A leading pharmaceutical company needed to evaluate the toxicity of drug candidates for obesity and diabetes, aiming to de-risk R&D and avoid costly clinical trial failures.
To achieve this, Elucidata helped by aggregating internal and public omics data, developing an NLP model to extract critical information from clinical literature, and harmonizing multi-modal data into a unified framework for efficient analysis.
This saved the company 1000+ hours, avoided ~$6M in failed trial costs, and accelerated time to insight by 4X.
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