CASE STUDY

Accelerated Cancer Target ID by 75% with ML & Curated Data

Key Highlights

  • The company aimed to find targets for differentiation therapy for cancers including AML.
  • Data retrieval, harmonization and ML model development are time-consuming.
  • To help the company circumvent the time factor, Elucidata curated an omics data atlas and developed custom pipelines.
  • The company was able to identify two targets in 2-3 months compared to the 1-2 years that it generally takes.
Get your case study now
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

Transforming Academic Core Facilities with Polly: AI-Driven Data Management for Efficiency, Collaboration, and Scalability

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

Driving Breakthroughs in Clinical Research: Polly, the Only Multimodal AI-Ready Platform for New Product Development

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

Real-Time Data Quality Assessment with Elucidata's Polly

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

Elucidata Delivers 100% Automated AAV Genome Sequencing Pipelines at 4X Lower Costs

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

AI-driven Chatbot Optimization: Achieving Human-Level Accuracy and Speed in Data Retrieval

Read More
Request Demo