Study Shows Genetic Support for Drug Targets Could Double Clinical Development Success Rate

NEW YORK (GenomeWeb) – Pursuing drug targets that have supporting genetic evidence could double the clinical development success rate, according to researchers led by GlaxoSmithKline’s Philippe Sanseau.

More than half of clinical trials fail because the drugs are not effective, and drawing on genes that have been linked to disease could help inform the drug target selection process and make it more successful.

As Sanseau and his colleagues reported in Nature Genetics today, they examined how known genetic associations predict drug mechanisms as well as how well drug mechanisms that have genetic support fare through the drug development pipeline.

Overall, we estimate that drug mechanisms with genetic support would succeed twice as often as those without it (from phase I to approval),” Sanseau and his colleagues wrote in their paper. “Therefore, increasing the proportion of discovery and development activities focused on targets with genetic support and allowing genetic data to guide selection of the most appropriate indications should lead to lower rates of failure due to lack of efficacy in clinical development.”

To make these comparisons, the researchers amassed a set of gene-trait associations and of drug target-indication associations.

They mapped common variant genetic associations housed in GWASdb and rare, Mendelian traits from the Online Mendelian Inheritance in Man (OMIM) database to Medical Subject Heading (MeSH) terms to come up with a set of 16,459 gene-trait combinations. Similarly, by drawing on drug development data in the Informa Pharmaprojects database, they developed a set of 19,085 target-indication pairs.

Sanseau and his colleagues noted that the target genes for drugs approved in the United States or the European Union — which was how the researchers defined a ‘successful drug mechanism’ — were enriched among genes associated with human trait variation.

The greatest enrichment, they noted, was among genes from OMIM, as 206 out of 389 target genes for approved drugs were also associated with a Mendelian trait. Genes linked to disease through a genome-wide association study were also enriched, though to a lesser degree.

Some 61 percent of approved drug indications had at least one genetic association with a related trait, the researchers reported. In addition, about 40 percent of approved indications had at least five reported associations.

The researchers noted that the drug indications that had fewer than five genetic associations encompassed both conditions that have been studied with little success as well as under-studied conditions.

Sanseau and his colleagues focused on a subset of 158 approved drug indications with at least five genetic associations to a similar trait — which the researchers took to mean that the indication has been fairly well studied using genetic approaches — to examine the support that such an association provides for the drug mechanism.

Sixty-seven of 820 target-indication pairs were supported by one or more genetic associations, they reported.

The portion of target-indication pairs with genetic evidence increased along the drug-development pipeline, suggesting to the researchers that genetic associations predict successful mechanisms of action.

The percentage of target-indication pairs with genetic evidence was lowest for those in phase I trials, but increased to 8.2 percent for approved drugs. This, the researchers noted, is a four-fold increase and indicates that the odds of successful drug mechanisms with genetic support is many times higher than without.

This genetic support had the largest influence on the transition from a phase II clinical trial to a phase III clinical trial, but had the least influence on progressing from phase III to approved drug status. This, the researchers noted, could be because failures at phase III differ from earlier ones — they could reflect a failure to improve upon the current standard of care rather than targeting a biological mechanism that was not actually disease causing.

Sanseau and his colleagues note that their attempt to map all possible causal genes could have inflated the proportion of successful drug mechanisms with genetic support. At the same time, as functional genomic data is limited, causal relationships could have been missed, skewing the enrichment estimates in the other direction.

Still, “[w]e estimate that selecting genetically supported targets could double the success rate in clinical development,” the researchers said. “Therefore, using the growing wealth of human genetic data to select the best targets and indications should have a measurable impact on the successful development of new drugs.”

Source: https://www.genomeweb.com/drug-discovery-development/study-shows-genetic-support-drug-targets-could-double-clinical

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