IDruggable genome

NEWS: New Model Helps Predict Novel Uses for Current Drugs

Jun 22, 2017

A team of investigators led by scientists at University College London has recently developed a quicker and less expensive method to determine which drugs currently on the market might be useful for treating other ailments. Findings from the new study—published recently in Science Translational Medicine through an article entitled “The druggable genome and support for target identification and validation in drug development”—were generated by mapping results for numerous genome-wide association studies (GWAS) to an updated set of genes encoding drug (and druggable) targets. These potential new development and repurposing opportunities “could be extended by the deployment of genotyping arrays that ensure comprehensive capture of variation in the druggable genome, in larger samples with a broader set of disease data,” the authors wrote.

Developing new drugs to treat human ailments is notoriously slow and costly. Thus pharmaceutical companies are always searching for new drug development techniques. In this new effort, the research team began with the idea various drugs that have passed clinical trials and are now used to treat people for certain ailments might also work to treat some other disorders that have a similar genetic link. If true, such drugs could make it to patients much sooner, because they have already been shown to be safe. All a drug company would have to do is show that the drug helped patients with the second ailment. However, determining which drugs might be good targets is not an easy task.

In an attempt to speed the process along, the investigators turned to databases of information on diseases that have been linked to a genetic cause and other databases of information about drugs currently on the market and the diseases they are meant to treat. They also developed an algorithm to sort the data from the various databases according to the genetic link between a given disease and the drug used to treat it.

“We showed previously that biomarker and disease endpoint associations of single nucleotide polymorphisms (SNPs) in a gene encoding a drug target accurately depict the effect of modifying the same target with a pharmacological agent; others have shown that genomic support for a target is associated with a higher rate of drug development success,” the authors remarked. “To delineate drug development (including repurposing) opportunities arising from this paradigm, we connected complex disease- and biomarker-associated loci from genome-wide association studies (GWAS) to an updated set of genes encoding druggable human proteins, to compounds with bioactivity against these targets and, where these were licensed drugs, to clinical indications. We used this set of genes to inform the design of a new genotyping array, to enable druggable genome-wide association studies for drug target selection and validation in human disease.”

The analysis provided researchers a list of 4,479 potential drug possibilities that were then reviewed by physicians who looked at the possibilities and tossed out those that they knew would not work in the ways envisioned, eventually narrowing the list down to 144 drugs that could be tested to see if they could help patients with the targeted ailments. If so, not only would some patients receive a new therapy much more quickly, but the pharmaceutical company would save millions in development costs.

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