Core Capabilities

Solutions Built for Life Sciences

Six integrated capability areas — each engineered for the data complexity, regulatory rigor, and operational demands of pharmaceutical, biotech, and clinical research organizations.

HomeSolutions
01

AI-Powered Clinical Data Analytics

From raw data to regulatory-grade intelligence.

PharmaceuticalBiotechCROs

Bracy Analytics transforms complex clinical datasets — from EDC systems, EHRs, and registries — into structured, analysis-ready intelligence. Our Python and R-based pipelines are engineered for the rigorous data environments of Phase I–IV trials, post-market surveillance, and real-world data programs.

Key Capabilities
  • Automated data cleaning, transformation, and CDISC mapping (SDTM/ADaM)
  • Exploratory and confirmatory statistical analysis
  • Integrated safety and efficacy reporting
  • Scalable cloud-native data pipelines
02

OncoSentinel™ — Clinical Relapse Risk Stratification

AI-powered cancer relapse prediction. Built for clinical validation and regulatory review.

Oncology PracticesPharmaceuticalAcademic Medical CentersCancer Registries

OncoSentinel™ is Bracy Analytics' flagship predictive ML platform — estimating cancer relapse probability, time-to-relapse, risk category (Low / Moderate / High), and key contributing risk factors for individual patients across cancer types, stages, and treatment histories.

Key Capabilities
  • Relapse probability at 1-year, 3-year, and 5-year intervals
  • Time-to-relapse prediction via survival analysis models
  • Risk stratification with explainable AI factor attribution (SHAP)
  • Multi-algorithm ensemble: Random Forest, XGBoost, DNN, survival models
  • Three-tier clinical validation strategy (internal, external, performance)
03

Clinical Trial Automation

Reduce manual burden. Accelerate time-to-submission.

CROsPharmaceuticalBiotech

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 trial lifecycle.

Key Capabilities
  • Automated data review and discrepancy flagging
  • Programmatic generation of TLFs (Tables, Listings, Figures)
  • Real-time trial monitoring dashboards
  • Automated SAE and deviation tracking
04

Regulatory & Submission Support

AI-assisted submissions built for FDA, EMA, and ICH.

PharmaceuticalBiotech

Streamline the preparation, validation, and submission of regulatory packages with AI-assisted document generation and compliance checking. Our tools are designed around FDA, EMA, and ICH guidelines — reducing review cycles and minimizing submission errors.

Key Capabilities
  • Automated NDA/BLA/MAA package preparation
  • CDISC compliance validation (SDTM, ADaM, Define-XML)
  • AI-assisted clinical study report (CSR) generation
  • Regulatory intelligence and gap analysis
05

Real-World Evidence & Patient Outcomes

Defensible RWE for label expansions and payer submissions.

PharmaceuticalBiotechHealthcare Systems

Harness real-world data from claims, EHRs, patient registries, and wearables to generate evidence that supports label expansions, post-market commitments, and health technology assessments. Rigorous methodology, transparent assumptions, defensible results.

Key Capabilities
  • Comparative effectiveness and outcomes research
  • Propensity score matching and causal inference methods
  • Patient-reported outcome (PRO) analytics
  • HEOR modeling and payer evidence packages
06

NLP for Clinical Documentation

Structured insight from unstructured clinical text.

PharmaceuticalHealthcare SystemsDigital Health

Extract structured, analysis-ready data from unstructured clinical notes, adverse event narratives, medical records, and literature using state-of-the-art natural language processing. Purpose-built for the vocabulary and regulatory context of life sciences.

Key Capabilities
  • Named entity recognition for clinical concepts (MedDRA, SNOMED, ICD)
  • Adverse event narrative coding and signal detection
  • Automated medical record abstraction
  • Literature mining and evidence synthesis
How We Work

A Rigorous Engagement Process

01

Discovery & Scoping

We assess your data environment, program objectives, and regulatory context to define a precise solution scope.

02

Solution Design

Our team architects a Python/R-based solution aligned with your infrastructure, compliance requirements, and timelines.

03

Development & Validation

We build, test, and validate against your specifications — with full documentation for regulatory audit readiness.

04

Deployment & Support

Solutions are deployed to your environment with training, handover documentation, and ongoing support options.

Built On
Python & R
CDISC Aligned
SDTM · ADaM · Define-XML
Regulatory Ready
FDA · EMA · ICH
Cloud Native
AWS · Azure · GCP
Audit Traceable
Full validation documentation
Engage With Us

Discuss Your Program Requirements

Our clinical analytics team works directly with your data scientists, statisticians, and regulatory leads to scope the right solution for your program.

6
Core Capability Areas
FDA EMA ICH
Regulatory Frameworks Supported
Python & R
Native Development Languages
100%
Audit-Ready Deliverables