CASE STUDY

Elucidata Transforms RNAi Drug Discovery: 2X Faster Gene ID & Cell Annotation

A Cambridge-based RNA interference (RNAi) therapeutics company is developing precision medicine for rare genetic diseases by silencing specific genes linked to these conditions. They collaborated with Elucidata for high-quality AI-ready public datasets, along with a pipeline for re-annotation of scRNASeq datasets.
To achieve their goals of predicting genes for RNAi drug development, customers required access to high-quality single-cell datasets from humans, mice, and macaques. They faced challenges in finding and managing these datasets due to time-consuming searches, low quality, and inaccurate cell type identification, both in public repositories and in-house.
Elucidata assisted them in retrieving high-quality, AI-ready single-cell datasets that are needed to eradicate the affected gene present only in the affected cells. We also developed a pipeline to analyze these datasets for identifying genes linked to disease progression or drug delivery.
We delivered high-quality, AI-ready datasets that were consistently processed, curated, and annotated for cell types based on their reference markers, with human-in-the-loop validation. Resulted in 2X faster identification of ranked potential target genes and 1.8M cells harmonized, 5 tissues, 3 organisms, 43 datasets.

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