Clinical Trial Workflow and Data Integration

This page describes the end-to-end workflow for acne severity assessment in a clinical trial using the Legit.Health platform, from protocol design through to EDC data delivery.

Workflow overview

The clinical trial workflow consists of eight stages:

Protocol design: Configure the study with Legit.Health
Site setup: Deploy the platform to investigator sites
Patient enrollment: Register patients in the platform
Image capture: Guided smartphone photography at the site
AI scoring: Automated endpoint calculation
Report review: Investigator reviews the severity report
Severity tracking: Longitudinal score monitoring
Data export: Structured delivery to EDC systems

1. Protocol design

Before the study begins, Legit.Health works with the sponsor or CRO to configure the study protocol:

Configuration item	Options	Example
Imaging perspectives	2-perspective diagonal, 3-perspective perpendicular, custom	2 perspectives (Hayashi Criterion)
Endpoints	Lesion count, density, IGA, ALADIN (any combination)	Lesion count + IGA (co-primary) + density (exploratory)
Global aggregation	Maximum, sum, or mean of local scores	Maximum (default)
DIQA threshold	Strict (pivotal) or lenient (RWE)	Strict for Phase III
Data export format	API, CSV, CRF-mapped fields	CRF-mapped to sponsor’s EDC

A study-specific investigator manual is generated for each trial, providing site personnel with step-by-step instructions, example images, and a knowledge test to confirm training.

2. Site setup

The Legit.Health clinical trials platform is deployed as a web application accessible from any browser. Each investigator site receives:

Login credentials for all study personnel
Pre-configured protocol (perspectives, endpoints, scoring method)
Investigator manual (digital, accessible from the platform)
Training resources and knowledge test

No hardware installation is required; investigators use their existing smartphones for image capture.

3. Patient enrollment

After enrolling a patient in the study per the clinical protocol, the investigator creates the patient record in the Legit.Health platform:

Add new

Select the condition

Select the body area(s)

Select the most common

Face

Do you want to track this condition?

In follow up

Add condition

Each patient is identified by a study-specific pseudonymised identifier; no personal data (name, date of birth) is stored in the platform.

4. Image capture

The investigator captures photographs of the patient's face using the Legit.Health mobile application:

The application provides:

Perspective guidance: Visual silhouettes showing the required capture angle for each perspective
Real-time DIQA quality check: The image is evaluated for focus, lighting, framing, and resolution immediately after capture
Immediate feedback: If the image fails quality standards, the investigator is prompted to recapture with specific guidance
Confirmation: Once all perspectives pass quality checks, the images are submitted for AI processing

For the standard 2-perspective protocol, the entire capture process takes approximately 30–60 seconds.

5. AI scoring

Once images are submitted, the AI processes them automatically. Processing takes approximately ~1.2 seconds for 2 images combined. The system produces:

Per-lesion bounding box detection (inflammatory lesions: papules, pustules, nodules)
Lesion count ( $N$ ) per perspective
Spatial density ( $D$ ) per perspective
IGA score per perspective (local) and global
ALADIN composite score per perspective (local) and global
DIQA quality score per image

The report is immediately available for the investigator to review.

6. Report review

The investigator reviews the severity report directly in the platform. The report includes:

Global scores: IGA (0–4) and ALADIN (0–10), with severity classification
Per-perspective breakdown: Lesion count, density, and local scores for each perspective, with annotated images showing bounding boxes around detected lesions
Image quality: DIQA score for each captured image

The investigator can verify that the AI's detections align with their clinical observation. If the images are inadequate, the investigator can recapture and resubmit; only the latest submission for each visit is retained.

7. Severity tracking

For follow-up visits, the platform tracks severity evolution across all assessments for the patient:

This longitudinal view enables:

Visual comparison of scores over time
Treatment response identification: clear trends in score improvement or worsening
Protocol adherence monitoring: verify that assessments are captured at the correct visit intervals
Automated charting of the severity trajectory for clinical review

8. Data export and EDC integration

Assessment results are structured for integration with the sponsor's EDC (Electronic Data Capture) system.

Exported data fields

Field	Description	Format
Patient identifier	Study-specific pseudonymised ID	String
Visit date	Date and timestamp of the assessment	ISO 8601
Global IGA score	IGA severity (0–4)	Integer
Global ALADIN score	Composite severity (0–10)	Float
Global lesion count	Total inflammatory lesions (deduplicated across perspectives)	Integer
Per-perspective IGA	Local IGA score for each perspective	Integer
Per-perspective lesion count	Lesions detected per perspective	Integer
Per-perspective density	Spatial density per perspective	Float (0–1)
DIQA scores	Image quality score per perspective	Float
Severity classification	Clear / Almost clear / Mild / Moderate / Severe	String

Integration methods

API-based: Automated data flow from the Legit.Health platform to the sponsor’s EDC system via RESTful API
CSV export: Structured CSV files for manual import into EDC systems
CRF field mapping: Data fields pre-mapped to the sponsor’s Case Report Form structure, configured during protocol design
QuantifiCare platform integration: For studies using the combined QuantifiCare + Legit.Health solution, scoring data flows through QuantifiCare’s platform to the sponsor’s data management system

All exported data is structured for direct mapping to CRF fields in standard EDC systems (Medidata Rave, Veeva Vault CDMS, Oracle InForm, etc.).

The integration is API-based and system-agnostic; it works with any EDC system (Medidata Rave, Oracle InForm, Veeva Vault EDC, and others). Export formats include RESTful API, CSV/Excel, and structured JSON. Legit.Health provides IQ/OQ validation documentation and data mapping specifications to support the sponsor's integration validation activities.

Decentralised and hybrid trial support

Hybrid designs

Some study designs combine investigator-captured and patient-captured images:

Investigator timepoints: Primary visits (e.g., baseline, month 3, month 6, month 12) where images are captured by trained site personnel at the clinic
Patient timepoints: Intermediate visits (e.g., monthly check-ins) where the patient captures images at home using the mobile application

The same AI scoring pipeline processes both types of images. DIQA quality control is applied identically, ensuring that patient-captured images meet the same quality standards as investigator-captured images.

Remote patient capture

For fully decentralised protocols:

Patients download the Legit.Health mobile application
The app guides them through the capture process with the same perspective silhouettes and DIQA quality checks used at investigator sites
Captured images are transmitted securely to the platform for AI scoring
The investigator can review scores remotely

Benefits for sponsors

Reduced site burden: Fewer in-clinic visits needed for severity assessment
Increased data frequency: More timepoints without increasing site workload
Patient convenience: Assessments from home reduce travel burden
Continuous monitoring: More frequent assessments enable finer-grained treatment response detection

Workflow overview​

1. Protocol design​

2. Site setup​

3. Patient enrollment​

4. Image capture​

5. AI scoring​

6. Report review​

7. Severity tracking​

8. Data export and EDC integration​

Exported data fields​

Integration methods​

Decentralised and hybrid trial support​