Abstract

This chapter focuses on the basic elements of computational drug repositioning and overviews the various in silico, in vivo, and in vitro approaches. It describes the use of Systematic Drug Repositioning (SDR) technologies to predict hitherto unknown adverse drug reactions (ADRs), or to derive mechanistic explanations of known ADRs. The chapter discusses the intellectual property (IP) and commercial aspects of SDR, which are among the major factors that will determine its success. It shows that Pirlindol is neuroprotective in MOG-induced experimental allergic encephalomyelitis, a mouse model of progressive multiple sclerosis (MS). The chapter identifies the risk factors that may increase an individual's susceptibility to this ADR. It illustrates a process through which computational drug repositioning methods can suggest mechanistic hypotheses that can help explain an ADR and propose modifiable risk factors. While computational SDR uses the mechanism of action of the drugs under study to identify novel indications, in vitro/in vivo screening uses the opposite approach.

Keywords:
Drug Medicine Pharmacology

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Topics

Computational Drug Discovery Methods
Physical Sciences →  Computer Science →  Computational Theory and Mathematics
Plant-based Medicinal Research
Life Sciences →  Pharmacology, Toxicology and Pharmaceutics →  Pharmacology
Pharmacogenetics and Drug Metabolism
Life Sciences →  Pharmacology, Toxicology and Pharmaceutics →  Pharmacology

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