Pharma-AI Collaboration Drives ~$3M Cost Reduction by Using Highly Curated Public Data

CASE STUDY

Pharma-AI Collaboration Drives ~$3M Cost Reduction by Using Highly Curated Public Data

Key Highlights

A leading genomics-based drug discovery company wanted to accelerate the identification of putative targets across immunological diseases and cancer by complementing their research with publicly available data.
The highly curated data on Elucidata’s Public OmixAtlas played a pivotal role in helping pharma company identify 1 target for an immunology group in just 6 months, as compared to the usual time period of 2-3 years.
The partnership helped de-risk advancement to phase II leading to lower trial costs there by saving ~ $3M. It also worked in favor of saving time of R&D and bioinformatics personnel by freeing up ~2000 hours annually.

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