Clinical Trial Automation
Reduce manual burden. Accelerate time-to-submission.
Automate the data collection, monitoring, and reporting workflows that slow clinical programs. Our automation frameworks integrate with leading EDC, CTMS, and eTMF platforms to eliminate redundant manual processes across the full trial lifecycle.
Clinical trial programming is one of the most labor-intensive processes in drug development — and one of the most amenable to intelligent automation. SDTM and ADaM dataset construction, Define.xml generation, data review checks, TLF programming, and submission readiness tracking all follow predictable, rule-based logic that can be automated without sacrificing quality. Bracy Analytics has built a suite of automation tools that apply AI-assisted programming recommendations, metadata-driven utilities, and programmatic validation to compress timelines and reduce error rates across the trial data lifecycle. The result is faster submissions, lower programming costs, and more time for statisticians and programmers to focus on the work that requires human judgment.
What We Deliver
Automated SDTM & ADaM Dataset Validation
Programmatic validation of SDTM and ADaM datasets against CDISC rules, FDA/PMDA validator requirements, and sponsor-defined specifications — with automated issue reporting and resolution tracking.
Define.xml Generation & Compliance Checking
Automated generation of Define.xml files from metadata repositories, with compliance checking against CDISC Define-XML 2.1 standards and submission-ready formatting.
Automated Data Review & Discrepancy Management
Rule-based and ML-assisted data review checks that flag discrepancies, protocol deviations, and data quality issues — integrated with EDC query workflows for efficient resolution.
AI-Assisted Programming Recommendations
AI tools that analyze data specifications and historical programming patterns to recommend SDTM/ADaM mapping logic, variable derivations, and programming approaches — accelerating programmer productivity.
Metadata-Driven Programming Utilities
Metadata-driven frameworks that generate dataset shells, variable labels, and programming templates from annotated CRFs and data specifications — reducing manual setup time.
Submission Readiness Tracking
Real-time dashboards that track submission readiness across all datasets, validation checks, and documentation requirements — giving project managers clear visibility into submission timelines.
Real-World Applications
A pharmaceutical company needs to prepare SDTM and ADaM datasets for 15 studies in an NDA submission within a compressed timeline.
Automated validation and metadata-driven programming utilities reduce dataset preparation time by 55%, with all validation issues tracked and resolved programmatically.
A CRO managing multiple concurrent sponsor programs needs to standardize CDISC programming processes across diverse data environments.
Standardized metadata-driven framework deployed across all programs, enabling consistent CDISC mapping regardless of EDC platform or therapeutic area.
A biotech company needs Define.xml files generated for a BLA submission with tight timelines and limited internal programming resources.
Automated Define.xml generation from existing metadata produces compliant files in hours rather than days, freeing programmers for higher-value tasks.
A sponsor needs real-time visibility into data review status and query resolution rates across 25 global sites.
Automated data review dashboard deployed, providing daily site-level visibility and reducing average query resolution time from 12 days to 5 days.
Ready to Discuss Clinical Trial Automation?
Our team will assess your program context and design a solution scoped to your data environment, regulatory obligations, and timelines.