A global biopharma used the Tetra platform to automate CRO data ingestion and screening data handling for biologics R&D.
The company wanted to speed biologics discovery and development and time-to-insight. It used the Tetra Scientific Data and AI platform to automate CRO data ingestion, remove manual data cleansing, accelerate .CZI image processing and streamline high-throughput screening workflows. The page gives no figures.
TetraScience is a scientific data company that centralises and harmonises lab instrument and partner data into AI-ready form for pharma R&D.
This sits in the Data Providers stage of the AI use-case lifecycle: Named examples from the real-world-data, claims and competitive-intelligence providers pharma AI systems are trained on, benchmarked against, or run inside of.
Published by TetraScience on its own site — read the original case study on tetrascience.com ↗
Note: Page gives no quantified results.
Related use cases
- 01Bayer expanded TetraScience's Scientific Data Foundry across pharma and crop science R&D to harmonise lab and CRO/CDMO data.
- 02How Bioventus evolved their commercial strategy with real world data and intelligence
- 03Clarivate and CLEO diagnostics are making early detection of ovarian cancer a reality
- 04Making informed investment decisions (Attracting breakthrough innovations from academic research) - SPRIND case study
- 05Gedeon Richter — Case study | Clarivate Regulatory Intelligence Tracking Application
- 06Integrating patient centricity into the Menarini mature brand strategy for commercial excellence