Unlocking Efficiency in Clinical Trials with GenAI
Modern clinical trials are increasingly complex, generating vast amounts of unstructured data that require significant manual effort to process. GenAI offers a breakthrough in automating data abstraction, reducing workload, and enhancing accuracy.
Key highlights from this white paper:
- High Accuracy in Data Extraction: GenAI models achieved over 90% accuracy in extracting key clinical concepts from unstructured data sources such as electronic medical records (EMRs), lab reports, adverse events, and more.
- Significant Time Savings: GenAI-driven automation reduced data extraction time from three minutes per data point to less than one second each, delivering substantial operational efficiencies over the course of a trial.
- Improved Data Quality: With formatting aligned to Clinical Data Acquisition Standards Harmonization (CDASH) specifications, GenAI ensures consistent and reliable data for downstream clinical applications.
- Reduced Manual Effort: Automating data abstraction minimizes the burden on clinical research staff, allowing them to focus on higher-value tasks.
- Scalable and Flexible Implementation: GenAI models can be adapted to different trial designs and data formats with layered prompt engineering techniques, enhancing applicability across diverse studies.
- Cost Efficiency: GenAI-enabled automation may reduce clinical trial costs associated with data validation and monitoring.
Read this white paper to see how GenAI is transforming clinical workflows, helping organizations extract data from the complex, unstructured sources produced by trials.
