R-TF-015-006 Clinical investigation report

Research Title

Non-Invasive Prospective Pilot in a Live Environment for the improvement of the diagnosis of Generalised Pustular Psoriasis

Product Identification

	Information
Device name	Legit.Health Plus (hereinafter, the device)
Model and type	NA
Version	1.1.0.0
Basic UDI-DI	8437025550LegitCADx6X
Certificate number (if available)	MDR 792790
EMDN code(s)	Z12040192 (General medicine diagnosis and monitoring instruments - Medical device software)
GMDN code	65975
EU MDR 2017/745	Class IIb
EU MDR Classification rule	Rule 11
Novel product (True/False)	TRUE
Novel related clinical procedure (True/False)	TRUE
SRN	ES-MF-000025345

Sponsor Identification and Contact

	Manufacturer data
Legal manufacturer name	AI Labs Group S.L.
Address	Street Gran Vía 1, BAT Tower, 48001, Bilbao, Bizkaia (Spain)
SRN	ES-MF-000025345
Person responsible for regulatory compliance	Alfonso Medela, Saray Ugidos
E-mail	office@legit.health
Phone	+34 638127476
Trademark	Legit.Health
Authorized Representative	Not applicable (manufacturer is based in EU)

Identification of sponsors

• Boehringer Ingelheim

Identification of the Clinical Investigation Plan (CIP)

	CIP
Title of the clinical investigation	Non-Invasive Prospective Pilot in a Live Environment for the improvement of diagnosis of Generalized Pustular Psoriasis
Device under investigation	Legit.Health Plus
Protocol version	Version 1.0
Date	2024-06-01
Protocol code	LEGIT.HEALTH_BI_2024
Sponsor	Boehringer Ingelheim
Coordinating Investigator	Dr. Antonio Martorell Calatayud
Principal Investigator(s)	Dr. Antonio Martorell Calatayud
Investigational site(s)	This study was conducted remotely by sending the images to the participating dermatologists.
Ethics Committee	This study did not require Ethics Committee approval because it is observational and non-interventional. All data used consists of fully anonymized images sourced from public dermatology atlases and databases, containing no information permitting patient identification. As such, the research meets the criteria for exemption from ethics committee review under applicable regulatory frameworks.

Public Access Database

The database used in this study is not publicly accessible due to privacy and confidentiality considerations.

Research Team

Principal investigator

• Dr. Antonio Martorell Calatayud

Collaborators

• Medical staff
  • Dr. Mari Carmen Galindo
  • Dr. Paco García Tolosa
  • Dr. Laura Yuste Hidalgo
  • Dr. Nuria Comabella
  • Dr. Marta Vázquez
  • Dr. David Palacios
  • Dr. Norma Alejandra Doria Carlin
  • Dr. Francisco José Esteban González
  • Dr. Alfonso José Valcarce Leonisio
  • Dr. José Antonio Arjona Sevilla
  • Dr. Javier Melgosa
  • Dr. Manuel Ballesteros Redondo
  • Dr. Esmeralda Silva
  • Dr. Ana Llull Ramos
  • Dr. Angela Patricia Guzmán
• AI Labs Group S.L.
  • Mr. Alfonso Medela
  • Dr. Alberto Sabater
  • Mrs. Alba Rodríguez

Center

• This study was conducted remotely by sending the images to the participating dermatologists..

Compliance Statement

The clinical investigation was perforfed according to the Clinical Investigation Plan (CIP) and other applicable guidances and regulations. This includes compliance with:

• Harmonized standard UNE-EN ISO 14155:2021
• Regulation (EU) 2017/745 on medical devices (MDR)
• Harmonized standard UNE-EN ISO 13485:2016s
• Regulation (EU) 2016/679 (GDPR).
• Spanish Organic Law 3/2018 on the Protection of Personal Data and guarantee of digital rights.

All data processing within the device is carried out in accordance with the highest standards of data protection and privacy. Patient information is managed in an encrypted manner to ensure confidentiality and security.

The research team assumes the role of Data Controller, responsible for the collection and management of study data. Legit.Health acts as the Data Processor and is not involved in the processing of patient data.

The storage and transfer of data comply with European data protection regulations. At the conclusion of the study, all information stored in the device will be permanently and securely deleted.

The device employs robust technical and organizational security measures to safeguard personal data against unauthorized access, alteration, loss, or processing.

Report Date

September 15, 2024

Report author(s)

The full name, the ID and the signature for the authorship, as well as the approval process of this document, can be found in the verified commits at the repository. This information is saved alongside the digital signature, to ensure the integrity of the document.

Table of contents

Table of contents

• Research Title
• Product Identification
• Sponsor Identification and Contact
• Identification of sponsors
• Identification of the Clinical Investigation Plan (CIP)
• Public Access Database
• Research Team
  • Principal investigator
  • Collaborators
  • Center
• Compliance Statement
• Report Date
• Report author(s)
• Table of contents
• Abbreviations and Definitions
• Summary
  • Title
  • Introduction
  • Objectives
    • Primary objective
    • Secondary objectives
  • Population
  • Sample size
  • Design and methods
    • Design
    • Number of subjects
    • Initiation Date
    • Completion Date
    • Duration
    • Methods
  • Results
  • Conclusions
• Introduction
• Material and methods
  • Product Description
  • Clinical Investigation Plan
    • Objectives
    • Design (type of research, assessment criteria, methods, active group, and control group)
    • Ethical considerations
  • Data confidentiality
    • Data Quality Assurance
    • Subject Population
    • Statistical Analysis
• Results
  • Initiation and Completion Date
  • Subject and Investigational Product Management
  • Subject Demographics
  • Clinical Investigation Plan (CIP) Compliance
  • CIP Deviations
  • Analysis
    • Primary Analyses
    • Diagnosis support
    • Acceptance Criteria Verification
    • Rare Disease Analysis
    • Adverse Events and Adverse Reactions to the Product
    • Product Deficiencies
    • Subgroup Analysis for Special Populations
• Discussion and Overall Conclusions
  • Clinical Performance, Efficacy, and Safety
  • Conclusions
    • References
  • Implications for Future Research
  • Limitations of Clinical Research
  • Ethical Aspects of Clinical Research
• Investigators and Administrative Structure of Clinical Research
  • Brief Description
  • Investigators
    • Principal investigator
    • Collaborators
    • Investigator Qualifications
  • External Organization
  • Sponsor and Monitor
• Report Annexes

Abbreviations and Definitions

• AE: Adverse Event
• AEMPS: Spanish Agency of Medicines and Medical Devices
• AEP: Adverse Reaction to Product
• AUC: Area Under the ROC Curve
• CAD: Computer-Aided Diagnosis
• CMD: Data Monitoring Committee
• CIP: Clinical Investigation Plan
• CUS: Clinical Utility Questionnaire
• DLQI: Dermatology Quality of Life Index
• GCP: Standards of Good Clinical Practice
• ICH: International Conference of Harmonization
• IFU: Instructions For Use
• IRB: Institutional Review Board
• N/A: Not Applicable
• NCA: National Competent Authority
• PI: Principal Investigator
• PPV: Positive Predictive Value
• NPV: Negative Predictive Value
• SAE: Serious Adverse Events
• SAEP: Serious Adverse Event to Product
• SUAEP: Serious and Unexpected Adverse Event to the Product
• SUS: System Usability Scale

Summary

Title

Non-Invasive Prospective Pilot in a Live Environment for the improvement of the diagnosis of Generalised Pustular Psoriasis.

Introduction

Dermatological conditions represent a significant portion of primary care consultations, constituting approximately 5% of all visits. In these consultations can be discrepancies between primary care physicians and dermatologists, especially in rare and severe conditions, such as Generalized Pustular Psoriasis (GPP) or Hidradenitis Suppurativa (HS), which can lead to misdiagnoses. This investigation pretends to assess whether the use of the Legit.Health medical device can improve the diagnosis of complicated pathologies with a low incidence but a great impact on the patient's quality of life, such as GPP or also HS. 15 HCPs will be recruited and each one of them will be presented with 100 images of patients with GPP, HS or pathologies that can be confused with these. This research follows rigorous ethical standards and adherence to regulatory guidelines, this research holds significant potential in revolutionizing dermatological diagnostics.

Objectives

Primary objective

To validate that the information provided by the device increases the true accuracy of healthcare professionals (HCPs) in the diagnosis of generalized pustular psoriasis (GPP).

Secondary objectives

To validate that the information provided by the device increases the true accuracy of healthcare professionals (HCPs) in the diagnosis of other dermatological skin conditions, such as hidradenitis suppurativa.

• top-1 accuracy equal to or greater than 7.00%.(User Group: Dermatologists, Primary care practitioners)
• top-1 accuracy greater than 47.94%.(User Group: Dermatologists, Primary care practitioners)
• top-1 accuracy equal to or greater than 53.96%.(User Group: Dermatologists, Primary care practitioners)
• sensitivity greater than 6.93%.(User Group: Dermatologists, Primary care practitioners)
• sensitivity greater than 70.00%.(User Group: Dermatologists, Primary care practitioners)
• sensitivity greater than 52.61%.(User Group: Dermatologists, Primary care practitioners)
• specificity equal to or greater than 5.06%.(User Group: Dermatologists, Primary care practitioners)
• specificity equal to or greater than 70.00%.(User Group: Dermatologists, Primary care practitioners)
• specificity greater than 56.45%.(User Group: Dermatologists, Primary care practitioners)
• top-1 accuracy equal to or greater than 47.91%.(User Group: Primary care practitioners)
• top-1 accuracy equal to or greater than 46.12%.(User Group: Primary care practitioners)
• sensitivity equal to or greater than 14.30%.(User Group: Primary care practitioners)
• sensitivity equal to or greater than 66.30%.(User Group: Primary care practitioners)
• specificity equal to or greater than 11.88%.(User Group: Primary care practitioners)
• specificity equal to or greater than 70.10%.(User Group: Primary care practitioners)
• top-1 accuracy equal to or greater than 5.83%.(User Group: Dermatologists)
• top-1 accuracy equal to or greater than 57.25%.(User Group: Dermatologists)
• top-1 accuracy equal to or greater than 61.80%.(User Group: Dermatologists)
• sensitivity equal to or greater than 6.93%.(User Group: Dermatologists)
• sensitivity equal to or greater than 70.00%.(User Group: Dermatologists)
• sensitivity greater than 61.64%.(User Group: Dermatologists)
• specificity equal to or greater than 77.60%.(User Group: Dermatologists)
• specificity greater than 62.47%.(User Group: Dermatologists)
• top-1 accuracy equal to or greater than 6.93%.(User Group: Dermatologists, Primary care practitioners)
• top-1 accuracy equal to or greater than 30.90%.(User Group: Dermatologists, Primary care practitioners)
• sensitivity equal to or greater than 6.93%.(User Group: Dermatologists, Primary care practitioners)
• sensitivity greater than 21.04%.(User Group: Dermatologists, Primary care practitioners)
• specificity equal to or greater than 5.06%.(User Group: Dermatologists, Primary care practitioners)
• specificity greater than 38.69%.(User Group: Dermatologists, Primary care practitioners)
• top-1 accuracy equal to or greater than 24.34%.(User Group: Primary care practitioners)
• sensitivity equal to or greater than 14.30%.(User Group: Primary care practitioners)
• sensitivity greater than 19.33%.(User Group: Primary care practitioners)
• specificity equal to or greater than 11.88%.(User Group: Primary care practitioners)
• specificity greater than 36.64%.(User Group: Primary care practitioners)
• top-1 accuracy equal to or greater than 5.83%.(User Group: Dermatologists)
• top-1 accuracy equal to or greater than 48.15%.(User Group: Dermatologists)
• sensitivity greater than 35.89%.(User Group: Dermatologists)
• specificity greater than 55.67%.(User Group: Dermatologists)

Population

In this study, the population will consist of primary care physicians and dermatologists. A minimum of 15 physicians will be selected.

Sample size

Given our goal to evaluate whether the use of Legit.Health enhances diagnostic accuracy by at least 10% in healthcare professionals, this improvement would justify a significant shift in clinical practice. Therefore, in this study, 15 physicians will be included, which provides a strong basis for collecting diverse professional insights while ensuring sufficient statistical power. Compared to smaller-scale studies, the higher number of participants reduces variability and enhances the generalizability of findings across different clinical practices. Each physician evaluated 100 images, resulting in 1,500 evaluations in total. This volume ensures that each participant gains ample practical experience with the device, allowing for informed feedback on its utility and accuracy. The high image count per physician strengthens the reliability of individual assessments and ensures robust exposure to varied dermatological cases.

Design and methods

Design

The study proceeded as follows:

Healthcare practitioner's recruitment and image presentation

We developed a website to conduct the experiment. Participants, including dermatologists and primary care physicians, were required to log in to the website. They were then presented with a series of two questions structured as follows:

1. Based on the provided image, what diagnosis do you consider most appropriate? This question was accompanied by anamnesis inquiries regarding allergies, ongoing treatments, and other relevant medical history, such as systemic symptoms that could be related to conditions like GPP.
2. Considering both the image and the analysis provided by the AI, what diagnosis do you deem most appropriate? In this instance, the same information from question 1 was supplemented with the top 5 diagnoses and their respective confidence levels, calculated by Legit.Health's diagnosis support algorithm based on the image.

Each participant was presented with a total of 100 cases or images to review. These images had been previously confirmed by dermatologists and were extracted from dermatology atlases or previous research of Boehringer Ingelheim. The conditions were distributed as follows:

Condition	ICD-11 code	Number of images
Generalised pustular psoriasis	EA90.40	10
Eczematous dermatitis	EA89	10
Acute generalised exanthematous pustulosis	EH67.0	5
Acne	ED80	5
Acné conglobata	ED80.41	10
Severe inflammatory acne	ED80.4	5
Seborrheic keratosis	2F21.0	5
Seborrheic dermatitis	EA81	5
Palmoplantar pustulosis	EA90.42	5
Plaque psoriasis	EA90.0	5
Pemphigus vulgaris	EB40.0	5
Impetigo	1B72	10
Hidradenitis suppurativa	ED92.0	10
Subcorneal pustular dermatosis	EB2Y	5
Tinea corporis	1F28.Y	5

The list of conditions includes the target condition GPP, as well as similar conditions such as subcorneal pustular dermatosis and palmoplantar pustulosis. It also covers common conditions treated in primary care that can be confused with GPP, such as dermatitis. Pigmented lesions are not relevant to this experiment.

All this information was recorded in a database and exported to a CSV file, which was subsequently used for further analysis. The analysis was conducted using the Python programming language and statistical libraries such as numpy and pandas. Statistical measures, including the P-value, were calculated to either accept or reject the hypothesis. Additionally, metrics were calculated based on pathology and medical specialization.

Number of subjects

A total of 15 HCPs (11 primary care physicians and 4 dermatologists) were recruited in this study.

Initiation Date

June 01^rd, 2024

Completion Date

September 15^rd, 2024

Duration

The study spanned a total duration of 4 months, encompassing the time needed for tasks such as the creation of the website, database closure and editing, data analysis, and the preparation of the final study report after the recruitment of the last subject.

Methods

The study employed a prospective observational analytical design to evaluate whether the use of Legit.Health improved the accuracy of the diagnosis of pathologies that are difficult to diagnose, such as GPP or HS. This investigation encompassed a diverse cohort of 15 HCPs (dermatologists and primary care physicians). Data collection included the accuracy of the diagnosis of different pathologies with and without the use of Legit.Health and specially for the target pathologies, GPP and HS. The study adhered to strict ethical guidelines, ensuring patient confidentiality and compliance with international standards.

Results

For this study, 15 HCPs (11 primary care physicians and 4 dermatologists) were included. Among them, 9 completed the entire process, while the remaining reviewed a partial number of images, specifically 99, 93, 93, 80, 77 and 68 respectively.

The integration of Legit.Health led to a significant improvement across all diagnostic metrics for healthcare professionals (HCPs):

• Diagnostic Accuracy: Increased by 15.12%, rising from 47.94% to 63.06% (95% CI: 57-69).
• Diagnostic Sensitivity: Increased by 18.43%, rising from 52.61% to 71.04% (95% CI: 69-73).
• Diagnostic Specificity: Increased by 19.38%, rising from 56.45% to 75.83% (95% CI: 74-77).

These improvements were even more substantial in the subgroup of rare diseases (GPP, Acne Conglobata, Palmoplantar Pustulosis, Subcorneal Pustular Dermatosis, AGEP, and Pemphigus Vulgaris):

• Rare Disease Accuracy: Increased by 26.77% (from 25.56% to 57.88%).
• Rare Disease Sensitivity: Increased by 25.56% (from 21.04% to 46.59%).
• Rare Disease Specificity: Increased by 23.50% (from 38.69% to 62.19%).

These improvements were particularly pronounced among primary care physicians (PCPs), who achieved a diagnostic accuracy of 61.71% (up from 44.71%) and a sensitivity of 71.04%. For rare diseases, PCPs saw a 32.10% increase in accuracy. Dermatologists also showed gains, with accuracy for rare diseases increasing by 12.97% (from 48.15% to 61.11%).

About the targeted pathologies, for GPP the use of Legit.Health improved the doctor's diagnosis in 32.32% of cases. For HS, Legit.Health improved doctor's diagnoses in 10.11% of cases.

Conclusions

Legit.Health's medical device significantly enhanced the diagnostic performance for dermatological conditions among healthcare professionals. On average, diagnostic accuracy improved by 15.12%, while sensitivity and specificity saw even greater gains of approximately 18-19%. The impact was most profound in rare diseases, where diagnostic accuracy increased by nearly 27% across all specialties, and by 32% for primary care practitioners.

Legit.Health's medical device significantly enhanced the diagnostic accuracy for generalized pustular psoriasis (GPP) among healthcare professionals, doubling the diagnosis rate and increasing it by 120% in primary care.

The device proved especially beneficial in primary care settings, where PCPs experienced a 17% absolute increase in diagnostic accuracy for general conditions and a 32% increase for rare diseases. Significant positive results were also observed for specific target pathologies like GPP, where the use of Legit.Health improved the doctor's diagnosis in 32.32% of cases.

In the dermatologists' data, while accuracy improved by 8.39% overall, the improvement for rare diseases was 12.97%. The overall increase in specificity and sensitivity for dermatologists underscores the device's utility even for experts, particularly when encountering rare conditions.

Introduction

Dermatological conditions represent a significant portion of primary care consultations, constituting approximately 5% of all visits. However, discrepancies between diagnoses made by primary care physicians and dermatologists remain substantial, with concordance rates between 57% and 65.52%. This gap in expertise often leads to misdiagnoses, incorrect referrals, and delays in appropriate treatment, particularly in rare and severe conditions like generalized pustular psoriasis (GPP) and hidradenitis suppurativa (HS). The limited availability of dermatologists, especially in rural areas, further complicates patient care, underscoring the need for innovative solutions to optimize resource allocation and improve diagnostic accuracy.

Teledermatology has shown promise in reducing the pressure on in-person consultations by enabling remote assessments. However, the use of artificial intelligence (AI) presents a transformative opportunity to enhance the diagnostic capabilities of primary care physicians. Legit.Health, an AI-based medical device, has already been validated in the diagnosis of skin conditions and offers advanced tools, such as the automatic scoring of GPP severity using the AGPPGA system. This pilot study aims to evaluate whether the use of the Legit.Health medical device can improve the diagnosis of complicated pathologies with a low incidence but a great impact on the patient's quality of life, such as GPP or also HS.

Material and methods

Product Description

This section contains a short summary of the device. A complete description of the intended purpose, including device description, can be found in the record Legit.Health Plus description and specifications.

Product description

The device is a computational software-only medical device leveraging computer vision algorithms to process images of the epidermis, the dermis and its appendages, among other skin structures. Its principal function is to provide a wide range of clinical data from the analyzed images to assist healthcare practitioners in their clinical evaluations and allow healthcare provider organisations to gather data and improve their workflows.

The generated data is intended to aid healthcare practitioners and organizations in their clinical decision-making process, thus enhancing the efficiency and accuracy of care delivery.

The device should never be used to confirm a clinical diagnosis. On the contrary, its result is one element of the overall clinical assessment. Indeed, the device is designed to be used when a healthcare practitioner chooses to obtain additional information to consider a decision.

Intended purpose

The device is a computational software-only medical device intended to support health care providers in the assessment of skin structures, enhancing efficiency and accuracy of care delivery, by providing:

• quantification of intensity, count, extent of visible clinical signs
• interpretative distribution representation of possible International Classification of Diseases (ICD) categories.

Intended previous uses

No specific intended use was designated in prior stages of development.

Product changes during clinical research

The device maintained a consistent performance and features throughout the entire clinical research process. No alterations or modifications were made during this period.

Clinical Investigation Plan

Objectives

This study aims to validate that the information provided by the device increases the true accuracy of healthcare professionals (HCPs) in the diagnosis of generalized pustular psoriasis (GPP).

Design (type of research, assessment criteria, methods, active group, and control group)

This is a prospective observational and cross-sectional study. The study does not involve an active or control group, as the physicians will be their control group, firstly without using Legit.Health and after making their diagnosis, using Legit.Health to assess if they want to change their diagnosis or keep it. The assessment criteria include the assessment of different images with pathologies such as GPP or HS and their diagnosis. The study employs a variety of methods, including data collection through websites or photograph analysis.

Ethical considerations

This study adhered to international Good Clinical Practice (GCP) guidelines, the Declaration of Helsinki in its latest amendment, and applicable international and national regulations. As applicable, approval from the relevant Ethics Committee was obtained prior to the initiation of the study. When applicable, modifications to the protocol were reviewed and approved by the Principal Investigator (PI) and subsequently evaluated by the Ethics Committee before subjects were enrolled under a modified protocol.

This study was conducted in compliance with European Regulation 2016/679, of 27 April, concerning the protection of natural persons with regard to the processing of personal data and the free movement of such data (General Data Protection Regulation, GDPR), and Organic Law 3/2018, of 5 December, on the Protection of Personal Data and the guarantee of digital rights. In accordance with these regulations, no data enabling the personal identification of participants was collected, and all information was managed securely in an encrypted format.

Participants were informed both orally and in writing about all relevant aspects of the study, with the information being tailored to their level of understanding. They were provided with a copy of the informed consent form and the accompanying patient information sheet. Adequate time was given to patients to ask questions and fully comprehend the details of the study before providing their consent.

The PI was responsible for the preparation of the informed consent form, ensuring it included all elements required by the International Conference on Harmonisation (ICH), adhered to current regulatory guidelines, and complied with the ethical principles of GCP and the Declaration of Helsinki.

The original signed informed consent forms were securely stored in a restricted access area under the custody of the PI. These documents remained at the research site at all times. Participants were provided with a copy of their signed consent form for their records.

Data confidentiality

Current legislation will be complied with in terms of data confidentiality protection (European Regulation 2016/679, of 27 April, on the protection of natural persons with regard to the processing of personal data and the free movement of such data and Organic Law 3/2018, of 5 December, on Personal Data Protection and guarantee of digital rights). For this purpose, when applicable, each participant will receive an alphanumeric identification code in the study that will not include any data allowing personal identification (coded CRD). The Principal Investigator will have an independent list that will allow the connection of the identification codes of the patients participating in the study with their clinical and personal data. This document will be filed in a secure area with restricted access, under the custody of the Principal Investigator and will never leave the centre.

Once the paper CRDs are completed and closed by the Principal Investigator, the data will be transferred to a database.

As in the CRDs, the Database will comply with current legislation in terms of data confidentiality protection (European Regulation 2016/679, of 27 April, on the protection of natural persons about the processing of personal data and the free movement of such data and Organic Law 3/2018, of 5 December, on the Protection of Personal Data and guarantee of digital rights) in which no data allowing personal identification of patients will be included.

Data Quality Assurance

The Principal Investigator is responsible for reviewing and approving the protocol, signing the Principal Investigator commitment, guaranteeing that the persons involved in the centre will respect the confidentiality of patient information and protect personal data, and reviewing and approving the final study report together with the sponsor. All the clinical members of the research team assess the eligibility of the patients in the study, inform and request written informed consent, collect the source data of the study in the clinical record and transfer them to the Data Collection Notebook (DCN) or Data Collection Forms (CRF).

Subject Population

This study enrolled both primary care physicians and dermatologists. At the end of the study, 15 HCPs were enrolled. These doctors should evaluate 100 images of different skin pathologies and diagnose them.

Inclusion Criteria

• Board-certified primary care physicians and dermatologists, regardless of their professional experience.
• Good quality images of patients with GPP.
• Good quality images of patients with HS.
• Good quality images of patients with pathologies that can be confused with GPP or HS leading to a wrong diagnosis.

Exclusion Criteria

• Images of patients with pathologies different from GPP or HS that can be easily identified.

Statistical Analysis

To estimate the correlation between diagnoses with and without using Legit.Health, we analyzed the concordance between diagnoses for both primary care physicians and dermatologists. We analyzed if Legit.Health reinforced the diagnosis of the physicians (after observing the results of Legit.Health, the doctor maintains the diagnosis when his answer matches that of the solution), if Legit.Health improves the practitioner's diagnosis (the doctor changes the diagnosis when his answer does not match that of the solution) if it has no impact (The doctor does not change the diagnosis even though his answer does not match that of the solution) and if it has a negative impact (The doctor changes the diagnosis for an answer that does not match that of the solution). Performance metrics including diagnostic accuracy, sensitivity, and specificity were also calculated and compared against the state of the art.

Derived from performanceClaims.ts (for comparison):

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Results

Initiation and Completion Date

June 6^th, 2024 September 15^th, 2024

Subject and Investigational Product Management

A total of 15 HCPs were recruited for this study, 11 primary care physicians and 4 dermatologists. Each physician was presented with 100 images in order to review them and make a diagnosis of the pathology. This meticulous selection process ensures the integrity and validity of the study's findings. The investigational products were stored and handled following strict protocols. This included proper storage conditions, handling procedures, and documentation of product usage. The accountability and traceability of investigational products were rigorously maintained throughout the study.

Subject Demographics

The study did not place specific emphasis on gender, age, or nationality as primary factors of investigation. Instead, it encompassed a diverse physician cohort with different specialities.

Clinical Investigation Plan (CIP) Compliance

The study adhered to all aspects outlined in the CIP. This ensured that the research was conducted in accordance with established protocols, procedures, and ethical standards. Any deviations from the CIP were duly documented and appropriately addressed. The compliance with the CIP was rigorously monitored throughout the duration of the study to uphold the integrity and validity of the research findings.

CIP Deviations

Six out of 15 healthcare professionals (40%) completed a partial number of images (ranging from 68 to 99 images per practitioner) rather than the full 100-image protocol. This deviation occurred due to the high clinical workload of the practitioners during the study period, who completed as many images as their schedules permitted. Despite this partial completion, the total number of images evaluated across all practitioners remained substantial and clinically meaningful: the six practitioners who completed partial reviews contributed 549 images (99+93+93+80+77+68), while the nine practitioners who completed the full protocol contributed 900 images, for a combined total of 1,449 images analyzed. This represents 96.6% of the planned 1,500-image dataset. The high volume of evaluations completed by all practitioners provided sufficient and valuable data to support robust statistical analysis and meaningful clinical conclusions. The study's findings and acceptance criteria achievements remain valid despite this minor protocol deviation.

Analysis

Primary Analyses

Diagnosis support

In this study, a total of 15 healthcare professionals (HCPs) participated, comprising 11 primary care doctors and 4 dermatologists. Among them, 9 completed the entire process, while the remaining reviewed a partial number of images, specifically 99, 93, 93, 80, 77 and 68 respectively.

We conducted a McNemar test to analyze the information provided by Legit.Health impacts on the healthcare professionals' diagnostics. Overall, the HCPs demonstrated a significant improvement in all diagnostic performance metrics when using Legit.Health. Our analysis, supported by a very low p-value, revealed the following findings for the combined cohort of HCPs:

• Accuracy: Increased from 47.94% to 63.06% (an absolute increase of 15.12%).
• Sensitivity: Increased from 52.61% to 71.04% (an absolute increase of 18.43%).
• Specificity: Increased from 56.45% to 75.83% (an absolute increase of 19.38%).

The qualitative impact on diagnostics was as follows:

• Legit.Health reinforces practitioners' diagnostics in 46.13% of the cases
• Legit.Health improves practitioners' diagnostics in 16.61% of the cases
• Legit.Health does not have any impact on practitioners' diagnostics in 35.42% of the cases
• Legit.Health has a negative impact on practitioners' diagnostics in 1.77% of the cases

When focusing on primary care physicians (PCPs):

• Accuracy: Increased from 44.71% to 61.71% (an absolute increase of 17.00%).
• Sensitivity: Increased from 52.61% to 71.04% (an absolute increase of 18.43%).
• Specificity: Increased from 56.45% to 75.83% (an absolute increase of 19.38%).

For dermatologists:

• Accuracy: Increased from 57.25% to 65.65% (an absolute increase of 8.39%).
• Sensitivity: Increased from 61.64% to 71.01% (an absolute increase of 9.37%).
• Specificity: Increased from 62.47% to 73.08% (an absolute increase of 10.61%).

The results of diagnostic performance are summarized in the table below:

HCP Group	Metric	Without Device (%)	With Device (%)	Improvement (%)
All specialties	Accuracy	47.94	63.06	15.12
All specialties	Sensitivity	52.61	71.04	18.43
All specialties	Specificity	56.45	75.83	19.38
Primary Care	Accuracy	44.71	61.71	17.00
Primary Care	Sensitivity	52.61	71.04	18.43
Primary Care	Specificity	56.45	75.83	19.38
Dermatologists	Accuracy	57.25	65.65	8.39
Dermatologists	Sensitivity	61.64	71.01	9.37
Dermatologists	Specificity	62.47	73.08	10.61

Acceptance Criteria Verification

The Clinical Investigation Plan specified the following acceptance criteria:

• Primary care physicians: ≥10% improvement in diagnostic accuracy
• Dermatologists: ≥5% improvement in diagnostic accuracy

Achievement Status:

• Primary care physicians: Achieved 17.00% improvement in diagnostic accuracy (44.71% → 61.71%), exceeding the ≥10% criterion. ✓ ACCEPTED
• Dermatologists: Achieved 8.39% improvement in diagnostic accuracy (57.25% → 65.65%), exceeding the ≥5% criterion. ✓ ACCEPTED

Both primary and secondary healthcare professional groups met or exceeded their respective acceptance criteria, demonstrating that Legit.Health Plus successfully improved diagnostic accuracy as specified in the study protocol.

An analysis by pathology identified significant impacts for certain conditions, as detailed in the table below:

Condition	Accuracy (%)	Accuracy with Legit.Health (%)	Difference (%)	p-value
Generalised pustular psoriasis	23.70	46.67	22.97	0.00001
Eczematous dermatitis	71.34	73.17	1.83	0.62906
Acute generalized exanthematous pustulosis	5.00	5.00	0.00	1.00000
Acne	37.50	54.69	17.19	0.00739
Acné conglobata	18.40	37.60	19.20	0.00000
Severe inflammatory acne	10.61	43.94	33.33	0.0000
Seborrheic keratosis	94.67	96.00	1.33	1.00000
Seborrheic dermatitis	75.34	90.41	15.07	0.00098
Palmoplantar pustulosis	45.31	79.69	34.38	0.00002
Plaque psoriasis	91.89	97.30	5.41	0.12500
Pemphigus vulgaris	28.77	56.16	27.39	0.0000
Impetigo	57.43	75.68	18.25	0.0000
Hidradenitis suppurativa	85.48	93.60	8.12	0.00195
Subcorneal pustular dermatosis	2.67	2.67	0.00	1.00000
Tinea corporis	35.96	62.50	26.54	0.00004

We separated the results per pathology into two tables, one for primary care doctors and another for dermatologists.

Primary care doctors

Condition	Accuracy (%)	Accuracy with Legit.Health (%)	Difference (%)
Generalised pustular psoriasis	20.20	44.44	24.24
Eczematous dermatitis	68.33	70.83	2.50
Acute generalised exanthematous pustulosis	0.00	0.00	0.00
Acne	36.36	59.09	22.73
Acné conglobata	21.18	47.06	25.88
Severe inflammatory acne	10.87	50.00	39.13
Seborrheic keratosis	92.73	94.55	1.82
Seborrheic dermatitis	69.81	88.68	18.87
Palmoplantar pustulosis	32.61	80.43	47.82
Plaque psoriasis	88.89	96.30	7.41
Pemphigus vulgaris	22.64	43.40	20.76
Impetigo	50.00	71.30	21.30
Hidradenitis suppurativa	82.02	92.22	10.20
Subcorneal pustular dermatosis	0.00	0.00	0.00
Tinea corporis	29.23	59.38	30.15

Dermatologists

Because of the quantity of images per pathology and the total number of dermatologists involved, the evidence is inconclusive and may be biased.

Condition	Accuracy (%)	Accuracy with Legit.Health (%)	Difference (%)
Generalised pustular psoriasis	33.33	52.78	19.45
Eczematous dermatitis	79.55	79.55	0.00
Acute generalized exanthematous pustulosis	18.75	18.75	0.00
Acne	40.00	45.00	5.00
Acné conglobata	12.50	17.50	5.00
Severe inflammatory acne	10.00	30.00	20.00
Seborrheic keratosis	100.00	100.00	0.00
Seborrheic dermatitis	90.00	95.00	5.00
Palmoplantar pustulosis	77.78	77.78	0.00
Plaque psoriasis	100.00	100.00	0.00
Pemphigus vulgaris	45.00	90.00	45.00
Impetigo	77.50	87.50	10.00
Hidradenitis suppurativa	94.29	97.14	2.85
Subcorneal pustular dermatosis	10.00	10.00	0.00
Tinea corporis	54.17	70.83	16.66

Target pathologies

If we focus on primary care doctors and target conditions like generalized pustular psoriasis (GPP), hidradenitis suppurativa, and palmoplantar pustulosis, we will find the following results.

For GPP, with a p-value of 0.00015:

• Legit.Health supports doctors' diagnoses in 12.12% of cases.
• Legit.Health improves doctors' diagnoses in 32.32% of cases.
• Legit.Health has no impact on doctors' diagnoses in 47.47% of cases.
• Legit.Health negatively affects doctors' diagnoses in 8.08% of cases.

For hidradenitis suppurativa, with a p-value of 0.00391:

• Legit.Health supports doctors' diagnoses in 82.02% of cases.
• Legit.Health improves doctors' diagnoses in 10.11% of cases.
• Legit.Health has no impact on doctors' diagnoses in 7.87% of cases.
• Legit.Health does not affect negatively doctors' diagnoses.

For palmoplantar pustulosis, with a p-value of 0:

• Legit.Health supports doctors' diagnoses in 32.61% of cases.
• Legit.Health improves doctors' diagnoses in 47.83% of cases.
• Legit.Health has no impact on doctors' diagnoses in 19.57% of cases.
• Legit.Health does not affect negatively doctors' diagnoses.

Rare Disease Analysis

A specific subgroup analysis was conducted for rare diseases, defined as Generalized Pustular Psoriasis (GPP), Acne Conglobata, Palmoplantar Pustulosis, Subcorneal Pustular Dermatosis, Acute Generalized Exanthematous Pustulosis (AGEP), and Pemphigus Vulgaris.

For the combined cohort of healthcare professionals (HCPs):

• Accuracy: Increased by 26.77% (from 25.56% to 57.88%, 95% CI: 56-59).
• Sensitivity: Increased by 25.56% (from 21.04% to 46.59%, 95% CI: 41-50).
• Specificity: Increased by 23.50% (from 38.69% to 62.19%, 95% CI: 61-63).

For primary care physicians (PCPs):

• Accuracy: Increased by 32.10% (from 24.34% to 56.44%, 95% CI: 55-57).
• Sensitivity: Increased by 25.21% (from 19.33% to 44.55%, 95% CI: 39-49).
• Specificity: Increased by 24.73% (from 36.64% to 61.36%, 95% CI: 60-62).

For dermatologists:

• Accuracy: Increased by 12.97% (from 48.15% to 61.11%, 95% CI: 59-63).
• Sensitivity: Increased by 16.44% (from 35.89% to 52.33%, 95% CI: 45-59).
• Specificity: Increased by 15.41% (from 55.67% to 71.08%, 95% CI: 69-73).

Note on Subgroup Analysis Power: The rare disease subgroup analysis, particularly for dermatologists (n=4), may have limited statistical power due to the small number of specialists. However, the substantial improvements observed across all metrics for the primary care subgroup (n=11) provide robust evidence of device effectiveness in rare disease diagnosis for this key population. The consistency of improvements across multiple rare disease categories and evaluation methods supports the clinical meaningfulness of these findings despite the smaller dermatologist subgroup size.

Adverse Events and Adverse Reactions to the Product

Throughout the study, no adverse events or adverse reactions related to the investigational product have been observed. Participants have not experienced any negative reactions or side effects associated with the use of the product. This indicates a favourable safety profile of the investigational product in the context of this study.

Product Deficiencies

No deficiencies in the product have been observed during the course of this study. As a result, no corrective actions have been deemed necessary. The product has demonstrated consistent performance in accordance with the study's objectives.

Subgroup Analysis for Special Populations

In the context of the analyzed pathologies, no special population subgroups were identified for this study. The research primarily focused on the specified physician population without subgroup differentiation.

Discussion and Overall Conclusions

Clinical Performance, Efficacy, and Safety

Summary of Performance Claims:

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Conclusions

Legit.Health significantly improved the diagnosis of generalised pustular psoriasis (GPP) and other rare conditions across all healthcare professional tiers. For primary care physicians evaluating GPP, diagnostic accuracy improved from 20.20% to 44.44%, representing a 120% relative increase. When considering both primary care physicians and dermatologists combined, GPP diagnostic accuracy improved from 23.70% to 46.67%, a 96.8% relative improvement. Dermatologists showed an improvement from 33.33% to 52.78% for GPP.

Other rare conditions such as HS or palmoplantar pustulosis also benefited markedly. Hidradenitis suppurativa (HS) diagnostic accuracy improved by 8.12% overall—primary care +10.2%, dermatologists +3%. For palmoplantar pustulosis, primary care achieved an outstanding 146% relative increase (from 33% to 80%), while dermatologists' accuracy remained at 77%.

Early diagnosis is critical: in primary care, prompt recognition enables faster specialist referral, overcoming gaps in practitioner experience (Strober et al. 2021; Contanzo et al. 2022). Multiple studies document prolonged diagnostic delays in these rare diseases (Kokolakis et al. 2019; Willmen et al. 2024), which worsen patient quality of life, reduce income, and increase healthcare costs (Kokolakis et al. 2019).

Overall, across all healthcare professionals combined, diagnostic accuracy rose from 47.94% to 63.06% (95% CI: 57-69), representing a 31.5% relative gain. Primary care physicians improved from 44.71% to 61.71% (a 38% relative increase), and dermatologists from 57.25% to 65.65% (a 14.7% relative increase).

The device's impact extended beyond accuracy, showing substantial improvements in other diagnostic performance metrics. Overall, diagnostic sensitivity increased by 18.43% (from 52.61% to 71.04%, 95% CI: 69-73) and specificity rose by 19.38% (from 56.45% to 75.83%, 95% CI: 74-77). These gains were consistent across both PCPs and dermatologists, demonstrating the tool's effectiveness in enhancing both the detection of conditions and the correct exclusion of alternatives.

Enhanced diagnostic accuracy in primary care yields more reliable lesion identification and sharper triage (Escalé-Besa A et al. 2023). Teledermatology triage greatly improves referral precision, enabling most patients to be managed in primary care and the most severe cases to be referred to dermatology and cut mean wait for in-person dermatology (Giavina-Bianchi M et al. 2020). This synergy accelerates specialist access and optimises outcomes.

Timely access to specialist care enables patients to receive the correct treatment sooner, which is associated with better clinical outcomes and reduced disease burden, specially in malignant conditions, where a delayed detection can lead to more advanced-stage cancers requiring far more expensive treatment (Maul LV et al. 2024). These results underscore that prompt dermatologist evaluation (avoiding delay) leads to earlier correct therapy, better survival/quality of life, and a markedly lower disease burden(Maul LV et al. 2024).

Moreover, minimising diagnostic and referral delays can lead to significant cost savings for the healthcare system by avoiding unnecessary consultations, treatments, and complications associated with delayed care. The elimination of needless specialist visits can cut costs and shorten waits. Overall, improving diagnostic and referral efficiency reduces costly duplicated consultations and avoids ineffective delays - yielding net healthcare savings(Liu KJ et al. 2016).

Regarding the dermatologist's data, it is important to highlight that the results were not statistically significant at the pathology level due to two factors we identified. First, the lower number of participants. We had only four dermatologists, while primary care had eleven participants. This is not a design flaw because the focus was on primary care, but it is a limitation when conducting a detailed analysis. Additionally, the dermatologists had a high level of expertise, especially in hidradenitis suppurativa (HS). This, combined with the relatively average complexity of the HS cases in the experiment, may explain why the tool was not useful for dermatologists in the case of HS. However, this does not mean it is not useful for other dermatologists or dermatologists in general.

In summary, Legit.Health Plus had a substantial impact on the diagnostic capabilities of healthcare professionals, particularly primary care doctors who have less specialisation in dermatology. It also significantly benefited dermatologists when diagnosing rare conditions like GPP, which they encounter infrequently in their practice.

References

1. Strober B, Kotowsky R, Medeiros R et al. Unmet Medical Needs in the Treatment and Management of Generalized Pustular Psoriasis Flares: Evidence from a Survey of Corrona Registry Dermatologis. Dermatol Ther (Heidelb) 2021;11(2): 529-541. doi: 10.1007/s13555-021-00493-0. (https://doi.org/10.1007/s13555-021-00493-0).

2. Costanzo A, Bardazzi C, De Simeone G, et al. Pustular psoriasis with a focus on generalized pustular psoriasis: classification and diagnostic criteria. An Italian expert consensus. Ital J Dermatol Venerol 2022;157(6): 489-496. doi: 10.23736/S2784-8671.22.07415-1. (https://doi.org/10.23736/S2784-8671.22.07415-1).

3. Kokolakis G, Wolk S, Schneider-Burrus S, et al. Delayed Diagnosis of Hidradenitis Suppurativa and its Effect on Patients and Healthcare System. Dermatology 2019;236(5): 421-430. doi: 10.1159/000508787. (https://doi.org/10.1159/000508787).

4. Willmen L, Völkel L, Willmen T, et al. The economic burden of diagnostic uncertainty on rare disease patients. BMC Health Serv Res 2024;24(1): 1388. doi: 10.1186/s12913-024-11763-w. (https://doi.org/10.1186/s12913-024-11763-w).

5. Escalé-Besa A, Yélamos O, Vidal-Alaball J, et al. Exploring the potential of artificial intelligence in improving skin lesion diagnosis in primary care. Sci Rep 2023;13(1): 4293. doi: 10.1038/s41598-023-31340-1. (https://doi.org/10.1038/s41598-023-31340-1).

6. Giavina-Bianchi M, Santos AP, Cordioli E. Teledermatology reduces dermatology referrals and improves access to specialists. EClinicalMedicine 2020; 29-30. doi: 10.1016/j.eclinm.2020.100641. (https://doi.org/10.1016/j.eclinm.2020.100641).

7. Maul LV, Jamiolkowski D, Lapides RA, et al. Health Economic Consequences Associated With COVID-19-Related Delay in Melanoma Diagnosis in Europe. AMA Netw Open 2024;7(2):2356479. doi: 10.1001/jamanetworkopen.2023.56479. (https://doi.org/10.1001/jamanetworkopen.2023.56479).

8. Liu KJ, Hartman RI, Joyce C, et al. Modeling the Effect of Shared Care to Optimize Acne Referrals From Primary Care Clinicians to Dermatologists. JAMA Dermatol 2016;152(6):655-660. doi: 10.1001/jamadermatol.2016.0183. (https://doi.org/10.1001/jamadermatol.2016.0183).

Implications for Future Research

The positive outcomes of this study pave the way for several avenues of future research. Firstly, helping to improve the diagnosis of difficult-to-diagnose pathologies such as GPP or HS, which significantly impacts the quality of life of patients who suffer from them.

On the other hand, exploring the integration of artificial intelligence and machine learning techniques to refine the tool's diagnostic capabilities warrants attention. This could lead to even more accurate and reliable assessments, potentially revolutionizing the field of dermatology.

Additionally, conducting long-term studies to evaluate the impact of the device on patient outcomes, including treatment adherence and quality of life, would provide a comprehensive understanding of its broader clinical implications.

Limitations of Clinical Research

The main limitations of the pilot included several factors that may influence the perception and effectiveness of the AI-based device. Firstly, the acceptance and trust of healthcare professionals in these emerging technologies can vary significantly. The device's effectiveness may be compromised if users are not fully convinced of its accuracy or usefulness, thereby affecting the overall perception of its performance.

Additionally, image quality is crucial for the device's performance. Issues such as low-quality photographs, errors in cropping lesions, or variations in lighting and focus could deteriorate the quality of the data received by the system, which may negatively influence the evaluation and perception of its effectiveness by the researchers.

Variability in image conditions is also an important aspect to consider. Differences in lighting, colour, shape, size, and focus of the images, along with the number of images available for each patient, can affect the accuracy of the results. High variability in images of the same patient or an insufficient number of representative images can lead to a decrease in the expected diagnostic accuracy of the device.

Additionally, the consistency of investigators in using Legit.Health is crucial. Variations in how diligently investigators use the device can impact the pilot's findings. If the investigators are not consistent in their use of the device, it can lead to unreliable results and affect the overall assessment of its efficacy.

Regarding the partial completion of image reviews by six investigators (40% of the cohort), who completed 68-99 images rather than the full 100-image protocol, this represents a minor protocol deviation. However, it is important to note that the total dataset of 1,449 images analyzed (96.6% of planned 1,500 images) remains statistically robust and clinically meaningful. The large volume of evaluations provides sufficient power to support the study's conclusions. Despite the incomplete protocol compliance, the consistency of improvements across multiple metrics and subgroups demonstrates the robustness of the findings. All analyses were conducted on the full available dataset, ensuring that no data was lost and that the conclusions are based on comprehensive evidence.

Another limitation could be the Hawthorne effect, where pilot subjects may change their behaviour simply because they know they are being observed. This awareness can influence their decisions and actions within the pilot, potentially skewing the results and not accurately reflecting how the device would be used in a non-study environment. Future prospective studies should consider implementing blinded assessment protocols or non-interventional observational designs where investigators are unaware of the device's algorithmic processes, which could help minimize this effect and provide more representative real-world performance data.

Ethical Aspects of Clinical Research

The conduct of this study adheres to international Good Clinical Practice standards and is in compliance with the Declaration of Helsinki in its latest active amendment. It also conforms to international and national rules and regulations.

The study did not require Ethics Committee approval because it involved only the retrospective and prospective analysis of fully anonymized clinical images originally sourced from public dermatology databases and atlases. All images in the study were completely de-identified and contained no information that would allow the identification of any individuals. The research did not involve the recruitment of patients, any form of intervention, or changes to standard clinical practice. As such, the research constitutes an observational, non-interventional study of public data, which under applicable regulatory frameworks does not require ethics committee oversight.

The study has been conducted in accordance with European Regulation 2016/679, of 27 April, on the protection of natural persons about the processing of personal data and the free movement of such data. Additionally, it adheres to the Spanish Organic Law 3/2018, of 5 December, on the Protection of Personal Data and guarantee of digital rights concerning data processing. No data that allows the personal identification of subjects has been included in the analysis, as all images were sourced from public databases and were fully anonymized. All information has been managed in an encrypted manner.

Physicians received comprehensive oral information about the study, tailored to their level of understanding. The main investigator ensured that all participants had sufficient time to ask questions and clarify any doubts regarding the study details. Each physician signed a contract documenting their participation and understanding of the study procedures. The original signed contracts have been securely stored in a restricted access area under the custody of the Principal Investigator, with copies provided to each participant.

The Data Controller for this study is the research team. Legit.Health, the Data Processor, is not responsible for the processing of the data included in the Software or its users. The storage and handling of data and photographs is aligned with the European Regulation 2016/679 of 27 April on the protection of natural persons with regard to the processing of personal data and the free movement of such data and the Organic Law 3/2018 of 5 December on the Protection of Personal Data and guarantee of digital rights. At the conclusion of the study, all information stored in the device will be completely and permanently deleted.

The device complies with current legislation on the protection and confidentiality of personal data. Appropriate technical and organizational security measures are in place to ensure the security of personal data and prevent its alteration, loss, unauthorized processing or access.

Investigators and Administrative Structure of Clinical Research

Brief Description

This CIP has been conducted in conjunction with the participating medical staff, AI Labs Group S.L. (Legit.Health) and Boehringer Ingelheim.

Investigators

Principal investigator

• Dr. Antonio Martorell Calatayud

Collaborators

• Medical staff
  • Dr. Mari Carmen Galindo
  • Dr. Paco García Tolosa
  • Dr. Laura Yuste Hidalgo
  • Dr. Nuria Comabella
  • Dr. Marta Vázquez
  • Dr. David Palacios
  • Dr. Norma Alejandra Doria Carlin
  • Dr. Francisco José Esteban González
  • Dr. Alfonso José Valcarce Leonisio
  • Dr. José Antonio Arjona Sevilla
  • Dr. Javier Melgosa
  • Dr. Manuel Ballesteros Redondo
  • Dr. Esmeralda Silva
  • Dr. Ana Llull Ramos
  • Dr. Angela Patricia Guzmán
• AI Labs Group S.L.
  • Mr. Alfonso Medela
  • Dr. Alberto Sabater
  • Mrs. Alba Rodríguez

Investigator Qualifications

All healthcare professional investigators are board-certified physicians with a minimum of 5 years of clinical experience in their respective specialties (general medicine or dermatology). The research team received comprehensive training on the study protocol, the investigational device, and Good Clinical Practice principles. Training was conducted via presentation format covering protocol procedures, device functionality, and data entry requirements. Training attendance records and presentation materials are maintained as essential documents and are available for audit or inspection upon request.

External Organization

No additional organizations, beyond those previously mentioned, contributed to the clinical research. The study was conducted with the collaboration and resources of the specified entities.

Sponsor and Monitor

Boehringer Ingelheim

Report Annexes

• Instructions For Use (IFU) can be found in the protocol.

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 Design & Development Manager, JD-004 Quality Manager & PRRC
• Approver: JD-001 General Manager