AI-Powered Clinical Data Analytics
From raw data to regulatory-grade intelligence.
Bracy Analytics transforms complex clinical datasets — from EDC systems, EHRs, and registries — into structured, analysis-ready intelligence engineered for Phase I–IV trials, post-market surveillance, and real-world data programs.
Clinical data is among the most complex, high-stakes data in existence. It arrives from dozens of sources — EDC platforms, lab systems, wearables, EHRs, and external registries — in inconsistent formats, with missing values, protocol deviations, and evolving data dictionaries. Traditional analytics approaches cannot keep pace with the volume or the regulatory demands. Bracy Analytics applies modern AI and machine learning to this problem: automated pipelines that clean, transform, and map data to CDISC standards; statistical models that surface signal from noise; and reporting infrastructure that produces audit-ready outputs at the speed clinical programs require.
What We Deliver
Automated CDISC Data Mapping
Python and R pipelines that transform raw EDC exports into SDTM and ADaM datasets aligned with CDISC standards, with automated validation against CDISC rules and sponsor-defined specifications.
Exploratory & Confirmatory Statistical Analysis
Full statistical analysis support from EDA through confirmatory hypothesis testing — including mixed models, survival analysis, Bayesian methods, and non-parametric approaches.
Integrated Safety & Efficacy Reporting
Automated generation of integrated summary tables, listings, and figures (TLFs) for safety, efficacy, and PK/PD endpoints — formatted for CSR and regulatory submission.
Scalable Cloud-Native Data Pipelines
Cloud-native architectures on AWS, Azure, or GCP that scale with trial size — from single-site Phase I programs to global Phase III studies with thousands of patients and millions of data points.
Data Quality Assessment & Anomaly Detection
ML-powered data quality checks that identify outliers, inconsistencies, and protocol deviations in real time — reducing query burden and improving data integrity before database lock.
Interactive Analytics Dashboards
R Shiny and Streamlit dashboards that give clinical teams real-time visibility into data completeness, safety signals, enrollment trends, and efficacy readouts throughout the trial.
Real-World Applications
A Phase III sponsor needs SDTM and ADaM datasets prepared for NDA submission within 8 weeks of database lock.
Automated CDISC mapping pipelines reduce dataset preparation time by 60%, with full validation documentation ready for FDA review.
A biotech company running a multi-site global trial needs real-time visibility into data completeness and query rates across 40 sites.
Cloud-native monitoring dashboard deployed in 2 weeks, giving the data management team daily visibility and reducing site query resolution time.
A CRO managing 12 concurrent sponsor programs needs to standardize data review processes across diverse therapeutic areas.
Standardized automated data review framework deployed across all programs, reducing manual review time by 50% and improving consistency.
A pharmaceutical company needs integrated safety and efficacy TLFs for a CSR covering a 2,000-patient Phase III study.
Programmatic TLF generation produces all required tables, listings, and figures in regulatory-submission format, with full audit trail.
Ready to Discuss AI-Powered Clinical Data Analytics?
Our team will assess your program context and design a solution scoped to your data environment, regulatory obligations, and timelines.