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Case Study: Agios Uses NLP to Innovate and Accelerate Drug Discovery Pipelines

Case Study: Agios Uses NLP to Innovate and Accelerate Drug Discovery Pipelines

This case study outlines how our Linguamatics NLP platform allowed Agios Pharmaceuticals to innovate and accelerate drug discovery pipelines.

  • Situation: Agios wanted to rapidly identify suitable tool compounds to use in its chemical genetics screens, and identify pathways and targets for cancer drug discovery. Traditional text searching to find tool compounds with the desired selectivity and potency properties was labour-intensive and inefficient, producing increasingly irrelevant answers, and Agios wanted a better, faster solution. 
  • Solution: Agios decided to use Linguamatics NLP to look for suitable inhibitors and other tool compounds in the published literature. Agios used Linguamatics powerful ontologies, linguistic, and semantic capabilities to find tool compounds with the required efficacy, selectivity and mechanism of action. The resulting tool compounds were run against a panel of tumor cell lines, which highlighted two compounds that inhibited growth in core specific cell lines. After further in-house research and experiments, key responder gene targets were identified, which enabled rapid lead compound discovery.
  • Success: The Linguamatics NLP workflow empowered Agios to drop cumbersome and ineffective traditional search techniques, and to rapidly uncover appropriate tool compounds for use in the chemical genetics screen. Because the located compounds had the desired efficacy, selectivity, and mechanism of action, they were much more likely to be active and to reveal responder genes in the cell line panel. Starting in 2014, this shortened the lead identification phase to 15 months, the optimization phase to four years, and resulted in announcement of an IND submission in Q2 2018. Overall, Agios shaved 3 years from the average time for target identification to clinical trials; and this process is being repeated for other therapeutic areas.  

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