Large Language Models (LLMs) are rapidly transforming pharmaceutical research, offering unprecedented capabilities across diverse workflows. However, their pervasive adoption introduces a critical challenge: the propensity for fluent AI hallucinations. These outputs often appear grammatically correct and scientifically plausible, yet can be fundamentally inaccurate in ways difficult to detect without a robust, structured ground truth for validation.
At GSK, they are systematically tackling this challenge by embracing semantic grounding. This involves rigorously classifying our data using established ontology classes—transforming unstructured “strings” into well-defined “things”—and replacing ambiguous free-text references to key research entities with persistent Uniform Resource Identifiers (URIs). This presentation will demonstrate why semantic grounding is more than just a data enhancement; it is a fundamental prerequisite for building truly trustworthy and reliable AI systems in pharmaceutical R&D, essential for driving innovation and ensuring data integrity.
Speakers
- Alice Augustine, GSK
- Jim Morris, Progress Software
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