CASE STUDY

100% Automation and ~$1.34M Savings in Single-cell Data Ops

Key Highlights

  • A US-based cancer diagnostics company sought to leverage proprietary data to identify diagnostic markers for AML.
  • They wanted to streamline their data management workflow, from ingestion, preprocessing, and curation to insight generation, for raw Single Cell Multiome (scRNA + scATAC) data.
  • Major challenges included the lack of templatized solutions for single-cell multiome data ingestion, processing and storage, the large size of each dataset, and the lack of infrastructure to draw effective insights from this data.
  • Elucidata’s partnership offered them a well-rounded solution to their problems by offering customized pipelines, a robust, flexible and scalable compute infrastructure, and a tailor-made web app to support their data workflow end-to-end.
Get your case study now
Please enter only business email ids.
Thank you for showing interest!

To know more about us, book a demo here.
Oops! Something went wrong while submitting the form.

All Case Studies

Case study: Accelerated Target ID using ML-Ready data on Polly

Data Interoperability as a Service: 6X Faster Clinico-Genomic Data Integration & Analysis with Polly

Read More
Case study: Accelerated Target ID using ML-Ready data on Polly

Elucidata Cuts 95% Manual Scientist Effort in Protein Production Workflows

Read More
Case study: Accelerated Target ID using ML-Ready data on Polly

Predicting Spatially Resolved Gene Expression from Histopathology Images

Read More
Case study: Accelerated Target ID using ML-Ready data on Polly

500 Hours Of Data Wrangling Saved While Ensuring Superior Data Quality

Read More
Case study: Accelerated Target ID using ML-Ready data on Polly

80% Faster Data Management & 50% Fewer Data Queries for Academic Core Facilities

Read More
Case study: Accelerated Target ID using ML-Ready data on Polly

Six Months to Success: Accelerating AML Target-indication Assessment With Advanced Knowledge Graphs

Read More
Request Demo