
At SCDM 2024, DFnet’s Director of Quality, Phil Kirsch, joined industry leaders from Memorial Sloan Kettering Cancer Center and Veeva Systems to tackle a big question:
What if clinical research didn’t have to be a one-off, hand-crafted effort?
Standardization has transformed industries—from manufacturing to healthcare—making processes faster, more efficient, and more accessible. Yet, in clinical research, many studies still rely on custom-built setups, limiting scalability and slowing progress.
The panel explored how leveraging standards like CDISC, HL7, and XML-based protocols could:
- Automate study database creation and validation
- Improve data quality through AI-driven anomaly detection
- Speed up clinical trial reporting with AI-assisted analysis
While some organizations have started implementing these ideas, the full potential is still ahead. As AI continues to evolve, integrating better standards and automation will be critical for making clinical research faster, more efficient, and more reliable.
How does DFnet use standardization to make clinical research more effective?
One way is through our prebuilt CDISC modules, which speed up CRF development while supporting standardization—helping teams streamline study setup and ensure data consistency from the start.
DFnet is also actively exploring AI’s role in eClinical solutions. Our development team has conducted extensive research in this space, and we recently hosted a two-day AI-themed user group meeting in Boston to explore how AI can advance clinical research.
Missed the SCDM session? Download the slide deck below.