Exposure bracketing is a widely used strategy in clinical pharmacology to optimize dosing for targeted patient populations. In many programs, these brackets must be extrapolated from prior human and animal studies to define the minimum and maximum safe and efficacious dose ranges for a given therapy and treatment paradigm.

Traditionally, this requires a labor-intensive and time-consuming review of internal and external studies to manually extract the necessary PK/PD data. Recent advances in artificial intelligence (AI) now provide a compelling alternative: automating the ingestion of large volumes of unstructured data from reports, presentations, and publications and transforming them into analysis-ready datasets.

Watch the on-demand recording of our webinar for an in-depth discussion on how emerging AI techniques, such as prompt chaining, can streamline and scale data aggregation in clinical pharmacology workflows.

Complete the form to access the recording.