A purpose-built AI workflow for Clinical Safety & Toxicology teams delivering 99% cost reduction and 95% time reduction per target safety assessment, with citation-accurate, regulatory-grade outputs.
A top-5 pharmaceutical company's Clinical Safety and Toxicology team was spending significant resource on manual literature reviews to extract evidence for target validation and safety profiling. The process was slow, costly and difficult to scale as data volumes grew, creating bottlenecks across multiple research programmes.
Biorelate deployed a purpose-built AI workflow combining NLP with structured biomedical ontologies to extract and normalise safety evidence from millions of publications at scale. Built around the 'Fail Early, Fail Cheap' principle, it surfaces safety signals at the target ID stage and integrates directly with existing workflows.
Biorelate deployed a purpose-built AI workflow combining NLP with structured biomedical ontologies to extract and normalise safety evidence from millions of publications at scale. Built around the 'Fail Early, Fail Cheap' principle, it surfaces safety signals at the target ID stage and integrates directly with existing workflows.
We'll scope a custom Galactic Data workflow for your Clinical Safety & Toxicology team, specific to your target classes and regulatory context.