Clinical Trial Statistical Analysis Made Simple
Transform complex medical research data into regulatory-ready insights with AI-powered biostatistical analysis tools designed for healthcare professionals.
Picture this: You're three months into a Phase III trial with 2,847 patients across 47 sites. The data is pouring in, the regulatory deadline is approaching, and your biostatistician just went on maternity leave. Sound familiar? Clinical trial statistical analysis doesn't have to be a nightmare of complex formulas and sleepless nights.
With Sourcetable's AI-powered analysis tools, you can tackle everything from survival analysis to interim monitoring with the confidence of a seasoned biostatistician—even if you're more comfortable with clinical protocols than p-values.
Why Healthcare Teams Choose Sourcetable
From protocol design to regulatory submission, streamline every aspect of your clinical trial analysis
Regulatory-Ready Reports
Generate FDA and EMA compliant statistical reports with automated formatting, proper citations, and audit trails that satisfy the most stringent regulatory requirements.
Real-Time Safety Monitoring
Set up automated safety monitoring dashboards that flag adverse events, track stopping rules, and generate DSMB reports without manual intervention.
Advanced Biostatistics
Perform complex analyses including Kaplan-Meier survival curves, Cox regression, mixed-effects models, and adaptive design statistics with simple natural language commands.
Multi-Site Data Integration
Seamlessly combine data from multiple clinical sites, handle missing data patterns, and maintain data integrity across different EDC systems and formats.
Protocol Deviation Analysis
Automatically identify and analyze protocol deviations, assess their impact on primary endpoints, and generate deviation summary reports for regulatory submissions.
Sample Size Calculations
Calculate and adjust sample sizes based on interim analyses, perform power calculations for various endpoints, and model different dropout scenarios.
Your Clinical Trial Analysis Workflow, Simplified
From raw patient data to publication-ready results in four streamlined steps
Import Multi-Source Data
Connect your EDC system, laboratory databases, and imaging repositories. The platform automatically maps variables, handles different data formats, and creates a unified analysis dataset while maintaining full audit trails.
Define Analysis Plan
Upload your Statistical Analysis Plan (SAP) and let AI suggest appropriate statistical tests, identify primary and secondary endpoints, and set up interim analysis timepoints with proper alpha spending functions.
Run Automated Analysis
Execute complex biostatistical analyses with natural language commands. Generate survival curves, perform subgroup analyses, calculate treatment effects, and assess heterogeneity across study sites.
Generate Regulatory Reports
Produce FDA-compliant Clinical Study Reports, create tables/listings/figures (TLFs), and export results in CTD-ready formats with proper version control and electronic signatures.
Clinical Trial Analysis in Action
See how research teams are using Sourcetable to accelerate their statistical analysis workflows
Oncology Phase III Efficacy Analysis
A multinational cancer trial with 1,200 patients needed to analyze overall survival as the primary endpoint. Using Sourcetable, the team created Kaplan-Meier curves stratified by biomarker status, performed Cox proportional hazards regression with 15 covariates, and generated forest plots for subgroup analyses—all completed in 2 hours instead of 2 weeks.
Cardiovascular Safety Monitoring
A Phase II cardiac device trial required real-time safety monitoring with pre-specified stopping rules. The system automatically flagged when the composite safety endpoint exceeded the boundary (3 events vs. expected 1.2), triggered DSMB notifications, and generated safety run charts updated daily with new patient data.
Pediatric PK/PD Analysis
A rare disease study in children needed population pharmacokinetic modeling with sparse sampling. The platform handled mixed-effects modeling, generated individual and population parameter estimates, created diagnostic plots, and simulated dosing scenarios for different age groups—critical for determining pediatric dosing recommendations.
Adaptive Design Interim Analysis
A Phase IIb dose-finding study used group sequential design with two interim analyses. The system calculated conditional power, performed futility analysis, generated recommendations for sample size re-estimation, and maintained blinding throughout the adaptive modifications.
Biomarker Validation Study
A companion diagnostic development required ROC analysis, sensitivity/specificity calculations, and positive/negative predictive values across different cut-points. The analysis included bootstrapped confidence intervals, cross-validation procedures, and comparison of multiple biomarker models.
Multi-Regional Regulatory Submission
A global Phase III program needed consistent analyses across FDA, EMA, and PMDA requirements. The platform generated region-specific efficacy tables, safety summaries, and statistical appendices while maintaining consistency in the core statistical methodology and handling different regulatory preferences.
Advanced Statistical Methods for Clinical Trials
Clinical trials demand sophisticated statistical approaches that go far beyond basic hypothesis testing. Here's how Sourcetable handles the complex methodologies that regulatory agencies expect:
Survival Analysis and Time-to-Event
When analyzing time-to-event endpoints like overall survival or progression-free survival, traditional spreadsheet tools fall short. Sourcetable automatically handles censored observations, generates publication-quality Kaplan-Meier curves, and performs log-rank tests with stratification factors. Need to adjust for baseline covariates? Cox proportional hazards regression is just a natural language query away: "Create a Cox model for overall survival adjusting for age, gender, and ECOG status".
Mixed-Effects Models for Longitudinal Data
Patient measurements over time create correlated data that requires specialized handling. Whether you're analyzing repeated laboratory values, patient-reported outcomes, or pharmacokinetic profiles, Sourcetable's mixed-effects modeling capabilities account for within-patient correlation while handling missing data patterns that inevitably occur in clinical trials.
Multiplicity Adjustments
Multiple comparisons are the norm in clinical trials—multiple doses, multiple endpoints, multiple subgroups. The platform automatically applies appropriate correction methods (Bonferroni, Holm, Benjamini-Hochberg) and implements complex hierarchical testing procedures that maintain overall Type I error control while maximizing statistical power.
Adaptive Design Support
Modern trials increasingly use adaptive designs that modify aspects of the study based on interim data. Sourcetable supports group sequential designs with proper alpha spending functions, sample size re-estimation procedures, and dose-escalation algorithms while maintaining the integrity of statistical inference.
Meeting Regulatory Standards
Regulatory compliance isn't just about getting the statistics right—it's about demonstrating that your analysis methods are appropriate, well-documented, and reproducible. Here's how Sourcetable ensures your submissions meet the highest standards:
21 CFR Part 11 Compliance
Every analysis step is logged with user identification, timestamps, and audit trails. Electronic signatures ensure data integrity, and version control prevents unauthorized modifications. The system maintains complete documentation from raw data through final results, satisfying FDA requirements for electronic records.
ICH E9 Statistical Principles
The platform enforces ICH E9 guidelines by requiring pre-specification of analysis methods, maintaining separation between planned and exploratory analyses, and documenting any deviations from the original Statistical Analysis Plan. Missing data handling follows ICH E9(R1) estimand framework principles.
CDISC Standards Integration
Import data directly from CDISC SDTM domains and generate analysis datasets following ADaM standards. The system automatically creates ADSL (subject-level), ADTTE (time-to-event), and ADLB (laboratory) datasets with proper variable naming, labeling, and metadata.
Frequently Asked Questions
How does Sourcetable handle missing data in clinical trials?
Sourcetable implements multiple imputation methods appropriate for clinical trial data, including LOCF (Last Observation Carried Forward), mixed-effects models for repeated measures (MMRM), and pattern mixture models. The system follows ICH E9(R1) estimand principles, allowing you to specify the treatment policy for handling intercurrent events like treatment discontinuation, rescue medication use, or protocol deviations.
Can I import data directly from my Electronic Data Capture (EDC) system?
Yes, Sourcetable connects to major EDC systems including Medidata Rave, Oracle Clinical, and REDCap. The platform automatically maps EDC variables to analysis datasets, handles data formats and coding differences, and maintains audit trails showing data lineage from source to analysis. CDISC SDTM and ADaM standards are fully supported.
What about interim analyses and Data Safety Monitoring Board (DSMB) reports?
The platform supports group sequential designs with pre-specified stopping boundaries using Lan-DeMets alpha spending functions. You can set up automated monitoring for safety endpoints, efficacy boundaries, and futility stopping rules. DSMB reports are generated automatically with unblinded treatment comparisons while maintaining blinding for the study team.
How do I ensure my analysis meets FDA and EMA requirements?
Sourcetable follows regulatory guidance documents including FDA's Statistical Review Template and EMA's Guideline on Clinical Trials. The system generates regulatory-compliant outputs including Tables, Listings, and Figures (TLFs), Clinical Study Report sections, and analysis dataset documentation. All analyses include proper statistical methodology descriptions and assumption checking.
Can the platform handle complex statistical methods like survival analysis?
Absolutely. Sourcetable includes comprehensive survival analysis capabilities: Kaplan-Meier estimation with confidence intervals, log-rank tests (stratified and unstratified), Cox proportional hazards regression, accelerated failure time models, and competing risks analysis. The system automatically handles censored observations and generates publication-quality survival curves.
What about sample size calculations and power analysis?
The platform includes sample size calculators for common clinical trial designs: superiority, non-inferiority, and equivalence trials. You can calculate power for continuous and binary endpoints, time-to-event analyses, and crossover designs. The system also supports adaptive sample size re-estimation based on blinded or unblinded interim data reviews.
How does version control work for Statistical Analysis Plans?
Sourcetable maintains complete version history of your Statistical Analysis Plan with change tracking, approval workflows, and electronic signatures. Any modifications to planned analyses are documented with rationale and timestamps. The system clearly distinguishes between pre-specified analyses and post-hoc exploratory analyses in all outputs.
Can I collaborate with biostatisticians and clinical teams?
Yes, the platform supports role-based access with different permission levels for clinicians, biostatisticians, data managers, and regulatory affairs teams. Real-time collaboration features allow multiple users to review analyses, add comments, and approve results. All interactions are logged for audit purposes.
Frequently Asked Questions
If you question is not covered here, you can contact our team.
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Transform Your Clinical Trial Analytics
Join research teams worldwide who trust Sourcetable for regulatory-compliant statistical analysis