R-TF-015-001 Clinical Evaluation Plan

Purpose

Article 61(3) of the MDR 2017/745 states that clinical evaluation must follow a defined and methodologically sound procedure, meaning that Clinical Evaluation Plans need to be established in advance and should define how the evaluation will be conducted. The MDR Annex XIV Part A provides further details on requirements.

This Clinical Evaluation Plan (CEP) is dedicated to stage 0 of the clinical evaluation process, adhering closely to the requirements outlined in the Medical Devices Regulation (MDR) 2017/745 and the guideline on medical devices and clinical evaluation (MEDDEV 2.7/1 rev4).

The evaluation and selection of the clinical data, the publications and the relevant observations to consider when providing and showing conformity with Regulation (EU) 2017/745 General Safety & Performance Requirements number 1, 2, 6 and 8 (requiring support from the clinical data) have been performed according to:

1. Requirements from Article 61 and Annex XIV from Regulation (EU) 2017/745.
2. Recommendations from the MDCG guidelines MDCG 2020-13, MDCG 2020-1 and MDCG 2020-5.
3. Recommendations from the MEDDEV 2.7/1 Rev.4 guideline.

The clinical evaluation that we develop and discuss through this Clinical Evaluation Report (CER) shows the evaluation of the clinical data related to the product Legit.Health Plus (hereinafter, "the device").

This Clinical Evaluation Reportand has the following purposes:

• Evaluating the conformity of the product towards the General Safety and Performance Requirements (GSPR) requiring clinical evidence from Regulation (EU) 2017/745.
• Evaluating of the clinical data compilated in order to demonstrate the acceptance of its valid clinical association, the technical performance and the clinical performance of the MDSW.
• Determining the evaluation and acceptability of the Benefit-risk ratio in the conditions when the product is used according to its intended use and indications, stated in its technical documentation.
• Compiling of all the clinical data collected through clinical investigations with the product, systematic bibliographic research of clinical literature, and information related to the product risk management, with special emphasis to the finding and management of the identification of unknown risks and/or secondary effects.

A CEP is a roadmap for conducting the clinical evaluation process. It includes the scope, methodological, and systematic approach to proceeding and concluding the clinical evaluation, to document it in a CER.

This plan applies to the device. The device is classified as a class IIb medical device. There is a previous version of the device that has been commercialized since 2020. The product is manufactured under a Conformity Assessment based on a Quality Management System in accordance with Chapter I of Annex IX of Regulation (EU) 2017/745 Medical Devices.

This CEP will be checked and, if necessary, updated in each milestone and/or reviews.

Scope of the clinical plan as part of the clinical evaluation

The clinical evaluation is based on a comprehensive analysis of available pre- and post-market clinical data that is relevant to the intended purpose of the device, including clinical performance data and clinical safety data.

There are discrete stages in performing a clinical evaluation:

• Stage 0: Define the scope, plan the clinical evaluation (also referred to as scoping and the clinical evaluation plan).
• Stage 1: Identify pertinent data.
• Stage 2: Appraise each individual data set, in terms of its scientific validity, relevance and weighting.
• Stage 3: Analyze the data, whereby conclusions are reached about
  • compliance with general safety and performance requirements, including its benefit/risk profile,
  • the contents of information materials supplied by the manufacturer (including the label, IFU of the device, available promotional materials, including accompanying documents possibly foreseen by the manufacturer),
  • residual risks and uncertainties or unanswered questions (including rare complications, long-term performance, safety under widespread use), whether these are acceptable for CE-marking, and whether they are required to be addressed during PMS.
• Stage 4: Finalize the clinical evaluation report.

Before a clinical evaluation is undertaken, the manufacturer should define its scope based on the General Performance and Safety Requirements that need to be addressed from a clinical perspective and the nature and history of the device.

The scope serves as a basis for further steps, including identifying pertinent data. The manufacturer sets up a description of the device under evaluation and a clinical evaluation plan.

A clinical evaluation is required to be critical. Therefore, it needs to identify, appraise, and analyze both favorable and unfavorable data.

Depending on the stage in the lifecycle of the product, considerations for setting up the CEP should include the following different aspects:

• The device description.
• Whether there are any design features of the device, or any indications or target populations, require specific attention.
• Information needed for evaluation of equivalence if equivalence may possibly be claimed.
• Information from similar devices from the market
• The risk management documents of the device
• The current knowledge/ state of the art in the corresponding medical field.
• Data source(s) and type(s) of data to be used in the clinical evaluation.
• Whether the manufacturer has introduced/ intends to introduce any relevant changes.
• Whether any specific clinical concerns have newly emerged and need to be addressed.
• PMS aspects - recall from similar devices.
• Needs for planning PMS activities: PMCF.

The scope of the CEP is limited to the device.

References

Reference document code	Reference document description
MDR 2017/745	Regulation (EU) 2017/745 of the European Parliament and of the Council of 5 April 2017 on medical devices
MEDDEV 2.7/1 revision 4	European Commission Guidelines on Medical Devices Clinical Evaluation
IMDRF/AE WG/N43FINAL:2020	IMDRF terminologies for categorized Adverse Event Reporting (AER): terms, terminology structure and codes
MDCG 2023-3	Questions and Answers on vigilance terms and concepts as outlined in the Regulation (EU) 2017/745 on medical devices
2023/C 163/06	Commission Guidance on the content and structure of the summary of the clinical investigation report
MDCG 2020-10/1 Rev.1MDCG 2020-10/2 Rev. 1	Guidance on safety reporting in clinical investigationsAppendix: Clinical investigation summary safety report form
MDCG 2020-1	Guidance on clinical evaluation (MDR) / Performance evaluation (IVDR) of medical device software
MDCG 2022-21	Guidance on Periodic Safety Update Report (PSUR) according to Regulation (EU) 2017/745 (MDR)
MDCG 2020-6	Regulation (EU) 2017/745: Clinical evidence needed for medical devices previously CE marked under Directives 93/42/EEC or 90/385/EEC
MDCG 2020-7	Guidance on PMCF plan template
MDCG 2020-8	Guidance on PMCF evaluation report template
IMDRF MDCE WG/N65FINAL:2021	Post-Market Clinical Follow-Up Studies
MDCG 2020-13	Clinical evaluation assessment report template
IMDRF MDCE WG/N56FINAL:2019	Clinical evaluation
IMDRF MDCE WG/N55 FINAL:2019	Clinical evidence
ISO 13485:2016, Adm 11	Quality Management Systems - Regulatory Requirements for Medical Devices
ISO 14971:2019	Medical devices - Application of Risk Management to Medical Devices

Acronyms and definitions

Acronyms

Acronyms	Definition
CEP	Clinical Evaluation Plan
CER	Clinical Evaluation Report
CIP	Clinical Investigation Plan
EU/EC	European Union / European Community
EMDN	European Medical Devices Nomenclature
FSCA	Field Safety Corrective Action
GSPR	General Safety and Performance Requirement
IFU	Instructions for Use
MDD	Medical Devices Directive
MDR	Medical Device Regulation
PICO	Population/ people/patient/ problem, Interventions, Comparison and Outcome
PMS	Post Market surveillance
PMCF	Post Market Clinical Follow Up
QMS	Quality Management System
SOTA	State of the Art
SRN	Single Registration Number
UDI/DI	Unique Device Identification / Device Identifier

Definitions

Term	Definition
Benefit / Risk Determination	The analysis of all assessments of benefit and risk of possible relevance for the use of the device for the intended purpose, when used in accordance with the intended purpose given by the manufacturer (MDR, Article 2(24))
Clinical Data	Information concerning safety or performance that is generated from the use of a device and is sourced from the following:clinical investigation(s) of the device concerned,clinical investigation(s) or other studies reported in scientific literature, of a device for which equivalence to the device in question can be demonstrated,reports published in the peer-reviewed scientific literature on other clinical experience of either the device in question or a device for which equivalence to the device in question can be demonstrated,clinically relevant information coming from post-market surveillance, in particular, the post-market clinical follow-up (MDR).
Clinical Development Plan	A plan that indicates progression from exploratory investigations, such as first-in-man studies, feasibility and pilot studies, to confirmatory investigations, such as pivotal clinical investigations, and a PMCF for a device or product under evaluation (MDR Annex XIV PART A 1(a)).
Clinical Evaluation	A systematic and planned process to continuously generate, collect, analyze and assess the clinical data pertaining to a device in order to verify the safety and performance, including clinical benefits, of the device when used as intended by the manufacturer (MDR).A methodologically sound ongoing and continuous procedure to collect, appraise, and analyze clinical data pertaining to a medical device and to analyze whether there is sufficient clinical evidence to confirm compliance with relevant Essential Requirements or Principles for clinical safety and performance of that device when used in accordance with the manufacturer's instructions for use (MEDDEV 2.7/1).
Clinical Evidence	Clinical data and clinical evaluation results pertaining to a device of sufficient amount and quality to allow a qualified assessment of whether the device is safe and achieves the intended clinical benefit(s) when used as intended by the manufacturer (MDR).
Clinical Performance	Article 2 (52) MDR defines clinical performance as the ability of a device, resulting from any direct or indirect medical effects which stem from its technical or functional characteristics, including diagnostic characteristics, to achieve its intended purpose as claimed by the manufacturer, thereby leading to a clinical benefit for patients, when used as intended by the manufacturer (MDCG 2020-1).
Clinical Safety	Freedom from unacceptable clinical risks, when using the device per the manufacturer's Instructions for Use (MEDDEV 2.7/1).According to MDR, Article 62 (1), the clinical investigation shall be designed with the purpose of verifying the clinical safety of the device and to determine any undesirable side-effects, under normal conditions of use of the device, and assess whether they constitute acceptable risks when weighed against the benefits to be achieved by the device (MDR).
Intended Purpose	The use for which a device is intended according to the data supplied by the manufacturer on the label, in the instructions for use or in promotional or sales materials or statements and as specified by the manufacturer in the clinical evaluation (MDR).
Post-Market Clinical Follow-Up (PMCF) Plan	A PMCF plan shall specify the methods and procedures set up by the manufacturer, to proactively collect and evaluate clinical data from the use in or on humans of a CE marked medical device, placed on the market or put into service within its intended purpose, as referred to in the relevant conformity assessment procedure.The aim of the PMCF plan is:confirming the safety (The confirmation of the safety includes the acceptability of identified risks and particularly residual risks) and performance, including the clinical benefit if applicable, of the device throughout its expected lifetime;identifying previously unknown side-effects and monitor the identified side-effects and contraindications.identifying and analyzing emergent risks on the basis of factual evidence;ensuring the continued acceptability of the benefit-risk ratio, referred to in Section 1 and 9 of Annex I in the MDR.identifying possible systematic misuse or off-label use of the device, with a view to verifying that the intended purpose is correct.
PMCF Study	A study carried out following marketing authorization intended to answer specific questions (uncertainties) relating to safety, clinical performance and/or effectiveness of a device when used in accordance with its labelling (IMDRF MDCE WG/N65FINAL:2021).
Post-Market Surveillance (PMS)	All activities carried out by manufacturers in cooperation with other economic operators to institute and keep up to date a systematic procedure to proactively collect and review experience gained from devices they place on the market, make available on the market or put into service for the purpose of identifying any need to immediately apply any necessary corrective or preventive actions (MDR).
Risk	Combination of the probability of occurrence of harm and the severity of that harm (MDR).
Risk Management	Systematic application of management policies, procedures and practices to the tasks of analyzing, evaluating, controlling and monitoring risk. Risk assessments should document intended as well as reasonably foreseeable misuse (ISO 14971).
State of the Art	Developed stage of current technical capability and/or accepted clinical practice in regard to products, processes and patient management, based on the relevant consolidated findings of science, technology and experience.Note: The STATE-OF-THE-ART embodies what is currently and generally accepted as good practice in technology and medicine. The state-of-the-art does not necessarily imply the most technologically advanced solution. The STATE-OF-THE-ART described here issometimes referred to as the “generally acknowledged STATE-OF-THE-ART”
Technical Performance	Capability of a MDSW to accurately and reliably generate the intended technical/analytical output from the input data (MDCG 2020-1).
Valid Clinical Association	Means the association of an MDSW output with a clinical condition or physiological state (MDCG 2020-1).

Responsibilities

The clinical evaluation should be conducted by a suitably qualified individual or a team.

Manufacturer

The manufacturer should consider the following aspects:

• The manufacturer defines requirements for the evaluators that are in line with the nature of the device under evaluation and its clinical performance and risks.
• The manufacturer should be able to justify the choice of the evaluators through reference to their qualifications and documented experience and to present a declaration of interest for each evaluator.

Person responsible for clinical evaluation

As a general principle this person should possess knowledge of the following:

• research methodology (including clinical investigation design and biostatistics)
• information management (scientific background)
• experience with relevant databases
• regulatory requirements
• medical writing
• Knowledge of the device

The evaluators should meet at least one the following training and experience requirements in the relevant field:

• a degree from higher education in the respective field and five years of documented professional experience
• ten years of documented professional experience (if he/she does not have the degree mentioned above).

Clinical Affairs

Clinical Affairs is responsible for:

• Reviewing scientific literature
• Development of post-market clinical follow-up plans
• Development and/or application of methods to process and assess collected data
• Review of relevant specialist or technical literature
• Databases and/or registers
• Develop suitable indicators and threshold values that shall be used to continuously assess the benefit-risk analysis.

Regulatory Affairs & Quality Assurance Responsible

The quality department is responsible for the following:

• Managing post-market surveillance system
• Processing customer complaints
• Generating complaint trend data and analysis, complaint investigations, and evaluation of returned device(s).
• Analysis of any failures represents potential vigilance events, recall, or other remedial action.
• Maintaining technical documentation and ensuring products meet applicable standards and regulations (this role is named as Management representative in QMS).
• Review of post-market surveillance plans
• Review of post-market surveillance data and trending
• Review and approve risk analysis, reports, technical documentation
• Review and release proposed changes.

Identification of relevant product requirements

In view of the willing to demonstrate the scientific validity of the exposed data, it is essential to elaborate a clear and methodological plan for the identification, retrieval, appraisal and weighting of clinical data. The endpoints must be consistent with currently accepted scientific standards and must be justified according to the State of the art (SOTA).

Taking into account the regulatory status of the product under the scope of the clinical evaluation, the organization considers the applicable General Safety and Performance Requirements (GSPR) by demonstrating their compliance with the product by using clinical data providing sufficient clinical evidence. The level of clinical evidence will be appropriate considering the risk class, intended use and characteristics of the product under the scope.

According to MDCG 2020-1 guideline, there are three key components to be taken into account when compiling clinical evidence:

• Valid clinical association is understood as the extent to which, the MDSW's output (e.g. concept, conclusion, calculations) based on the inputs and algorithms selected, is associated with the targeted physiological state or clinical condition. This association should be well founded or clinically accepted. The valid clinical association of a MDSW should demonstrate that it corresponds to the clinical situation, condition, indication or parameter defined in the intended purpose of the MDSW.
• Validation of the technical performance is the demonstration of the MDSW's ability to accurately, reliably and precisely generate the intended output, from the input data.
• Validation of the clinical performance is the demonstration of a MDSW's ability to yield clinically relevant output in accordance with the intended purpose. The clinical relevance of a MDSW's output is a positive impact
  • On the health of an individual expressed in terms of measurable, patient-relevant clinical outcome(s), including outcome(s) related to diagnosis, prediction of risk, prediction of treatment reponse(s), or
  • Related to its function, such as that of screening, monitoring, diagnosis or aid to diagnosis of patients, or
  • On patient management or public health.

As a minimum clinical data will be used to show that the device is safe, has an acceptable benefit/risk profile, performs as intended (GSPR 1), and has an acceptable side-effect profile (GSPR 8) as outlined in Annex I of the MDR 2017/745 and in the following table.

#	Annex I Requirement
1	Devices shall achieve the performance intended by their manufacturer and shall be designed and manufactured in such a way that, during normal conditions of use, they are suitable for their intended purpose. They shall be safe and effective and shall not compromise the clinical condition or the safety of patients, or the safety and health of users or, where applicable, other persons, provided that any risks which may be associated with their use constitute acceptable risks when weighed against the benefits to the patient and are compatible with a high level of protection of health and safety, taking into account the generally acknowledged state of the art.
2	The requirement in this Annex to reduce risks as far as possible means the reduction of risks as far as possible without adversely affecting the benefit-risk ratio.
6	The characteristics and performance of a device shall not be adversely affected to such a degree that the health or safety of the patient or the user and, where applicable, of other persons are compromised during the lifetime of the device, as indicated by the manufacturer, when the device is subjected to the stresses which can occur during normal conditions of use and has been properly maintained in accordance with the manufacturer's instructions.
8	All known and foreseeable risks, and any undesirable side-effects, shall be minimized and be acceptable when weighed against the evaluated benefits to the patient and/or user arising from the achieved performance of the device during normal conditions of use.
17.2	For devices that incorporate software or for software that are devices in themselves, the software shall be developed and manufactured in accordance with the state of the art taking into account the principles of development life cycle, risk management, including information security, verification and validation.

Device description

The description written in this section is detailed enough to allow for a valid evaluation of the state of compliance with GSPR, the retrieval of meaningful literature data, and the assessment of equivalence to other devices described in the scientific literature.

The device is a Class IIb device with Rule 11 applied in accordance with Annex VIII chapter III of Regulation (EU) 2017/745 of Council of European Union of 5 April 2017. The previous generation of the device, marketed since 2020 following the acquisition of its Spanish manufacturing license, has undergone continuous evaluation through post-market activities.

Device identification

	Information
Device name	Legit.Health Plus (hereinafter, the device)
Model and type	NA
Version	1.0.0.0
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
Class	Class IIb
Classification rule	Rule 11
Novel product (True/False)	FALSE
Novel related clinical procedure (True/False)	FALSE
SRN	ES-MF-000025345

Manufacturer identification

	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, María Diez, Giulia Foglia
E-mail	office@legit.health
Phone	+34 638127476
Trademark	Legit.Health

Intended use

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.

Quantification of intensity, count and extent of visible clinical signs

The device provides quantifiable data on the intensity, count and extent of clinical signs such as erythema, desquamation, and induration, among others; including, but not limited to:

• erythema,
• desquamation,
• induration,
• crusting,
• xerosis (dryness),
• swelling (oedema),
• oozing,
• excoriation,
• lichenification,
• exudation,
• wound depth,
• wound border,
• undermining,
• hair loss,
• necrotic tissue,
• granulation tissue,
• epithelialization,
• nodule,
• papule
• pustule,
• cyst,
• comedone,
• abscess,
• draining tunnel,
• inflammatory lesion,
• exposed wound, bone and/or adjacent tissues,
• slough or biofilm,
• maceration,
• external material over the lesion,
• hypopigmentation or depigmentation,
• hyperpigmentation,
• scar,
• ictericia

Image-based recognition of visible ICD categories

The device is intended to provide an interpretative distribution representation of possible International Classification of Diseases (ICD) categories that might be represented in the pixels content of the image.

Device 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 medical indication

The device is indicated for use on images of visible skin structure abnormalities to support the assessment of all diseases of the skin incorporating conditions affecting the epidermis, its appendages (hair, hair follicle, sebaceous glands, apocrine sweat gland apparatus, eccrine sweat gland apparatus and nails) and associated mucous membranes (conjunctival, oral and genital), the dermis, the cutaneous vasculature and the subcutaneous tissue (subcutis).

Intended patient population

The device is intended for use on images of skin from patients presenting visible skin structure abnormalities, across all age groups, skin types, and demographics.

Intended user

The medical device is intended for use by healthcare providers to aid in the assessment of skin structures.

User qualification and competencies

In this section we specificy the specific qualifications and competencies needed for users of the device, to properly use the device, provided that they already belong to their professional category. In other words, when describing the qualifications of HCPs, it is assumed that healthcare professionals (HCPs) already have the qualifications and competencies native to their profession.

Healthcare professionals

No official qualifications are needes, but it is advisable if HCPs have some competencies:

• Knowledge on how to take images with smartphones.

IT professionals

IT professionals are responsible for the integration of the medical device into the healthcare organisation's system.

No specific official qualifications are needed, but it is advisable that IT professionals using the device have the following competencies:

• Basic knowledge of FHIR
• Understanding of the output of the device.

Use environment

The device is intended to be used in the setting of healthcare organisations and their IT departments, which commonly are situated inside hospitals or other clinical facilities.

The device is intended to be integrated into the healthcare organisation's system by IT professionals.

Operating principle

The device is computational medical tool leveraging computer vision algorithms to process images of the epidermis, the dermis and its appendages, among other skin structures.

Body structures

The device is intended to use on the epidermis, its appendages (hair, hair follicle, sebaceous glands, apocrine sweat gland apparatus, eccrine sweat gland apparatus and nails) and associated mucous membranes (conjunctival, oral and genital), the dermis, the cutaneous vasculature and the subcutaneous tissue (subcutis).

In fact, the device is intended to use on visible skin structures. As such, it can only quantify clinical signs that are visible, and distribute the probabilities across ICD categories that are visible.

Contraindications and precautions required by the manufacturer

Contraindications

We advise not to use the device if:

• Skin structures located at a distance greater than 1 cm from the eye, beyond the optimal range for examination.
• Skin areas that are obscured from view, situated within skin folds or concealed in other manners, making them inaccessible for camera examination.
• Regions of the skin showcasing scars or fibrosis, indicative of past injuries or trauma.
• Skin structures exhibiting extensive damage, characterized by severe ulcerations or active bleeding.
• Skin structures contaminated with foreign substances, including but not limited to tattoos and creams.
• Skin structures situated at anatomically special sites, such as underneath the nails, requiring special attention.
• Portions of skin that are densely covered with hair, potentially obstructing the view and hindering examination.

--

• Skin structures that are not accessible by a camera, such as being located in a skin fold or is otherwise covered.
• Skin structures that contain a scar or fibrosis consistent with previous trauma.
• Skin structures where the skin is very damaged (i.e., very ulcerated or bleeding lesions).
• Skin structures greater than 1 cm away from the eye.
• Skin structures that contain foreign matter (i.e., tattoo, cream).
• Skin structures located on special anatomic sites (i.e., under the nail).
• Skin structures surrounded or covered by a significant amount of hair.

Precautions

After analysing the risks associated to the use of the device, we have identified some residual risks.

The following table summarizes the residual risks and the recomended course of action for each of them:

#	Situation	Recommended course of action
5	Incorrect clinical information: the care provider receives into their system data that is erroneous	The device must always be used under the supervision HCP, who should confirm or validate the output of the device considering the medical history of the patient, and other possible sympthoms they could be suffering, especially those that are not visible or have not been supplied to the device
6	Incorrect diagnosis or follow up: the medical device outputs a wrong result to the HCP	The device must always be used under the supervision HCP, who should confirm or validate the output of the device considering the medical history of the patient, and other possible sympthoms they could be suffering, especially those that are not visible or have not been supplied to the device. Also, we encourage you to review the metadata returned by the device about the output, such as explainability media and other metrics.
9	Image artefacts/resolution: the medical device receives an input that does not have sufficient quality in a way that affects its performance	The Instructions for Use contain extensive indication on how to take pictures in a section called 'How to take pictures'. We also offer training to the users to improve the imaging process so that it is optimal for the device's operation; feel free to request such training to your closest sales representative. Also, we encourage you to pay attention to the information regarding image quality that the device outputs alognside the clinical information.
11	Data transmission failure from care provider's system: the care provider's system cannot connect to the device to send data	The Instructions for Use contain extensive indication on how to integrate the device into the care provider's system in a section called 'Installation manual'.
12	Data input failure: the medical device cannot receive data from care providers	The Instructions for Use contain extensive indication on how to integrate the device into the care provider's system in a section called 'Installation manual'.
13	Data accessibility failure: the care provider cannot receive data from the medical device	The Instructions for Use contain extensive indication on how to integrate the device into the care provider's system in a section called 'Installation manual'.
14	Data transmission failure: the medical device cannot send data to care providers	The Instructions for Use contain extensive indication on how to integrate the device into the care provider's system in a section called 'Installation manual'.
30	Inadequate lighting conditions during image capture: The medical device receives an input that does not have sufficient quality	This is similar to risk ID 9, but with a very simple solution: use the flash. If you can't use the flash and still the image is dark, move to a different environment with better lightning. Also, we encourage you to pay attention to the information regarding image quality that the device outputs alognside the clinical information.

Warnings

In case of observing an incorrect operation of the device, notify us as soon as possible. You can use the email support@legit.health. We, as manufacturers, will proceed accordingly. Any serious incident should be reported to us, as well as to the national competent authority of the country.

Undesirable effects

Any undesirable side-effect should constitute an acceptable risk when weighed against the performances intended.

It is not known or foreseen any undesirable side-effects specifically related to the use of the software.

Intended clinical benefits

The device provides clinical benefits by enhancing the precision and efficiency of dermatological assessments through advanced image analysis of visible skin structures. By quantifying the intensity, count, and extent of clinical signs, it offers detailed and consistent data, which aids healthcare providers in evaluating a wide range of skin conditions across the epidermis, appendages, associated mucous membranes, dermis, cutaneous vasculature, and subcutis. Additionally, it interprets and maps possible ICD classifications, streamlining clinical workflows and supporting standardized assessments for more accurate, data-driven patient care.

Device classification

The device is classified as Class IIb device according to Rule 11 of Annex VIII of MDR 2017/745.

Software intended to provide information which is used to take decisions with diagnosis or therapeutic purposes is classified as class IIa, except if such decisions have an impact that may cause:

• death or an irreversible deterioration of a person's state of health, in which case it is in class III; or
• a serious deterioration of a person's state of health or a surgical intervention, in which case it is classified as class IIb.

Software intended to monitor physiological processes is classified as class IIa, except if it is intended for monitoring of vital physiological parameters, where the nature of variations of those parameters is such that it_could result in immediate danger to the patient, in which case it is classified as class IIb. All other software is classified as class I.

The software in question is classified as Class IIb for its application in melanoma detection based on its intended use and the potential impact on patient health. This significant potential for patient harm from a misdiagnosis justifies classifying the software as Class IIb.

Product category

Software-only medical device.

Device variants and packaging

No variants.

Previous version of the device

The predecessor of the current device is named Legit.Health (hereinafter, "the legacy device"). This earlier version was designed to provide a standalone interface as well as an API, allowing users to engage with it independently of their existing Electronic Health Records. However, this design direction was later recognized as suboptimal, as most organizations expressed a preference for integrating the device's functionalities directly into their existing systems.

In other words: the new generation differs from the previous device in that it's meant to integrate into organisation's softwares. It is used server-to-server, by computer programs. This means that the new device is simpler and contains less elements. This design allows us to focus on other issues, such as interoperability and documentation. And it allows us to invest our development efforts into the scalable architecture of the device, the structure of the input and the output, and helping customers during the integration process.

The legacy device has been commercialized since 2020 (after obtaining the manufacturing license in Spain) and was certified under the Medical Devices Directive (MDD).

Since that time, we've partnered with 21 diverse customers. The customers span from goverment-run care providers to for-profit care providers. Over this period, more than 4,500 diagnostic reports have been crafted by more than 500 professionals. They've utilized our product to help over a thousand patients.

Components

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.

Principles of operation

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.

Mode of action

One core feature of the device is a deep learning-based image recognition technology for the recognition of ICD categories. In other words: when the device is fed an image or a set of images, it outputs an interpretative distribution representation of possible International Classification of Diseases (ICD) categories that might be represented in the pixels content of the image.

The device makes its prediction entirely based on the visual content of the images, with no additional parameters.

The device has been developed following an architecture called Vision Transformer (ViT). This architecture is inspired in the Transformer architecture, which is extensively used in other areas such as NLP and has brought significant advancements in terms of performance.

Another core feature of the device is to provide a quantifiable data on the intensity, count and extent of clinical signs such as erythema, desquamation, and induration, among others.

To achieve that, the device uses a range of deep learning technologies, combined and developed for that specific use. Here's a list of the technologies used:

• Object detection: used to count clinical signs such as hives, papules or nodules.
• Semantic segmentation: used to determine the extent of clinical signs such as hair loss or erythema.
• Image recognition: used to quantity the intensity of visual clinical signs like erythema, excoriation, dryness, lichenification, oozing, and edema.

Device lifecycle

The device is not yet CE marked and has not been commercialized yet.

Expected lifetime

The expected operational lifetime of the device is established at 5 years, which is subject to regular software updates and the lifecycle of the integrated components and platforms. The lifetime will be increase in equivalent spans as the design and development continues and maintenance and re-design activities are carried out.

This timeline accounts for the expected evolution of the underlying operating systems and tools, the progression of medical device technology, and the necessary update cycles to maintain security and operability.

Risk management

Risk management was performed as part of the development process. The risk assessment was conducted in accordance with the 2017/745 MDR and the international standard ISO 14971:2019 Medical Devices-Application of Risk Management to Medical Devices.

Risk management and clinical evaluation are interlinked at many levels: the clinical evaluation shall consider data from risk management activities related to our device as input data for defining relevant safety parameters. Also, any not acceptable residual risk from the risk analysis must be specifically assessed in the CER to provide supporting evidence about the clinical benefits outweighing the residual risk. Finally, clinical evaluation and its periodic reviews and updates is a relevant source of input data for the maintenance and corresponding review and update of the product's risk analysis.

Standard	Title
EN ISO 13485:2016/A11:2021	Medical devices. Quality management systems. Requirements for regulatory purposes
EN ISO 15223-1:2021	Medical devices. Symbols to be used with medical device labels, labeling and information to be supplied. Part 1: General requirements.
EN ISO 20417: 2021	Medical devices - Information to be supplied by the manufacturer.
EN ISO 14971:2019	Medical devices. Application of risk management to medical devices.
EN ISO 20417:2021	Medical devices - Information to be supplied by the manufacturer
UNE-EN 62304:2007/A1:2016 (EN 62304:2006/A1:2015)	Medical device software - Software life-cycle processes
UNE-EN 62366-1:2015/A1:2020 (EN 62366-1:2015/A1:2020)	Medical devices - Part 1: Application of usability engineering to medical devices

Generic hazards applicable to the device

According to the risk management, the following generic hazards are considered relevant to address the safety of the device:

• Incompatibility with other devices
• Inadequate labelling
• Inadequate instructions for use
• Inadequate specification of accessories
• Complicated instructions for use
• Instructions for use not available or separate from the product
• Use by untrained personnel
• Reasonably foreseeable misuse
• Inadequate warning of adverse effects
• Incorrect diagnosis
• Wrong data transfer
• Misinterpretation of results
• Incompatibility with consumables, accessories or other devices
• Inadequate to the planned functions
• Inadequate or absent maintenance specifications, including performance checks
• Inadequate maintenance
• Absence of limitation of product lifetime

The clinical evaluation for the product shall address all these points through assessing the relevant clinical evidence, determining if there is enough evidence to support a good safety profile.

Risk mitigation measures

We believe that the special controls, when combined with the general controls, will be sufficient to provide reasonable assurance of safety and efficacy for the device. The information below summarizes the potential risks identified for the subject device with respect to its intended purpose.

The risk assessment of the hazards of the device and the design, process and application of the product has been performed by us. The complete table of risks and risk control measures can be found in the R-TF-013-002 Risk Management Record.

All residual risks have been reduced as far as possible. All individual and residual risks were determined to be acceptable according to the risk acceptability criteria described in the R-TF-013-003 Risk Management Report.

All safety findings identified during the clinical evaluation will be investigated if they are captured in the risk assessment.

ID	Hazard	Mitigation measures
5	Incorrect clinical information	Information about device outputs and intended user (HCP) are detailed in the IFU. The medical device returns metadata about the output that helps supervising it, such as explainability media and other metrics.
6	Incorrect diagnosis or follow up	Information about device outputs and intended user (HCP) are detailed in the IFU. The medical device returns metadata about the output that helps supervising it, such as explainability media and other metrics The device returns an interpretative distribution representation of possible ICD categories, not just one single condition.
9	Image artefacts/resolution	A requirement of the device defines the creation of a processor whose purpose is to ensure that the image have enough quality. In other words, an algorithm, similar to the ones used to classify diseases, is used to check the validity of the image and provides an image quality score. The device returns meaningful messages to the users about the quality score of the images, this allows care providers to re-take a photo. We also offer training to the users to optimize the imaging process so that it is optimal for the device's operation.
11	Data transmission failure from healthcare provider's system	State-of-the-art techniques of security and software availability. The device returns meaningful messages about the error to help troubleshooting.
12	Data input failure	State-of-the-art techniques of security and software availability. The device returns meaningful messages about the error to help troubleshooting.
13	Data accessibility failure	State-of-the-art techniques of security and software availability. The device returns meaningful messages about the error to help troubleshooting.
14	Data transmission failure	State-of-the-art techniques of security and software availability. The device returns meaningful messages about the error to help troubleshooting. The endpoints of the device follow HL7's FHIR interoperability standard.
30	Inadequate lighting conditions during image capture	A requirement of the device defines the creation of a processor whose purpose is to ensure that the image have enough quality. In other words, an algorithm, similar to the ones used to classify diseases, is used to check the validity of the image and provides an image quality score. The device returns meaningful messages to the users about the quality score of the images, this allows care providers to re-take a photo. We also offer training to the users to optimize the imaging process so that it is optimal for the device's operation.

Acceptability of the benefit-risk ratio

The benefit/risk ratio for the device shall be deemed acceptable as long as:

1. All the applicable safety-related GSPRs are met based on a critical assessment of the relevant safety parameters defined in section 9.6 providing a good safety profile for the device;
2. All the performance-related GSPRs are met, based on the outcome parameters defined in 9.6 and as assessed through a critical revision of relevant clinical evidence.
3. Any residual risks with clinical impact as identified in the risk assessment of the device are adequately addressed.

The current Clinical Evaluation aims to confirm the benefits of the device and ensure its safety through the review of the Post-market Surveillance Plan and Risk Management documentation.

State of the art

Sources

The current state of the art in the corresponding medical field, the following aspects and information will be checked:

• Applicable standards and guidance documents
• Information relating to the medical field in which the device is used
• Benchmark devices and other devices available on the market

The CER shall contain a thorough state-of-the-art review to analyze and assess the benefit-risk profile of currently available methods for the various indications and for the device's intended purpose. An objective, comprehensive literature review will be performed to identify, select, and collect the relevant literature to determine whether the device offers a safe and effective performance for the intended purpose. The review will be focused on relevant data to the device under evaluation, relevant data to the intended purpose of similar devices, and claimed performance and safety data (including incidents and contraindications).

Identification of relevant medical conditions / medical fields concerned

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

• quantifiable data on the intensity, count and extent of clinical signs such as erythema, desquamation, and induration, among others.
• interpretative distribution representation of possible International Classification of Diseases (ICD) categories that might be represented in the pixels content of the image.

Therefore, the medical condition identified are all skin diseases listed and described in the ICD-11 (code 14).

Applicable standards and guidelines

The clinical evaluation of the device will be performed according to the relevant legal framework and following the applicable and established standards described in the section above.

A literature search of guidelines will be performed in Google and Pubmed searching the following terms: ICD-11 disease of skin guideline in order to find medical guidelines related with ICD-11 Classification of Dermatological Diseases.

Systematic literature search for SOTA description

A systematic literature search will be conducted to complete the state of the art of the device, using the PICO method.

Data search question using the PICO method

As part of the literature search strategy, the PICO method was used to subsequently establish the algorithms. The PICO method is a format used for the development of appropriate clinical questions, consisting of answering the following questions to establish the search keywords:

• P (problem/patient/population): Who are the users, patients or affected population?
• I (intervention/indicator): What is the management strategy for the identified population?
• C (comparator): Is there a control group and/or alternative treatment option to be considered?
• O (outcome of interest): What are the relevant patient outcomes of the intervention studied?

The choice of keywords for the implementation of the PICO methodology is based on the intended purpose and medical condition of the device.

• P (problem/patient/population): Patients with visible skin structure abnormalities; skin diseases listed in ICD-11 code 14; across all age groups, skin types, and demographics.
• I (intervention/indicator): Use of a computational software-only medical device that processes images of skin structures to provide clinical data for aiding practitioners in skin assessments.
• C (comparator): Other smartphone applications. SkinVision and Molescope. Traditional methods of clinical skin examination without software assistance; non-software-based skin assessments by healthcare professionals.
• O (outcome of interest): Improved efficiency and accuracy in clinical decision-making for skin disease assessment; support in diagnosis through interpretative data and quantification.

Generation of keywords and algorithm for bibliographic search

According to the description of the words described using the PICO methodology, the following search terms or keywords have been defined.

	Description	Keywords	Algorithm
P (problem /patient /population)	Patients with visible skin structure abnormalities; skin diseases listed in ICD-11 code 14; across all age groups, skin types, and demographics.	"skin cancer", "epidermis", "chronic skin conditions", "skin conditions", "inflammatory skin diseases", "malignant skin lesions", "melanoma", "acne", "psoriasis", "dermatofibroma", "dermatosis"	("skin cancer" OR "epidermis" OR "chronic skin conditions" OR "skin conditions" OR "inflammatory skin diseases" OR "malignant skin lesions" OR "melanoma" OR "acne" OR "psoriasis" OR "dermatofibroma" OR "dermatosis")
I (intervention/ indicator)	Use of a computational software-only medical device that processes images of skin structures to provide clinical data for aiding practitioners in skin assessments.	"software", "digital imag*", "smartphone", "web application"	("software" OR "digital imag*" OR "smartphone" OR "web application")
C (comparator)	Other smartphone applications. SkinVision and Molescope. Traditional methods of clinical skin examination without software assistance; non-software-based skin assessments by healthcare professionals.	"SkinVision", "artificial intelligence", "machine learning", "deep learning", "computer vision", "deep neural networks", "metaoptima", "clinical exam", "visual inspection", "manual assessment"	("SkinVision" OR "artificial intelligence" OR "machine learning" OR "deep learning" OR "computer vision" OR "deep neural networks" OR "metaoptima" OR "clinical exam" OR "visual inspection" OR "manual assessment")
O (outcome)	Improved efficiency and accuracy in clinical decision-making for skin disease assessment; support in diagnosis through interpretative data and quantification.	"estimation", "classification", "followup", "diagnos*", "quantif*"	("estimation" OR "classification" OR "followup" OR "diagnos*" OR "quantif*")

By combining the four elements of the PICO method, the final search algorithm was obtained:

("skin cancer" OR "epidermis" OR "chronic skin conditions" OR "skin conditions" OR "inflammatory skin diseases" OR "malignant skin lesions" OR "melanoma" OR "acne" OR "psoriasis" OR "dermatofibroma" OR "dermatosis") AND ("software" OR "digital imag\*" OR "smartphone" OR "web application") AND ("SkinVision" OR "artificial intelligence" OR "machine learning" OR "deep learning" OR "computer vision" OR "deep neural networks" OR "metaoptima" OR "clinical exam" OR "visual inspection" OR "manual assessment") AND ("estimation" OR "classification" OR "followup" OR "diagnos\*" OR "quantif\*")

Bibliographic search strategy for determining the state of the art

To perform the search, we use PubMed as the source of scientific information. PubMed is a search engine with free access to the MEDLINE database of references and abstracts on life sciences and biomedical topics, which is considered the most complete and orderly. The US National Library of Medicine (NLM) at the National Institutes of Health maintains the database as part of the information retrieval system. MEDLINE has about 5200 journals published in the United States and in more than 70 countries around the world from 1966 to the present. Use PMID (PubMed Identifier) as the unique identifier assigned to each PubMed record.

The search filters to be applied in PubMed are as follows:

• Text availability: "abstract", "full-text".
• Species: humans
• Publication date: 10 years (23-10-2014 to 23-10-2024)
• Article Language: English
• The full search algorithm is:

("skin cancer" OR "epidermis" OR "chronic skin conditions" OR "skin conditions" OR "inflammatory skin diseases" OR "malignant skin lesions" OR "melanoma" OR "acne" OR "psoriasis" OR "dermatofibroma" OR "dermatosis") AND ("software" OR "digital imag\*" OR "smartphone" OR "web application") AND ("SkinVision" OR "artificial intelligence" OR "machine learning" OR "deep learning" OR "computer vision" OR "deep neural networks" OR "metaoptima" OR "clinical exam" OR "visual inspection" OR "manual assessment") AND ("estimation" OR "classification" OR "followup" OR "diagnos\*" OR "quantif\*")

Criteria for selection of state-of-the-art articles

After compiling the results obtained from the PubMed database, we checked for duplicates and made an initial selection of articles based on the content of the title and abstract. We consider that one article is duplicated when there is another article within the list of results with identical title, authors, and content.

The articles whose abstract is related to the device under evaluation will be evaluated with the evaluation criteria described in the following table.

#	Evaluation criteria	Article information	Score
1	Device evaluated	Data for device being evaluated (software-only medical devices that leverage computer vision to process images of the epidermis, dermis, and appendages for assisting healthcare practitioners)	3
1	Device evaluated	Data for a similar device (other computational software-only devices that use similar computer vision technology for analyzing skin structures, but may have slight variations (e.g., targeting specific diseases or focusing on non-ICD skin classifications)	2
1	Device evaluated	Data for a different device	1
2	I - Intended purpose	Studies or data focused on devices designed to support healthcare practitioners in the assessment of skin structures, providing quantification of visible clinical signs and potential ICD classification as additional data for clinical decisions, without confirming a diagnosis.	3
2	I - Intended purpose	Data on devices that assist in the assessment of skin abnormalities or similar structures but may not provide the same output (e.g., no ICD classification) or may serve a slightly different purpose (e.g., focusing on diagnosis instead of decision support).	2
2	I - Intended purpose	Studies or data evaluating devices used for unrelated medical purposes, such as those focusing on diagnostic confirmation or processing images for organs other than the skin.	1
3	Results	The measured results reflect the intended purpose of the device and provide valuable data on the safety and effectiveness of the devices.	3
3	Results	The age or conditions of target patient group is not defined.	2
3	Results	The device is not used in the target patient group defined.	1
4	R - Results	The measured results reflect the intended purpose of the device and provide valuable data on the safety and effectiveness of the devices.	3
4	R - Results	The measured results are related to the intended purpose but do not provide data on the safety and efficacy of the devices.	2
4	R - Results	The measured results are not related to the intended purpose.	1
5	Data source type	Guideline, meta-analysis, systematic review, review	3
5	Data source type	Randomized controlled trials	2
5	Data source type	Other studies	1

Final score is obtained as a result of the multiplication of the score of each of the evaluation criteria. Articles with a score higher of 8 will be evaluated in the Clinical Evaluation Report as part of the SOTA of device.

Similar devices

The following medical devices similar to the device have been identified.

Device name	Targeted medical conditions	CE Marking
SkinVision	Skin Cancer	Yes
DermEngine	Dermatology-related conditions	Not Found
Triage	Skin Disorders	Not Found
First Derm	Skin Conditions	Not Found
Cureskin	Skin and Hair Conditions	Not Found
MoleMapper	Melanoma Detection	Not Found
Eczema Tracker	Eczema	Not Found
VisualDx	Various Medical Conditions	Not Found
MoleScope (by Fotofinder)	Mole imaging, other skin conditions like acne, eczema, psoriasis	Yes

A comparative table with the main technical and clinical characteristics extracted from the instructions for use of the device and SkinVision and MoleScope will be included in the Clinical Evaluation Report. Furthermore, a search on incidents and alerts related to those devices will be done.

Safety and performance endpoints

The safety and performance endpoints, considering the current knowledge and state of the art, include:

• Safety Endpoints:
  • Patient Safety: Minimizing risks of misdiagnosis and misinterpretation of imaging data to ensure accurate clinical information for healthcare practitioners.
  • Data Privacy and Security: Implementing state-of-the-art security measures to protect sensitive patient information, ensuring compliance with data protection regulations.
  • Prevention of Over-Reliance on Imaging Data: Encouraging informed decision-making by healthcare practitioners and emphasizing the importance of integrating imaging data with clinical expertise.
  • Variability in Skin Condition Presentations: Accommodating intra- and inter-class variability to ensure accurate assessment of a wide range of skin conditions.
  • Diversity of Dataset: Addressing limitations in dataset diversity to enhance the algorithm's generalizability and applicability across different patient populations.
  • Robust Verification and Validation: Conducting thorough verification and validation processes, including real-world testing, to confirm consistent performance in various clinical environments.
• Performance Endpoints:
  • Diagnostic Accuracy: Evaluate how accurately the device identifies dermatological conditions compared to clinical diagnoses.
  • Clinical Utility: Assess the device's effectiveness in improving patient management and outcomes, such as reducing the need for in-person consultations.
  • User Satisfaction: Measure the satisfaction levels of both healthcare providers and patients regarding the device's usability and effectiveness.
  • Referral Efficiency: Analyze the impact of the device on the rate of unnecessary referrals to dermatology specialists.
  • Workflow Integration: Determine how well the device integrates into existing clinical workflows and its effect on overall efficiency.
  • Sensitivity and Specificity: Assess the device's ability to correctly identify true positive and true negative cases for various skin conditions.

These safety and performance endpoints are critical considerations in assessing the effectiveness and suitability of software like the device to give support to health care providers in the assessment of skin structures, enhancing efficiency and accuracy of care delivery, by providing:

• quantifiable data on the intensity, count and extent of clinical signs such as erythema, desquamation, and induration, among others.
• interpretative distribution representation of possible International Classification of Diseases (ICD) categories that might be represented in the pixels content of the image.

They help ensure that the product meets regulatory standards, clinical requirements, and patient needs while minimizing risks and maximizing therapeutic benefits.

Valid clinical association

Demonstration of valid clinical association has the objective to demonstrate the association of MDSW output (intensity, count and extent of visible clinical signs) and the organs affected as well as the association of the visible clinical signs measured and the interpretative distribution representation of possible ICD categories. For that purpose, different searches will be performed, which are described below. The demonstration of valid clinical association should cover:

• Has the quantifiable data on the intensity, count and extent of clinical signs such as erythema, desquamation, and induration, among others been validated against the International Classification of Diseases (ICD) categories?
• Are the visible clinical signs detected scientifically validated as appropiate for the interpretative distribution representation of possible International Classification of Diseases (ICD) categories that might be represented in the pixels content of the image?

The answers to these questions will be addressed as part of the CER.

Valid clinical association of the visible skin structure abnormalities

The device provides quantifiable data on the intensity, count and extent of clinical signs such as erythema, desquamation, and induration, among others.

In order to establish the correlation between the MDSW output (intensity, count and extent of visible clinical signs) and the organs affected, a systematic literature search will be performed:

• Period covered by the search: 2014-10-14 to 2024-10-14
• Sources used: PubMed.gov. PubMed is a free resource supporting the search and retrieval of biomedical and life sciences literature. The database citations (more than 34 million citations and abstracts of biomedical literature) primarily stem from the biomedicine and health fields, and related disciplines such as life sciences, behavioral sciences, chemical sciences, and bioengineering.
• Search algorithms: ("skin structure" OR "epidermis" OR "dermis" OR "hair" OR "hair follicle" OR "sebaceous gland*" OR "nails") AND ("visible clinical sign*" OR "skin condition" OR "erythema" OR "desquamation" OR "induration" OR "dryness" OR "swelling") AND ("intensity" OR "count" OR "quantif*")
• Language: English
• Filters: Full text, abstract, human
• Screening: Articles not related with the device under evaluation or medical condition will be discarded.If full text is not available, articles will be discarded also.
• Appraisal:
  • Correlation between MDSW output and condition
    • Article does not describe the correlation between the clinical visible signs and the measured skin structures (Score: 1)
    • Article has a limited description of the relation between the condition and MDSW output (Score: 2)
    • Article describes the correlation between the condition and the MDSW output and it is well explained and developed (Score: 3)
  • Methodology
    • Methods not described or described very poorly (Score: 1)
    • Limited description of the methodology applied (Score: 2)
    • Methods are well described (Score: 3)
  • Medical condition
    • Referred to other conditions (non-visible skin conditions) (Score: 1)
    • Different type of clinical conditions observed in visible skin (Score: 2)
    • Type of visible clinical skin conditions under evaluation (Score: 3)

Valid clinical association of the International Classification of Diseases (ICD) categories

the device provide interpretative distribution representation of possible International Classification of Diseases (ICD) categories that might be represented in the pixels content of the image. Several systematic literature searches will be performed in order to demonstrate the valid clinical association between the visible clinical signs measured and the most relevant and common ICD categories.

• Sources used: PubMed.gov. PubMed is a free resource supporting the search and retrieval of biomedical and life sciences literature. The database citations (more than 34 million citations and abstracts of biomedical literature) primarily stem from the biomedicine and health fields, and related disciplines such as life sciences, behavioral sciences, chemical sciences, and bioengineering.
• Language: English
• Filters: Full text, abstract, human
• Screening: Those article whose full text is not available or do not show significant correlation between the visible clinical signs and the diseases described, will be discarded.
• Appraisal:
  • Correlation between MDSW output and condition
    • Article does not describe the correlation between the clinical visible signs and the measured skin structures (Score: 1)
    • Article has a limited description of the relation between the condition and MDSW output (Score: 2)
    • Article describes the correlation between the condition and the MDSW output and it is well explained and developed (Score: 3)
  • Methodology
    • Methods not described or described very poorly (Score: 1)
    • Limited description of the methodology applied (Score: 2)
    • Methods are well described (Score: 3)
  • Medical condition
    • Referred to other conditions (non-visible skin conditions) (Score: 1)
    • Different type of diseases observed in visible skin (Score: 2)
    • Type of diseases under evaluation (Score: 3)

Technical performance

The technical performance aims to demonstrate that the MDSW's ability to accurately, reliably and precisely generate the intended output (assessment of all diseases of the skin incorporating conditions affecting the epidermis, its appendages (hair, hair follicle, sebaceous glands, apocrine sweat gland apparatus, eccrine sweat gland apparatus and nails) and associated mucous membranes (conjunctival, oral and genital), the dermis, the cutaneous vasculature and the subcutaneous tissue (subcutis)), from the input data (images of visible skin structure abnormalities).

Data generated and held by the manufacturer - Pre-clinical and Bench testing

The clinical evaluation will take into consideration the relevant regulatory requirements for the product under consideration. As a result, the pre-clinical, benchtop, and historical performance data are listed below.

The technical performance of the device will be reviewed and assessed in the Clinical Evaluation Report, with a focus on the following points:

• Design and Function Verification
  • Defined in document R-TF-012-006 Lifecycle Plan and Report.
  • Design Verification and Validation confirm the device's compliance with Design Requirements under real and simulated conditions.
• Machine Learning Model Validation and Testing
  • Documented in R-TF-012-009.
  • Covers three model types:
    • Image Recognition: Accuracy, sensitivity, specificity, AUC, and GradCAM interpretability.
    • Object Detection: Precision, recall, mAP, IoU, MAE.
    • Semantic Segmentation: IoU, F1 score, AUC.
  • Utilizes supervised learning, data splitting, augmentation, and consistent metrics to validate model robustness.
• Usability Engineering
  • Documented in R-TF-012-015 Summative evaluation report.
  • Ensures easy integration and use for healthcare providers and IT professionals via API in EHR systems, with secure REST API and FHIR compliance.
• Cybersecurity Framework
  • Documented in SP-012-002 Cybersecurity and Transparency Requirements.
  • Follows standards such as MDCG 2019-16 and IMDRF guidelines.
  • Manages security risks through encryption, access controls, and continuous threat assessment.
  • Security by Design principles applied throughout development, with strong focus on data protection, integrity, and user transparency.

This structured technical performance overview will be incorporated and thoroughly evaluated in the Clinical Evaluation Report to demonstrate compliance and efficacy in supporting clinical workflows securely and effectively

Clinical performance

The aim of the clinical performance is to demonstrate its capacity to generate clinically relevant outputs aligned with its intended purpose of supporting dermatological assessments through image analysis. This involves validating that the software provides outputs that positively impact individual health by contributing to measurable, patient-relevant outcomes. Specifically, the device aims to aid healthcare professionals in diagnosing and monitoring skin abnormalities, improving diagnostic accuracy and patient management. By furnishing reliable and actionable insights that facilitate risk prediction, screening, and clinical evaluations, the device seeks to play a valuable role in enhancing patient care and public health within professional healthcare settings.

Specific performance and safety questions

The clinical performance evaluation for the device aims to answer the following questions:

1. Does the device effectively assist healthcare professionals in evaluating dermatological conditions by analyzing images of the skin structures, providing data that supports clinical decision-making?
2. Does the device consistently support the monitoring of skin conditions over time, enabling accurate longitudinal assessment for healthcare providers?
3. Does the device maintain the quality and accuracy of its image analysis and data processing to ensure reliable support for clinical evaluations?
4. Does the device exhibit an acceptable safety profile, with a risk level comparable to or lower than other AI-based dermatological assessment tools commonly used in clinical practice?
5. Does the device demonstrate equivalent or superior performance compared to other dermatological analysis tools in providing reliable clinical data to support patient evaluations?

These clinical questions aim to assess the effectiveness, safety, and performance of the device in clinics, hospitals, or specialized dermatology centers, where healthcare practitioners can leverage the device's image analysis to support evaluations of skin conditions, ensuring it meets the needs of healthcare professionals and patients while maintaining regulatory compliance and safety standards. The answers will be included in the Clinical Evaluation Report.

Type of clinical performance evaluation

The clinical performance is based on the available post-market clinical investigations pertinent to the device under evaluation and the scientific literature.

This evaluation includes the different data sources described in the section below.

Identification of relevant data

Data relevant to the clinical evaluation is listed below.

Data Source

• Data from State of the art (SOTA)
• Data generated and held by the manufacturer
• Risk Management and Risk Analysis
• Data from Post-Market Surveillance
• Data from Post-market clinical investigations
• Data from vigilance reporting
• Data retrieved from the literature

Data generated and held by the manufacturer

Risk management and risk analysis

We have established, implemented, documented, and maintained a risk management system in accordance with Annex I of MDR. This involves the establishment of a risk management plan for the device, allowing traceability for every hazard, identification and evaluation of risks, accomplishment and verification of the risk control measures, and verification that the residual risks are accepted. Risk management activities have been performed in accordance with ISO 14971:2019.

Data from Post-Market Surveillance (PMS)

The device has not yet been commercialized, but the previous generation of the device has been marketed since 2020. It has undergone a post-market surveillance since then. The R-TF-015-003 Clinical Evaluation Report includes a description of the main conclusions extracted from the PSUR and PMCF report created in 2023, regarding sales data, serious incidents and Field Safety Corrective Actions, trend reports, Corrective and Preventive Actions as well as non-conformities and main conclusions from PMCF activities performed.

Data from post-market clinical investigations

The post-market clinical investigations for the device encompass multiple studies designed to validate its performance in dermatological diagnosis and monitoring. These investigations will be reviewed in detail in the Clinical Evaluation Report.

1. Clinical validation study of a CAD system with artificial intelligence algorithms for early noninvasive detection of in vivo cutaneous melanoma (LEGIT_MC_EVCDAO_2019)
2. 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 (LEGIT_COVIDX_EVCDAO_2022)
3. Optimization of clinical flow in patients with dermatological conditions using Artificial Intelligence (LEGIT.HEALTH_IDEI_2023)
4. Non-Invasive Prospective Pilot in a Live Environment for the improvement of diagnosis of skin pathologies in primary care and dermatology (LEGIT.HEALTH_SAN_2024)
5. Non-Invasive Prospective Pilot in a Live Environment for the improvement of diagnosis of Generalized Pustular Psoriasis (LEGIT.HEALTH_BI_2024)
6. Non-Invasive Prospective Pilot in a Live Environment for the improvement of the diagnosis of skin pathologies in primary care (LEGIT.HEALTH_PH_2024_NIPPLE)
7. Pilot study for the clinical validation of an artificial intelligence algorithm to optimize the appropriateness of dermatology referrals (Ongoing Study) (LEGIT.HEALTH_DAO_Derivación_O_2022)

These studies collectively support the device's clinical utility, accuracy, and potential to optimize dermatological care.

Data from vigilance databases

Medical device alerts, recommendations and recalls regarding the similar devices (SkinVision and MoleScope) to the device will be searched in the following external publicly available databases. Keywords used will be related to devices with similar technology and intended purpose:

• FDA (Food and Drug Administration):
  • Provides Total Product Lifecycle data, including enforcement reports, warning letters, MAUDE database reports, CDRH inspections database, FDA recall database, and TPLC database.
• Swissmedic:
  • Swiss agency for the authorization and supervision of therapeutic products, offering a recall list of medical devices within the scope of market surveillance.
• MHRA (Medicines and Healthcare Products Regulatory Agency):
  • An executive agency of the Department of Health in Great Britain, responsible for ensuring the effectiveness and safety of medicines and medical devices.
• AEMPS Vigilancia de productos sanitarios:
  • A state agency in Spain attached to the Ministry of Health, responsible for guaranteeing the quality, safety, efficacy, and accurate information of medicines and health products.

Sources of literature. Data review

Systematic literature review

The goal of this review is to perform a complete and systematic review of all the literature associated with the intended purpose of the device under evaluation, its risks, and its similar devices. The most common method to perform a systematic literature search is to use the Patients, Interventions, Comparisons, and Outcomes (PICO) model.

The criteria for the selection of articles and their analysis will be:

• Scientific papers with original data and completed data, full article available in English.
• Papers with enough relevant information to the device under evaluation or its similar devices which address the Patients, Intervention, and Outcome of interest.
• Those items with the greatest impact will weigh more.
• Articles by authors of relevant prestige will have greater weight.
• Articles that provide positive information and those that are not in line with the use of the device, its results, or its safety will be considered.

Clinical databases are checked to get information on the processes (manually performed) associated with the device's intended purpose.

For the device under evaluation, the reference clinical database used by the manufacturer is PubMed.

Strategy for systematic literature review with PICO method

The literature review for the evaluation of safety and performance of the device in the clinical environment will be performed according to PICO method, described before.

Keywords defined for the search are described in the following table.

	Description	Keywords	Algorithm
P (problem /patient /population)	Skin cancer, epidermis, chronic skin conditions, skin conditions, inflammatory skin diseases, malignant skin lesions, melanoma, acne, psoriasis, dermatofibroma, dermatosis	“Skin cancer”, “epidermis”, “chronic skin conditions”, “skin conditions”, “inflammatory skin diseases”, “malignant skin lesions”, “melanoma”, “acne”, “psoriasis”, “dermatofibroma”, “dermatosis”	("skin cancer" OR "epidermis" OR "chronic skin conditions" OR "skin conditions" OR "inflammatory skin diseases" OR "malignant skin lesions" OR "melanoma" OR "acne" OR "psoriasis" OR "dermatofibroma" OR "dermatosis")
I (intervention/ indicator)	Legit.Health, software, digital imagi*	“Legit.Health”, “software”, “digital imagi*”	("Legit.Health" OR "software" OR "digital imag*")
C (comparator)	SkinVision, artificial intelligence, machine learning, computer vision, smartphone	“SkinVision”, “artificial intelligence”, “machine learning”, “computer vision”, “smartphone”	("Legit.Health" OR "software" OR "digital imag*")
O (outcome)	Performanc*, safe*, clinical	“Performanc*”, “safe*”, “clinical”	("performanc*" OR "safe*" OR "clinical")

As a result of combining the keywords defined in Table 9, the final algorithm is:

("skin cancer" OR "epidermis" OR "chronic skin conditions" OR "skin conditions" OR "inflammatory skin diseases" OR "malignant skin lesions" OR "melanoma" OR "acne" OR "psoriasis" OR "dermatofibroma" OR "dermatosis") AND ("Legit.Health" OR "software" OR "digital imag\*") AND ("SkinVision" OR "artificial intelligence" OR "machine learning" OR "computer vision" OR "smartphone") AND ("performanc\*" OR "safe\*" OR "clinical")

The filters to be applied for the search are the following:

• Pubmed
  • Text availability: Abstract, Full text
  • Language: English
  • Species: Human

The search will be performed for the last 10 years (2024-10-29 to 2024-10-29).

Screening of title and abstract's content

A first assessment will be made of the content of the title and abstract of the articles found. Articles not related to the intended use of the medical device under evaluation will be discarded.

Appraisal of article's content

The articles selected during the first screening phase are evaluated in their entirety and scored according to the following criteria:

Suitability criteria	Classification / Score
Article methodology	Methods not described or described very poorly (Score: 1) Limited description on the methodology applied (Score: 2) Methods well described including statistical analysis performed and/or other methods applied (Score: 3)
Article type	Case series, case report (Score: 1) Randomized control trials (Score: 2) Systematic review meta-analysis (Score: 3)
Targeted population	The article does not describe the intended population and/or inclusion and exclusion criteria are not clearly defined (Score: 1) The intended population is different to the device's population (Score: 2) Intended population is lay people, as the device's population (Score: 3)
Device under evaluation	Article does not refer to any software for the assessment of skin structures (Score: 1) Article does not refer to the device but refers on similar software devices for the assessment of skin structures (Score: 2) Article refers to the device (Score: 3)
Device safety/risks	No description on any safety-related outcome or risk associated with the device (Score: 1) Limited description on the safety issues identified related with the device as well as risks-associated with the device (Score: 2) Detailed description of safety issues identified related with the device as well as risks-associated with the device (Score: 3)

The final appraisal score is calculated as the result of the sum of the different criteria. Those articles with a score equal of lower to 10 points will be considered as low-quality evidence and will be discarded.

Clinical development plan

According to Article 10(3) of the Medical Devices Regulation 2017/745, manufacturers shall conduct a clinical evaluation in accordance with the requirements set out in Article 61 and Annex XIV, including a Post Market Clinical Follow-up Clinical Investigation.

Annex XIV states that the manufacturer shall specify and justify the level of clinical evidence necessary to demonstrate conformity with the relevant general safety and performance requirements. That level of clinical evidence shall be appropriate in view of the characteristics of the device and its intended purpose. To that end, manufacturers shall plan, conduct, and document a clinical evaluation.

The clinical development strategy for the device is provided in R-TF-015-008 Clinical Development Plan. The clinical investigations planned for the device will be conducted in accordance with the guidance documents MDCG 2024-5 (Guidance on the Investigator's Brochure content), and MDCG 2024-3 (Guidance on content of the Clinical Investigation Plan for clinical investigations of medical devices).

Relevant changes

The CER has been performed in accordance with regulatory requirements of the Medical Devices Regulation 2017/745.

Clinical concerns

Until now, no clinical concerns have been raised.

If any specific clinical concerns have newly emerged, they will be reported as such in the updated revision of this Clinical Evaluation Plan.

Related documents

• Instructions for use (IFU)
• R-TF-013-002 Risk management record
• R-TF-015-008 Clinical Development Plan
• R-TF-015-003 Clinical Evaluation Report
• R-TF-007-001 Post-Market Surveillance Plan
• R-TF-007-002 Post-Market Clinical Follow-Up Plan
• GP-013 Risk management
• GP-007 Post-market Surveillance
• GP-015 Clinical Evaluation
• GP-004 Vigilance system

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