BoyceLab · Clinical Informatics

RWDExchange

Evaluate real-world data exchangeability for use as external comparators in clinical trials.

v3.0

Step 1 of 4

Variable Assessment

Evaluate each candidate variable with six structured exchangeability questions. Add data quality metrics and confounders using the collapsible sections below.

Add New Variable
Exchangeability Questions
📊 Data Quality Metrics (optional)
🔗 Confounders & Analytical Approach (optional)
Assessed Variables
New to RWDExchange?
Open the demo to see the tool pre-loaded with a hypothetical ALS external comparator study — or add your first variable using the form above.
▶ Open the Demo →
Demo data is synthetic · everything runs locally in your browser

Step 2 of 4

Pocock's Criteria

Evaluate the seven criteria for acceptable use of historical controls (Pocock, 1976).

Reference: Pocock SJ. The combination of randomized and historical controls in clinical trials. J Chronic Dis. 1976;29(3):175-88. doi: 10.1016/0021-9681(76)90044-8

Select Variable
🔬
Add variables first

Step 3 of 4

FDA Guidance Assessment

Evaluate alignment with the FDA 2023 guidance on externally controlled trials.

Reference: US FDA. "Considerations for the Design and Conduct of Externally Controlled Trials." February 2023. View guidance ↗

Select Variable
📄
Add variables first

Step 4 of 4

Gray et al. Framework

Eight methodological domains for evidence assessment in studies using external comparators from real-world data.

Reference: Gray CM, Grimson F, Layton D, Pocock S, Kim J. A Framework for Methodological Choice and Evidence Assessment for Studies Using External Comparators from Real-World Data. Drug Saf. 2020;43(7):623-633. doi: 10.1007/s40264-020-00944-1

Select Variable
📐
Add variables first

Export & Summary

Assessment Report

0
Variables
0
Strong Potential
0
Conditional
0
Limited Potential
0
Fully Assessed
Composite Verdicts
📊
No variables yet
Export

Download individual sections or the full combined report. JSON export preserves all data for re-import or sharing.

User Guide

How To Use RWDExchange

About This Tool

RWDExchange provides a structured, multi-framework assessment of whether real-world data can serve as a reliable external comparator in a clinical trial. It implements four complementary frameworks: a variable-level feasibility score, Pocock's seven historical control criteria, FDA 2023 guidance for externally controlled trials, and the Gray et al. (2020) methodological framework — synthesized into a single composite verdict per variable.

All data is stored in your browser via localStorage. Use Export JSON to back up and Share to generate a shareable URL. Try demo.html to see the tool pre-loaded with synthetic data.

Steps
01

Variable Assessment

Add each variable. Answer six exchangeability questions for a 0–6 score. Optionally add data quality metrics (N, % missing, date range) and planned confounders.

02

Pocock's Criteria

Rate each of the seven Pocock criteria. The composite verdict ring updates live as you save.

03

FDA Guidance

Rate alignment with each of the eight 2023 FDA considerations.

04

Gray et al. Framework

Complete the eight methodological domain assessment covering research question fit, population representativeness, confounders, analytical approach, and reproducibility.

05

Report & Export

View composite verdicts and download CSV or JSON exports. Use Share to generate a URL encoding your full session.

Verdict Interpretation
🟢 STRONG (≥70%)

Variable is well-suited as an external comparator. Proceed to study design.

🟡 CONDITIONAL (45–69%)

Usable with documented caveats and sensitivity analyses.

🔴 LIMITED (<45%)

Significant limitations. Consider excluding or flagging as a major uncertainty.

⚪ PRELIMINARY

Variable score only. Complete all three frameworks for a full verdict.

In Development

OMOP Data Scan

🔭

Coming Soon

The OMOP Data Scan will scan OMOP CDM–formatted data using pre-specified concept codes representing the variables assessed in the other modules, enabling automated standardized data characterization for external comparator feasibility.

BETA · IN DEVELOPMENT

Contact: danielle@boycedatascience.com