Ontotext announced the release of Target Discovery, an AI-powered platform that speeds the process of discovering new safe and efficient drug candidates. Target Discovery combines knowledge from public and proprietary data, AI-derived data from scientific publications, patents and clinical trials. It also features analytics for target identification and selection that medical or scientific experts without technical skills. Knowledge graph technology can lower the cost and shorten the time for semantic data integration. It also brings in a new level of insights on top of highly connected data and provides normalized quality data for supporting AI analysis. Benefits include:
- Target Discovery stays up-to-date with the newest discoveries by automatically extracting knowledge from more than 80 million documents, including patents and clinical trials.
- Target Discovery combines all required data, whether public or proprietary, AI-derived or structured in one place. Information is updated regularly and includes a selections from AlphaFold, Open Targets, EMBL.
- One can quickly gain an overview of a disease or target with customizable visual analytics and dashboards over any type of data and source.
- Hidden relationships can be easily uncovered in a network of over 5 billion facts with advanced graph algorithms.
- Transparent insight provenance and evidence.