Case Study: a biopharma company predicts spatially resolved gene expression faster and more cost-effectively with Elucidata

a biopharma company reduces spatial transcriptomics costs by 40% with Elucidata

A biopharma company faced the challenge of high costs and long timelines associated with using spatial transcriptomics experiments for biomarker analysis. They partnered with Elucidata to find a more scalable and cost-effective solution using AI.

Elucidata developed an AI model that predicts spatially resolved gene expression directly from histopathology images. This solution, which leveraged a CLIP-like contrastive learning framework, reduced the need for costly experiments. The model achieved a 0.41 Spearman's correlation and successfully predicted out-of-distribution genes. For the customer, Elucidata's implementation reduced experimental costs by 40% and accelerated biomarker analysis timelines by four times, speeding the process from months down to weeks.

Biopharma Company