R-TF-015-008 Clinical development plan

Clinical development plan

Gantt chart

The following chart shows an overview of the process by which we provide evidence of the performance of our device.

Peer-reviewed publications

Automatic SCOring of Atopic Dermatitis Using Deep Learning: A Pilot Study

• Published: February 10, 2022
• DOI: https://doi.org/10.1016/j.xjidi.2022.100107

Dermatology Image Quality Assessment (DIQA): Artificial intelligence to ensure the clinical utility of images for remote consultations and clinical trials

• Published: December 13, 2022
• DOI: https://doi.org/10.1016/j.jaad.2022.11.002

Automatic International Hidradenitis Suppurativa Severity Score System (AIHS4): A novel tool to assess the severity of hidradenitis suppurativa using artificial intelligence

• Published: 05 June 2023
• DOI: https://doi.org/10.1111/srt.13357

Automatic Urticaria Activity Score (AUAS): Deep Learning-based Automatic Hive Counting for Urticaria Severity Assessment

• Published: July 11, 2023
• DOI: https://doi.org/10.1016/j.xjidi.2023.100218

The Utility and Reliability of a Deep Learning Algorithm as a diagnosis support tool in head & neck non-melanoma skin malignancies

• Published: September 6, 2024
• DOI: https://doi.org/10.1007/s00405-024-08951-z

Upcoming papers

Automatic Psoriasis Area and Severity Index

• Code: APASI
• Current status: Under review by the journal
• Journal: Journal of the European Academy of Dermatology and Venereology Clinical Practice (JEADV Clinical Practice)
• Submission date: March, 2025

Severity assessment and characterisation of Pressure Ulcer using deep learning

• Code: WOUNDS
• Current status: Work in progress.
• Journal: Journal of the American Academy of Dermatology (JAAD)
• Submission date: Q1, 2025

Overcoming measurement challenges in clinical trials: a deep learning-based approach for monocular surface area measurement

• Code: AREA ESTIMATION
• Current status: Paper submitted to the journal, waiting for its response.
• Journal: British Journal of Dermatology.
• Submission date: March, 2025

ALADIN: Automatic Lesion And Density INdex. A Novel Tool for Automatic Acne Severity Assessment

• Code: ALADIN
• Code: ALADIN
• Current status: Paper submitted to the journal, waiting for its response.
• Journal: JAMA Dermatology.
• Submission date: March, 2025.

Development and assessment of an automated imaging medical device based on artificial intelligence for evaluating the severity of generalized pustular psoriasis

• Code: AGPPGA
• Current status: Seeking a scientific journal for the paper.
• Journal: Pending determination of the journal.
• Submission date: Q2, 2025

Enhancing diagnostic accuracy of generalised pustular psoriasis with Legit.Health, an AI-based certified medical device

• Code: DIAGNOSTIC SUPPORT
• Current status: Work in progress. Pending Review.
• Journal: Pending determination of the journal.
• Submission date: Q2, 2025

Enhanced Dermatology Image Quality Assessment Via Cross-Domain Training

• Code: DIQA V2
• Current status: Work in progress
• Journal: International Conference Proceedings by ACM
• Submission date: September, 2025

Limitations of the Diverse Dermatology Images dataset for fairness benchmarking of machine learning models in dermatology: findings and recommendations

• Code: FITZPATRICK
• Current status: Work in progress (paper in preparation)
• Journal: Pending determination of the journal
• Submission date: Q3, 2025

Automatic WOund Severity Index (AWOSI) estimation and characterization using deep learning

• Code: WOUNDS
• Current status: Work in progress (waiting to finish the clinical validation).
• Journal: Journal of the American Academy of Dermatology (JAAD)
• Submission date: Q2, 2025

Real-world evaluation of an AI-powered dermatology tool: A multi-center study of Legit.Health's diagnostic performance in elderly homes

• Code: SANITAS
• Current status: Work in progress (waiting for author revision).
• Journal: Journal: Journal of the American Academy of Dermatology (JAAD)
• Submission date: Q2, 2025

Enhancing diagnostic accuracy of melanoma with Legit.Health, an AI-based certified medical device

• Code: MELANOMA
• Current status: Paper in preparation (waiting for authors revision).
• Journal: Journal of the European Academy of Dermatology and Venereology Clinical Practice (JEADV Clinical Practice).
• Submission date: Q2, 2025

Optimisation of clinical flow in patients with dermatological conditions using Legit.Health's AI medical device

• Code: IDEI
• Current status: Work in progress (paper in preparation).
• Journal: Pending determination of the journal
• Submission date: Q2, 2025

Artificial intelligence-based quantification to assess the Automatic Vitiligo Area Scoring Index

• Code: AVASI
• Current status: Work in progress (waiting to finish the clinical validation).
• Journal: Journal of Investigative Dermatology (JID).
• Submission date: Q2, 2025.

Activity in medical congress

Experience of using the Legit.Health artificial intelligence tool in the digital monitoring of chronic dermatological pathologies

Automatic International Hidradenitis Suppurativa Severity Score System

Hidradenitis artificial intelligence pilot project

Analysis of the Performance of a Medical Device with Artificial Intelligence for the Optimization of Clinical Flow in Patients with Pigmented Lesions

Performance Study of a Diagnostic Support Medical Device with Artificial Intelligence in 15 Nursing Homes

Analysis of the Performance of a Medical Device with Artificial Intelligence for the Optimization of Clinical Flow in Patients with Pigmented Lesions

Performance Analysis of an AI-Enhanced Medical Device for Optimizing Clinical Workflow in Patients with Pigmented Lesions

Automatic Generalized Pustular Psoriasis Physician Global Assessment (AGPPGA)

Validation study of artificial intelligence for the detection of Melanoma

ALADIN scale for automatic measurement of acne severity

Double intelligence: the future telematic follow-up of patients by Dra Elena Sanchez-Largo

Artificial Intelligence for the optimization of the referral of patients with skin pathologies

Automatic calculation of urticaria with Artificial Intelligence for accurate counting of wheals

Optimization of teledermatology in primary care

Automatic SALT: Reducing variability in the measurement of alopecia

Clinical investigation

The following table summarizes the clinical trials that have been conducted or are currently in progress. The table includes the code of the trial, its status, start and end dates, and acceptance criteria, among other details.

Medical DeviceAllLegit.Health PlusLegit.Health Legacy DevicePre/Post MarketAllPre-MarketPost-Market

LEGIT_MC_EVCDAO_2019

• Title: Clinical validation study of a CAD system with artificial intelligence algorithms for early noninvasive in vivo cutaneous melanoma detection
• Code: LEGIT_MC_EVCDAO_2019
• Medical Device: Legit.Health Legacy Device
• Start Date: 2020-02-10
• Completion Date: 2023-11-13
• Ethics Approval: true
• Authority Approval: false
• Pre/Post Market: Pre-Market
• Status: Pre-clinical
• Endpoints:
  • AUC more significant than 0.8
  • Sensitivity of 80% or higher
  • A specificity of 70% or higher
• Achievements:
  • AUC of 0.842 identifying melanoma
  • AUC of 0.8983 detecting malignancy
  • Top-3 sensitivity of 0.9032
  • Top-1 specificity of 0.8054
• Justification: The approval of AEMPS was not necessary since this study was carried out with the Legacy device (CE-marked) within its intended use, and it was a non-interventional study
• Journal Submission: Expected to be sent in May 2025 to the Journal of the European Academy of Dermatology and Venereology Clinical Practice

LEGIT_COVIDX_EVCDAO_2022

• Title: Clinical Validation of a Computer-Aided Diagnosis (CAD) System Utilizing Artificial Intelligence Algorithms for Continuous and Remote Monitoring of Patient Condition Severity in an Objective and Stable Manner
• Code: LEGIT_COVIDX_EVCDAO_2022
• Medical Device: Legit.Health Plus
• Start Date: 2022-04-13
• Completion Date: 2023-10-23
• Ethics Approval: true
• Authority Approval: false
• Pre/Post Market: Pre-Market
• Status: Clinical
• Endpoints:
  • A score of 8 or higher on the Clinical Utility Questionnaire (CUS) filled by medical staff
• Achievements:
  • Mean of 76.67 on the CUS (positive feedback overall, but sample size was small)
• Justification: Legit.Health Plus was used in this investigation under its intended use and within approved purposes. Test subjects were not subjected to conditions needing article 74(1) Regulation approvals
• Journal Submission: No

LEGIT.HEALTH_DAO_Derivación_PH_2022

• Title: Project to enhance Dermatology E-Consultations in Primary Care Centres using Artificial Intelligence Tools
• Code: LEGIT.HEALTH_DAO_Derivación_PH_2022
• Medical Device: Legit.Health Plus
• Start Date: 2022-06-24
• Completion Date: 2024-01-10
• Ethics Approval: true
• Authority Approval: false
• Pre/Post Market: Pre-Market
• Status: Clinical
• Endpoints:
  • An improvement of diagnostic accuracy of 10% (Ferri et al. 2020) in general practitioners and dermatologists
• Achievements:
  • 15 primary care physicians and 180 diagnostic reports were recorded for 131 patients
  • Legit.Health helped identify two cases of Hidradenitis suppurativa
  • Five confirmed melanoma cases through pathology (dermatologists suspected 10)
  • 60% sensitivity and 91% specificity in detecting melanoma, with AUC of 0.84 for malignancy
• Justification: Legit.Health Plus was used in this investigation under its intended use and within approved purposes. Test subjects were not subjected to conditions needing article 74(1) Regulation approvals
• Journal Submission: No

LEGIT.HEALTH_IDEI_2023

• Title: Optimisation of clinical flow in patients with dermatological conditions using Artificial Intelligence
• Code: LEGIT.HEALTH_IDEI_2023
• Medical Device: Legit.Health Plus
• Start Date: 2024-01-25
• Completion Date: 2024-08-23
• Ethics Approval: true
• Authority Approval: false
• Pre/Post Market: Pre-Market
• Status: Clinical
• Endpoints:
  • An improvement in diagnostic accuracy of 10% (Ferri et al. 2020)
  • Scores ≥ 70 on the System Usability Scale (SUS)
  • An AUC ≥ 0.8 detecting malignancy
  • A sensitivity of 80% detecting malignancy
  • A specificity of 70% detecting malignancy
• Achievements:
  • Retrospective analysis: Dermatologists AUC=0.79, Device AUC=0.76; Dermatologists' sensitivity=86%, Device=81%; Dermatologists' specificity=36%, Device=52%. Diagnosis accuracy—Dermatologists: top-1=0.56, top-3=0.70; Device: top-1=0.50, top-3=0.71, top-5=0.78
  • Prospective analysis: Dermatologists + Device: AUC=0.94, sensitivity=88%, specificity=85%, top-1 accuracy=0.85.
• Justification: Legit.Health Plus was used in this investigation under its intended use and within approved purposes. Test subjects were not subjected to conditions needing article 74(1) Regulation approvals
• Journal Submission: No

LEGIT.HEALTH_SAN_2024

• Title: Non-invasive prospective Pilot in a Live Environment for the Improvement of diagnosis of skin pathologies in Primary Care and Dermatology
• Code: LEGIT.HEALTH_SAN_2024
• Medical Device: Legit.Health Plus
• Start Date: 2024-06-01
• Completion Date: 2024-10-10
• Ethics Approval: false
• Authority Approval: false
• Pre/Post Market: Pre-Market
• Status: Clinical
• Endpoints:
  • An improvement of diagnostic accuracy in primary care physicians and dermatologists
  • A positive view of Legit.Health regarding diagnosis support
  • A 30% reduction of referrals to dermatology (Warshaw et al. 2011)
  • An improvement in remote consultations
• Achievements:
  • An increase in diagnostic accuracy of 27.02% (primary care) and 10.46% (dermatology)
  • 60.89% of consultations required no referral in primary care; 53.59% in dermatology
  • 59.68% of consultations could be handled remotely in primary care; 47.71% in dermatology
  • Design and usability scored 8/10, with strong consensus
• Justification: Observational, non-interventional study using non-sensitive anonymised data; no direct interaction with patients. Ethics approval deemed unnecessary
• Journal Submission: No

LEGIT.HEALTH_BI_2024

• Title: Non-Invasive Prospective Pilot in a Live Environment for the improvement of diagnosis of Generalized Pustular Psoriasis
• Code: LEGIT.HEALTH_BI_2024
• Medical Device: Legit.Health Plus
• Start Date: 2024-06-01
• Completion Date: 2024-09-15
• Ethics Approval: false
• Authority Approval: false
• Pre/Post Market: Pre-Market
• Status: Clinical
• Endpoints:
  • An improvement of diagnosis accuracy of GPP
  • An improvement of diagnosis accuracy of hidradenitis suppurativa or palmoplantar pustulosis among PCPs and dermatologists
• Achievements:
  • Diagnosis accuracy +17.42% in primary care and +8.40% in dermatology overall
  • +22.97% accuracy in generalised pustular psoriasis for both specialties
  • +8.92% accuracy in diagnosing hidradenitis suppurativa
  • +34.38% accuracy in diagnosing palmoplantar pustulosis
• Justification: Observational, non-interventional study using anonymised data; no direct patient interaction
• Journal Submission: No

LEGIT.HEALTH_PH_2024

• Title: Non-invasive prospective Pilot in a Live Environment for the Improvement of the diagnosis of skin pathologies in Primary Care
• Code: LEGIT.HEALTH_PH_2024
• Medical Device: Legit.Health Plus
• Start Date: 2024-06-04
• Completion Date: 2024-09-13
• Ethics Approval: false
• Authority Approval: false
• Pre/Post Market: Pre-Market
• Status: Clinical
• Endpoints:
  • An improvement of diagnostic accuracy in primary care physicians
  • A positive view of Legit.Health regarding diagnosis support
  • A 30% reduction of referrals to dermatology
  • An improvement in remote consultations
• Achievements:
  • +9.29% increase in diagnostic accuracy in primary care
  • 48.89% of cases did not need referral
  • 60.74% of cases can be managed remotely
• Justification: Observational, non-interventional study using anonymised data; no direct patient interaction
• Journal Submission: No

LEGIT.HEALTH_DAO_Derivación_O_2022

• Title: Pilot study for the clinical validation of an artificial intelligence algorithm to optimize the appropriateness of dermatology referrals. (Ongoing Study)
• Code: LEGIT.HEALTH_DAO_Derivación_O_2022
• Medical Device: Legit.Health Plus
• Start Date: 2022-11-23
• Completion Date: 2025-04-04
• Ethics Approval: true
• Authority Approval: false
• Pre/Post Market: Pre-Market
• Status: Clinical
• Endpoints:
  • Improve the adequacy of referrals to dermatology
  • Reduce waiting lists by at least 30% (Warshaw et al. 2011)
  • Reduce costs in secondary care
• Achievements:
  • Currently 200 lesions recruited. Further analysis is pending.
• Justification: Legit.Health Plus was used in this investigation under its intended use and within approved purposes. Test subjects were not subjected to conditions needing article 74(1) Regulation approvals
• Journal Submission: No

Legit.Health_AIHS4_2025

• Title: Evaluation of AIHS4 Performance in the M-27134-01 Clinical Trial for Hidradenitis Suppurativa
• Code: Legit.Health_AIHS4_2025
• Medical Device: Legit.Health Plus
• Start Date: 2024-06-04
• Completion Date: 2024-07-11
• Ethics Approval: false
• Authority Approval: false
• Pre/Post Market: Pre-Market
• Status: Clinical
• Endpoints:
  • AIHS4 improves severity assessment compared to interobserver agreement
  • AIHS4 maintains temporal consistency across visits
  • AIHS4 achieves high agreement in lesion classification across anatomical regions
• Achievements:
  • 59.27% agreement with the researchers overall
  • 71.66% agreement vs the gold standard (researchers = 47.91% vs gold standard)
• Justification: Observational, non-interventional study using anonymised data; no direct patient interaction
• Journal Submission: No

Legit.Health_triaje_VH_2025

• Title: Evaluating the performance of Legit.Health in automated triage in teledermatology
• Code: Legit.Health_triaje_VH_2025
• Medical Device: Legit.Health Plus
• Start Date: 2025-06-01
• Completion Date: N/A
• Ethics Approval: null
• Authority Approval: null
• Pre/Post Market: Post-Market
• Status: Planned
• Endpoints:
  • Assess impact on reducing average waiting time for skin cancer patients
  • Measure sensitivity and specificity of Legit.Health in detecting malignancy
• Achievements: N/A
• Justification: N/A
• Journal Submission: Not applicable yet

CVCSD_VC_2402

• Title: Study for the clinical validation of a medical device for prioritising follow-up visits in patients at risk of melanoma
• Code: CVCSD_VC_2402
• Medical Device: Legit.Health Plus
• Start Date: 2025-06-01
• Completion Date: N/A
• Ethics Approval: null
• Authority Approval: null
• Pre/Post Market: Post-Market
• Status: Planned
• Endpoints:
  • Evaluate the impact of Legit.Health on prioritising follow-up consultations in suspected melanoma
• Achievements: N/A
• Justification: N/A
• Journal Submission: Not applicable yet

Legit.Health_clinical_VH_2025

• Title: Pilot study for the clinical validation of a medical device for the automatic triage in teledermatology
• Code: Legit.Health_clinical_VH_2025
• Medical Device: Legit.Health Plus
• Start Date: 2025-06-30
• Completion Date: N/A
• Ethics Approval: null
• Authority Approval: null
• Pre/Post Market: Post-Market
• Status: Planned
• Endpoints:
  • Validate Legit.Health's capability to prioritise referrals from primary care to dermatology based on severity
• Achievements: N/A
• Justification: N/A
• Journal Submission: Not applicable yet

LEGIT_AFF_EVCDAO_2021

• Title: Pilot study for the clinical validation of a medical device for the quantification of severity and monitoring of the evolution of patients with FFA (Frontal Fibrosing Alopecia)
• Code: LEGIT_AFF_EVCDAO_2021
• Medical Device: Legit.Health Plus
• Start Date: 2025-07-31
• Completion Date: N/A
• Ethics Approval: null
• Authority Approval: null
• Pre/Post Market: Post-Market
• Status: Planned
• Endpoints:
  • Validate whether Legit.Health can measure severity of FFA by automatically counting hairs, equal or greater than the specialist ‘gold standard’
• Achievements: N/A
• Justification: N/A
• Journal Submission: Not applicable yet

Legit.Heath_acne

• Title: Pilot study for the clinical validation of a medical device for the automatic assessment of severity and remote monitoring of patients with acne
• Code: Legit.Heath_acne
• Medical Device: Legit.Health Plus
• Start Date: 2025-07-01
• Completion Date: N/A
• Ethics Approval: null
• Authority Approval: null
• Pre/Post Market: Post-Market
• Status: Planned
• Endpoints:
  • Validate that ALADIN severity scale (AI LABS GROUP S.L.) measures facial acne severity similarly to or better than a specialist using smartphone photos
• Achievements: N/A
• Justification: N/A
• Journal Submission: Not applicable yet

Legit_aEASI_HVN

• Title: Pilot study for the clinical validation of an automatic EASI scoring system with artificial intelligence algorithms to assess the severity of atopic dermatitis
• Code: Legit_aEASI_HVN
• Medical Device: Legit.Health Plus
• Start Date: 2025-07-01
• Completion Date: N/A
• Ethics Approval: null
• Authority Approval: null
• Pre/Post Market: Post-Market
• Status: Planned
• Endpoints:
  • Validate an automatic EASI (Eczema Area and Severity Index) measurement system to determine severity of atopic dermatitis with accuracy comparable or superior to expert consensus
• Achievements: N/A
• Justification: N/A
• Journal Submission: Not applicable yet

PMCF-ICD-DXP-2026

• Title: Image-based diagnosis non-interventional performance analysis
• Code: PMCF-ICD-DXP-2026
• Medical Device: Legit.Health Plus
• Start Date: 2026-11-01
• Completion Date: N/A
• Ethics Approval: false
• Authority Approval: false
• Pre/Post Market: Post-Market
• Status: Post-Market
• Endpoints:
  • AUC higher than 0.8 for the clinical indicators
  • Top-5 accuracy higher than 70%
  • Top-3 accuracy higher than 55%
  • Top-1 accuracy higher than 40%
• Achievements: N/A
• Justification: Observational, non-interventional study using anonymised data; no direct patient interaction
• Journal Submission: Not applicable yet

Timeline and milestones

• 2025
  • Start of the study CVCSD_VC_2402
  • Start of the study LEGIT.HEALTH_acne
  • Start of the study LEGIT.HEALTH_aEASI_2024
  • Start of the study LEGIT.HEALTH_triaje_VH_2024
  • Start of the study Legit.Health_DAO_wounds
  • Start of the study Legit.Health_clinical_VH_2025
  • Start of the study Legit.Health_AVASI
  • Start of the study LEGIT_AFF_EVCDAO
  • Completition of the study LEGIT.HEALTH_aEASI_2024
  • Completition of the study Legit.Health_DAO_wounds
• 2026
  • Completition of the study CVCSD_VC_2402
  • Completition of the study LEGIT.HEALTH_acne
  • Completition of the study LEGIT.HEALTH_triaje_VH_2024
  • Completition of the study Legit.Health_clinical_VH_2025
  • Completition of the study Legit.Health_AVASI
  • CE certification completed
  • FDA certification completed
  • Expected Market launch
• 2027
  • Completition of the study LEGIT_AFF_EVCDAO

Conclusions

This CDP outlines a structured and comprehensive approach to the clinical development of the device, ensuring thorough evaluation at each phase of development. The plan outlines a clear regulatory pathway, leading to the successful market introduction and long-term monitoring of the device.

Signature meaning

The signatures for the approval process of this document can be found in the verified commits at the repository for the QMS. As a reference, the team members who are expected to participate in this document and their roles in the approval process, as defined in Annex I Responsibility Matrix of the GP-001, are:

• Author: Team members involved
• Reviewer: JD-003, JD-004
• Approver: JD-005