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      • R-001-002 Manufacturer declaration of conformity
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      • R-001-009 Training on procedures of the QMS
      • R-001-009 Training on procedures of the QMS
      • R-001-009 Training on procedures of the QMS
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  • R-001-002 Manufacturer declaration of conformity for Brazil

R-001-002 Manufacturer declaration of conformity for Brazil

This is a draft

This document is a draft version.

AI Labs Group SL, located at Gran Vía 1, BAT Tower, 48001, Bilbao, Bizkaia (Spain) certifies under its responsibility that the manufactured product:

Information
Device nameLegit.Health Plus (hereinafter, the device)
Version1.0.0.0
Basic UDI-DI8437025550LegitCADx6X
Intended purposeThe complete intended purpose can be consulted below, in the section intended use or purpose.
GMDN code65975
EMDN codeZ12040192 (General medicine diagnosis and monitoring instruments - Medical device software)

Complies with the applicable standards:

  • UNE-EN ISO 13485:2018 (EN ISO 13485:2016) Medical devices - Quality management systems - Requirements for regulatory purposes
  • UNE-EN 62304:2007/A1:2016 (EN 62304:2006/A1:2015) Medical device software - Software life-cycle processes
  • UNE-EN ISO 14971:2020 (EN ISO 14971:2019) Medical devices - Application of risk management to medical devices
  • UNE-EN ISO 15223-1:2022 (EN ISO 15223-1:2021) Medical devices - Symbols to be used with information to be supplied by the manufacturer - Part 1: General requirements
  • UNE-EN ISO 20417:2021 (EN ISO 20417:2021) Medical devices - Information to be supplied by the manufacturer
  • UNE-EN 62366-1:2015/A1:2020 (EN 62366-1:2015/A1:2020) Medical devices - Part 1: Application of usability engineering to medical devices
  • UNE-EN ISO 14155:2021 (EN ISO 14155:2020) Clinical investigation of medical devices for human subjects - Good clinical practice

Complies with the provisions of

  • Collegiate board resolution - RDC No. 751, of September 15, 2022
  • Collegiate board resolution - RDC No. 657, of March 24, 2022
  • Collegiate board resolution - RDC No. 546, of August 30, 2021

Classification: Class II (Rule 11, RDC No. 751, of September 15, 2022)

ANVISA registration number: not yet available.

All documentation supporting this Declaration of Conformity is preserved in the quality management system of the manufacturer, supported by the ISO 13485 certificate issued by BSI.

This document was issued in Bilbao, on the following date:

Signature and date
General Manager full name

Intended use or purpose​

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.

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-001
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All the information contained in this QMS is confidential. The recipient agrees not to transmit or reproduce the information, neither by himself nor by third parties, through whichever means, without obtaining the prior written permission of Legit.Health (AI LABS GROUP S.L.)