Case Studies: Beyond Data Silos, an Intelligent Path to Seamless Trial Oversight.
Accelerating clinical trials requires sophisticated data pipelines and oversight mechanisms to maintain data integrity under strict ICH GCP guidelines. This domain specializes in automating RAW-to-SDTM transformations using intelligent bots and deploying dynamic R Shiny dashboards for end-to-end trial oversight and central statistical monitoring.
Additionally, it addresses complex bioinformatics needs by harmonizing heterogeneous omics data and establishing scalable architectures for advanced analytics, enabling organizations to define and report Quality Tolerance Limits (QTL) effectively.
Case Studies: Clinical R&D & Data Science
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RAW-to-SDTM Pipeline Automation
Challenge: Manual, time-intensive RAW-to-SDTM transformation, prone to mapping errors.
Solution: Intelligent BOTs for automated SDTM domain mapping. ASTRA pipeline integration. CDISC SDTM validation checks.
Results: Accurate and repeatable SDTM transformation. Reduced manual effort. Improved CDISC compliance. -
Control Tower: R Shiny Prototype — Roche
Challenge: Roche needed rapid decision-support for trial operational oversight with fragmented data.
Solution: R Shiny application for end-to-end trial oversight. KRI metrics with visual risk dashboards. Stakeholder-friendly navigation.
Results: Working prototype delivered at Hackathon. Positive client feedback. Enhanced clinical operations decision-making. -
Central Statistical Monitoring
Challenge: Global pharma sponsor facing regulatory scrutiny for trial data integrity under ICH GCP E6(R2). Detect trends, prioritise sites, comply with FDA/EMA. Solution: Automated data checks, dynamic reporting, QC and compliance framework.
Results: 12 high-risk sites detected. 40% reduction in on-site visits. Zero critical findings. -
QTL Reports & Statistical Monitoring
Challenge: Define, monitor, and report Quality Tolerance Limits across clinical studies per ICH GCP E6(R2); no standard tooling.
Solution: Three-stage QTL framework. R Shiny application for threshold determination. Statistical monitoring via JMP; reports to Quorum S3.
Results: 44 Target, 5 SSLL, 1 Determination run completed. Full compliance paper trail. Scalable QTL model using RADAR platform. -
Data Science — SDTM Mapping & Clinical Data Transformation
Challenge: Manual data mapping and code handling in clinical studies — time-consuming and error-prone.
Solution: Intelligent BOTs to identify data sources, apply mapping rules, and transform from cross-walks.
Results: Raw clinical data transformed into SDTM formats. Repeatable and fast. -
Bioinformatics & Data Analytics 1 — ctDNA Drug Combinations
Challenge: Integration of diverse biomarkers (methylation, SNPP, TMB, CNV) for drug combination optimisation.
Solution: In-depth ctDNA analysis. Multi-tiered biomarker assessment. Collaborative workflow with client.
Results: Actionable multi-dimensional biomarkers identified. Advanced understanding of genetic/epigenetic drug resistance. -
Bioinformatics & Data Analytics 2 — Scalable Data Architecture
Challenge: Designing data storage for historical and real-time analytical needs, implementing Slowly Changing Dimensions.
Solution: Star schema design, SCD techniques, layered metrics, ARD integration.
Results: Robust, scalable architecture for advanced analytics and BI. -
Bioinformatics & Data Analytics 3 — Harmonising Omics & Clinical Data
Challenge: Unifying heterogeneous omics and clinical datasets into a standardised framework.
Solution: Data harmonisation strategy, data pipelines, cross-functional collaboration.
Results: Foundational platform established. Clinical and bioinformatics data gap bridged.