Clinical Trial Experience
Legit.Health AI scoring is actively deployed in clinical trials with leading pharmaceutical companies. This page summarises our clinical trial engagements across indications, geographies, and use cases.
At a glance
Case study: Decentralised PASI scoring in Phase 3 psoriasis
Study profile
A Phase 3, multicentre, randomised, double-blind, placebo-controlled trial for moderate-to-severe plaque psoriasis, sponsored by a top-10 pharmaceutical company.
| Parameter | Detail |
|---|---|
| Indication | Moderate-to-severe plaque psoriasis |
| Phase | Phase 3 |
| Investigator sites | ~130 |
| Countries | 12 (Argentina, Australia, Belgium, Canada, Denmark, Germany, Hungary, Poland, Portugal, Spain, UK, US) |
| Subjects | ~250 |
| Capture model | Fully decentralised; patients self-capture at home |
| Imaging protocol | 11-perspective full-body (7 full-body + 4 close-ups) |
| Scoring | Automated PASI (APASI) + image quality validation |
| Language localisations | 14 |
| Photography visits | 6 timepoints over the long-term extension phase |
How the technology was used
Patients logged into the Legit.Health mobile application from home and captured 11 standardised photographs covering all four PASI body regions. The app provided step-by-step perspective guidance with visual silhouettes and real-time DIQA quality checks for each image. No clinic visit was required for these assessments.
The AI processed all images automatically, computing:
- Per-region erythema, desquamation, and induration intensity scores
- Pixel-level body surface area (BSA) segmentation per region
- Composite APASI score (0–72)
- DIQA image quality scores per perspective
Scored data was transferred to the sponsor's data science team via automated monthly S3 exports: no central reader, no manual scoring, no delays.
Why this matters
This deployment demonstrated that patients can successfully capture standardised full-body images at home using a standard smartphone, producing scoring data of sufficient quality for a pivotal Phase 3 programme. This model eliminates specific on-site visits, reduces patient burden, and enables continuous severity monitoring between clinic appointments.
Case study: Alopecia safety monitoring in Phase 3 MASH trial
Study profile
A Phase 3 trial for MASH/MASLD (metabolic-associated steatohepatitis) where alopecia was monitored as a safety endpoint.
| Parameter | Detail |
|---|---|
| Indication | MASH/MASLD with alopecia safety monitoring |
| Phase | Phase 3 |
| Capture model | In-clinic |
| Imaging protocol | 4-perspective scalp imaging |
| Scoring | Automated SALT (ASALT) |
How the technology was used
Investigators captured 4 scalp images per patient at scheduled clinic visits. The AI computed ASALT scores to track any alopecia development as a potential adverse event related to the investigational therapy.
Pipeline breadth
Beyond the case studies above, Legit.Health has active engagements spanning multiple indications and use cases:
Indications under active engagement
- Psoriasis: APASI scoring for Phase 3 and retrospective studies
- Acne: ALADIN scoring with automated lesion counting and IGA
- Alopecia: ASALT scoring for scalp assessment
- Atopic dermatitis: ASCORAD and visual sign detection
- Generalized pustular psoriasis (GPP): AI development for GPP identification and GPPGA scoring
Use case diversity
| Use case | Description |
|---|---|
| Severity scoring endpoint | Primary deployment model: automated PASI, IGA, SALT, or SCORAD scoring for efficacy assessment |
| Adverse event detection | AI-based monitoring of treatment-emergent adverse events (e.g., alopecia in MASH trials) |
| Retrospective image analysis | Large-scale analysis of 85,000+ clinical images for 22+ visual signs (erythema, swelling, oozing, excoriations, lichenification, dryness, and more) |
| Patient-facing API integration | API-based scoring integrated into patient self-tracking applications, enabling severity monitoring at scale |
Engagement scale
Active and pipeline engagements involve top-10 and top-20 pharmaceutical companies, spanning:
- Phase 2 and Phase 3 interventional trials
- Long-term extension studies
- Retrospective image analysis programmes
- Patient-facing digital health integrations
Integration models
Legit.Health supports multiple integration architectures to fit the sponsor's infrastructure:
| Model | Description | Example use |
|---|---|---|
| Clinical trials platform | Full web application with investigator portal, patient management, and reporting | Phase 3 decentralised trials |
| Mobile application | Patient-facing app with perspective guidance and DIQA quality control | Home-based capture |
| API integration | RESTful API for programmatic scoring, embeddable in sponsor or CRO platforms | Patient apps, retrospective analysis |
| Data export | Automated S3 transfer, CSV, or structured JSON export to EDC systems | All trial types |
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