Genomics guided drug re-purposing helps discover new mechanisms of action for diseases and treatments

Harned4tech
24 Jan 2020
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Harned4tech
27 Jan 2020
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Machine learning is currently one of the most important and rapidly evolving topics in computer-aided drug discovery

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Repurposing is an efficient approach to drug development
Data driven and genomics guided drug re-purposing makes it possible to find totally new mechanisms of action that may not have been previously suspect
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Machine learning is currently one of the most important and rapidly evolving topics in computer-aided drug discovery
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Genome Mapping for Individuals


Repurposing is an efficient approach to drug development, as it makes use of existing knowledge on pharmaceuticals and their mechanism(s) of action, thus minimizing the need for much of the preclinical and early safety work required by new chemical entity (NCE) drug discovery and development.

Many bioinformaticians believe that drug repurposing is one potential solution to Eroom’s Law: the observation that the efficiency of drug development halves about every decade.2 Thus, repurposing may offer a systematic approach to increasing the pace of therapeutic development. One of the benefits of drug repurposing is cost reduction; recent estimates suggest that marketing approval through repurposing can cost ∼70% less than that for NCE drug development projects. Drug repurposing is often much faster than NCE drug development: although the time from discovery to regulatory approval of an NCE may require 12 years or longer, repurposing can establish the same task in <6 years, nearly half the conventional time.3


A research study conducted by the Connectivity Map project from Broad Institute of Harvard & MIT based on the advances in genomics set up a systems - based approach to drug repurposing and discovery.

Instead of identifying the targets hit by a particular compound, say through a target-based screen, we can now measure and evaluate the genome-wide perturbation induced by a compound. In the case of the Connectivity Map, this perturbation was determined by transcriptional changes that result from exposing a cell line to a dose of the compound and measuring the changes in the transcriptome relative to untreated controls. 

By measuring all genes at one time, we can obtain a system-wide snapshot of how exposure to a particular drug affects the entire cell line.







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