Biostatistics
Dataset analysis, data cleaning, statistical programming, and data extraction from large unstructured sources including EHR and physician notes.
What you get
Statistical analysis plan
Pre-specified methodology document for regulatory and publication purposes
Data cleaning report
Documentation of data quality, transformations, and exclusion criteria
Analysis tables & figures
Publication-ready statistical tables and data visualizations
Clinical-grade analysis
Biostatistical analysis following ICH-GCP standards — from descriptive statistics to advanced modeling and subgroup analysis.
Unstructured data extraction
AI-assisted extraction from EHR systems, physician notes, and registry databases — turning messy data into analyzable datasets.
End-to-end data management
From raw dataset to statistical analysis plan, analysis execution, and publication-ready tables and figures.
About this service
From raw data to publication-ready results
Clinical and real-world datasets are often messy, incomplete, or locked in unstructured formats. We handle the full data pipeline — from cleaning and structuring to statistical analysis and publication-ready output.
Our biostatisticians work with clinical trial data, real-world evidence from EHR systems, patient registries, and medical claims databases. AI-enhanced tools accelerate data extraction from unstructured sources — while statistical expertise ensures rigorous, reproducible analysis.
Every analysis follows a pre-specified statistical analysis plan with documented methodology for regulatory and publication use.
Deliverables
What you get
Statistical analysis plan
Pre-specified methodology document for regulatory and publication purposes
Data cleaning report
Documentation of data quality, transformations, and exclusion criteria
Analysis tables & figures
Publication-ready statistical tables and data visualizations
Subgroup analysis
Pre-specified and exploratory subgroup analyses with appropriate adjustments
Data extraction report
Structured datasets extracted from EHR, registries, or unstructured sources
Statistical programming
SAS, R, or Python code with validation documentation
How we work
Five phases to rigorous analysis
01
Define objectives
Specify research questions, endpoints, and analytical approach.
02
Data preparation
Clean, structure, and validate the dataset for analysis.
03
Statistical analysis
Execute the analysis plan with appropriate methods and quality control.
04
Results generation
Produce publication-ready tables, figures, and summary statistics.
05
Documentation
Deliver analysis report, methodology documentation, and code archive.
AI-enabled workflow
AI-enhanced data extraction, expert-validated analysis
AI accelerates data extraction from unstructured sources and pattern detection. Biostatisticians design the analysis, validate results, and ensure methodological rigor.
What AI does
- Unstructured data extraction from EHR and physician notes
- Pattern detection and data quality screening
- Automated table and figure generation
- Cross-dataset consistency checking
What MAG experts do
- Statistical analysis plan design and methodology
- Analysis execution with appropriate statistical methods
- Results interpretation and clinical contextualization
- Regulatory-compliant documentation and reporting
Evidence Scanner™ modules used
AI-Enhanced EDC
Fact-Checker
Proof
How this service works in practice
Difficult-to-treat RA patient identification: AI-powered mining of unstructured EHR data
Result:Patient identification approach validated and deployed
Rheumatology
Read case →
National epidemiological study: protocol design through data collection and statistical analysis
Result:Replicated in 2 countries, published in peer-reviewed journal
Rare Disease
Read case →
Systematic review with meta-analysis: epidemiological data extraction and statistical pooling
Result:Published, cited 12 times in first year
Infectious Diseases
Read case →
Solves these challenges
Related problems
RWE data exists but was never properly analyzed
Data has been collected but never cleaned, structured, or turned into usable evidence.
See how we solve it →
Competitor data needs independent statistical assessment
Published competitor data needs rigorous re-analysis to assess claims and identify weaknesses.
See how we solve it →
Statistical claims need verification before publication
Every number in a manuscript or dossier must be traceable to a validated analysis.
See how we solve it →
Frequently asked
Common questions
What statistical software do you use?
We work with SAS, R, and Python for statistical programming. All code is documented and validated for regulatory purposes.
Can you handle real-world data?
Yes. We extract and analyze data from EHR systems, patient registries, medical claims databases, and physician notes — including unstructured text data.
Do you write statistical analysis plans?
Yes. We design pre-specified SAPs following ICH-GCP and regulatory guidelines, with appropriate methodology for each research question.
Can you support regulatory submissions?
All analyses include regulatory-compliant documentation — methodology reports, validation documentation, and code archives suitable for submission.
How do you handle data quality issues?
We document all data quality findings, cleaning decisions, and exclusion criteria transparently — with sensitivity analyses where appropriate.
Need data analyzed?
Share your dataset or research question. We’ll propose an analysis approach and timeline.
Book a scoping call →
Browse all services
Need rigorous data analysis?
Send us your dataset or research question. We’ll design the analysis plan and deliver publication-ready results.
AI infrastructure
AI-powered.
Expert-validated.
We built AI workflows into our daily practice — not as a marketing claim, but as the infrastructure that lets our medical experts deliver faster without cutting corners.
Research
Structured PubMed queries with narrative or table outputs
Monitoring
Weekly literature digests by drug, target, or topic
AI-Enhanced EDC
Electronic data capture with AI-assisted quality checks
Fact-Checker
Claim verification against your source documents
AI accelerates. Our experts validate.
Every output goes through expert medical review before it reaches your team. AI handles structure and speed — we handle scientific judgement and MLR readiness.
// EHR data extraction and analysis
extract("ehr_patient_records.json", {
mode: "unstructured_mining",
records: 4200,
output: "structured_dataset + quality_report",
})
Extracting structured data from 4,200 EHR records...
Extraction Report
4,200 records processed. 3,847 valid entries extracted. 12 data fields structured. 353 records flagged for manual review. Missing data: 4.2% overall...