Novel Genetic Priority Score Unveiled to Enhance Target Prioritization in Drug Development
Innovative approach integrates genetic data to identify drug targets with high potential for clinical trial success
Researchers optimized drug target prioritization to increase odds of clinical trial success by integrating diverse human genetic data through a computational score. Credit: Lab of Ron Do, PhD.
Driven by the need for a better way to prioritize targets for drug development, the Icahn School of Medicine at Mount Sinai has led the development of a novel “genetic priority score” (GPS) that will integrate various types of human genetic data into a single easy-to-interpret score.
The findings were described in the January 3 online issue of Nature Genetics [DOI: 10.1038/s41588-023-01609-2].
Studies have shown that drugs have an increased likelihood of success in clinical trials when the genes they target have been demonstrated to have genetic support. The new tool integrates multiple lines of genetic evidence to prioritize these drug targets.
The score measures the general ability of a gene to be targeted by drugs; genes with a high score in the new tool are more likely to succeed as a drug target. The score identifies both known drug gene targets as well as potential novel therapeutic targets.
“We built a genetic priority score that was inspired by the realization that diverse human genetic data provides insights into drug targets, yet there was an absence of a cohesive strategy for integrating these various data types into an easily interpretable score. So we developed a computational score to prioritize drug targets for enhanced drug discovery," says Ron Do, PhD, senior study author and the Charles Bronfman Professor in Personalized Medicine at Icahn Mount Sinai. “Remarkably, several genes with high GPS were already known to be targeted by approved drugs, providing validation for the new tool.”
The GPS, with its potential to streamline target prioritization, is positioned to have a significant impact on drug development. It offers a valuable resource for researchers seeking to optimize the selection of drug gene targets for enhanced efficiency in the drug development process, say the investigators.
“The rising cost of developing therapeutics, in the billions, is primarily due to high clinical trial failures, underscoring inefficiencies in drug development pipelines. Improving early-stage target prioritization is critical. Studies consistently show that drug indications with human genetic support are more likely to succeed in trials and gain approval,” says study first author Áine Duffy, a PhD candidate in the lab of Dr. Do.
The researchers are encouraged by the developments but emphasize this represents only a first step for prioritization and the need for careful follow-up and further investigation of gene targets with high scores. Next, the investigators plan to refine the model by incorporating additional genetic features and evaluating more sophisticated algorithms for constructing the GPS.
The paper is titled “Development of a human genetics-guided priority score for 19,365 genes and 399 drug indications.” Please see [DOI:10.1038/s41588-023-01609-2] to view competing interests.
The remaining authors, all with Icahn Mount Sinai except where indicated, are Ben Omega Petrazzini (Associate Bioinformatician); David Stein (PhD candidate); Joshua K. Park (MD/PhD candidate); Iain S. Forrest, PhD (and MD candidate); Kyle Gibson (MD candidate); Ha My Vy, PhD; Robert Chen Park (MD/PhD candidate); Carla Márquez-Luna, PhD; Matthew Mort, PhD (Cardiff University, UK); Marie Verbanck, PhD (Université Paris Cité and Icahn Mount Sinai); Avner Schlessinger, PhD; Yuval Itan, PhD; David N. Cooper, PhD (Cardiff University, UK), Ghislain Rocheleau, PhD; and Daniel M. Jordan, PhD.
The study was funded by the following: the NIH T32 Postdoctoral Research Award (5T32HL00782424); the National Institute of General Medical Sciences of the NIH (R35-GM124836); the National Heart, Lung and Blood Institute of the NIH (R01-HL139865) and (R01-HL155915); the French National Research Agency (ANR) (ANR-21-CE45-0023-01); the Leducq Foundation (21CVD01); The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai; and the Helmsley Foundation Award (2209-05535).
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