role in determining the efficacy-toxicity trade-off of multi-targeting strategies. Expert opinion: Even though it is widely appreciated that complex polypharmacological interactions can contribute both to therapeutic and adverse side-effects, systematic approaches for improving this balance by means of integrated experimental-computational strategies are still lacking. Future developments will be needed for comprehensive collection and harmonization of systems-wide target selectivity data, enabling better utilization and control for multi-targeted activities in the drug development process. Additional areas of future developments include model-based strategies for drug combination screening and improved pre-clinical validation options with animal models.

KEYWORDS:

Polypharmacology; computational models; data resources; drug combination therapies; drug repositioning; efficacy-toxicity ratio; multi-target drug design; profiling strategies; screening libraries; web-tools

PMID:
29233023
DOI:
10.1080/17460441.2018.1413089
[Indexed for MEDLINE]

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