Source - LSE Regulatory
RNS Number : 0809E
Spectral MD Holdings, Ltd.
09 March 2022
 

Spectral MD Holdings, Ltd

("Spectral MD" or the "Company" or the Group")

 

Notice of Full Year Results

Investor presentation

 

LONDON, U.K AND DALLAS, TX, U.S - Spectral MD Holdings, Ltd. (AIM: SMD), a predictive analytics company that develops proprietary AI algorithms and optical technology for faster and more accurate treatment decisions in wound care, announces that its full year results for the year ended 31 December 2021 will be released on Monday, 21 March 2022.

 

Investor presentation

Wensheng Fan, Chief Executive Officer, and Nils Windler, Chief Financial Officer, will provide a live presentation relating to the Company's results via the Investor Meet Company platform on Monday, 21 March at 16:30hrs GMT.

 

The presentation is open to all existing and potential shareholders. Questions can be submitted pre-event via your Investor Meet Company dashboard up until 9am GMT the day before the meeting or at any time during the live presentation.

 

Investors can sign up to Investor Meet Company for free and add to meet Spectral MD Holdings, Ltd. via:

https://www.investormeetcompany.com/spectral-md-holdings-ltd/register-investor 

 

Investors who already follow Spectral MD Holdings, Ltd. on the Investor Meet Company platform will automatically be invited.

 

For further information, please contact:

Spectral MD Holdings, Ltd.

https://investors.spectralmd.com/

Wensheng Fan, Chief Executive Officer

Nils Windler, Chief Financial Officer

via Walbrook PR



SP Angel Corporate Finance LLP (Nominated Adviser and Joint Broker)

+44 (0) 20 3470 0470

Stuart Gledhill / Caroline Rowe (Corporate Finance)

Vadim Alexandre / Rob Rees (Sales and Corporate Broking)




 

Stifel Nicolaus Europe Limited (Joint Broker)

+44 (0) 20 7710 7600

Charles Hoare / Ben Maddison / Will Palmer-Brown




Walbrook PR Ltd (Media & Investor Relations)

+44 (0)20 7933 8780 or spectralMD@walbrookpr.com

Paul McManus / Sam Allen

Louis Ashe-Jepson

 

+44 (0)79 8054 1893/ +44 (0)75 0255 8258

+44 (0) 7747 515393

 

 

 

About Spectral MD:                                                                                       

 

Using its DeepView® Wound Imaging Solution, an internally developed AI technology and multispectral imaging solution that has received FDA Breakthrough Designation for the burn indication, Spectral MD is able to distinguish between non-healing and healing human tissue invisible to the naked eye. Spectral MD currently is able to provide 'Day One' healing assessments for burn wounds and diabetic foot ulcers with other applications being explored.

 

Spectral MD has to date received substantial support from the U.S. government with contracts from institutions such as Biomedical Advanced Research and Development Authority, National Science Foundation, National Institute of Health and Defense Health Agency in support of the burn application for its DeepView® solution, with total grant funding received to date from all of these organisations of over $93 million, including $40.5 million received in 2021. This grant funding is non-dilutive to our shareholders and the Company believes it validates the important nature of our mission and technology. The Company leverages this funding to support R&D efforts that are applicable to burn, DFU and potentially other indications where DeepView® can play an important role in Day 1 wound healing assessment.

 

The Company has two principal trading subsidiaries, Spectral MD, Inc. and Spectral MD UK Limited.

 

DeepView®

DeepView® is a predictive analytics platform that integrates proprietary AI algorithms and advanced optical technology for wound healing predictions. It is non-invasive, non-radiation, non-laser and does not require the use of injectable dye. This integration can be characterised into four distinct components: DeepView® imaging, data extraction, AI model building and AI wound healing prediction.

 

·    The DeepView® imaging technology consists of patented, proprietary, multi-spectral optics and sensors that can classify wound tissue physiology and capture the viability of various biomarkers within the skin. The imaging technology extracts appropriate clinical data, processes the image, and displays a comparison of the original image next to an image with a colour overlay of the non-healing portions of the wound. The image acquisition takes 0.2 seconds, and the output takes approximately 20 to 25 seconds.

 

·    The DeepView® data extraction consists of proprietary optics that are able to collect millions of data points from each raw image. This information is then used to build and continually improve the AI model, which is trained and tested against a proprietary database of more than 66.7 billion pixels with an ever-growing input of clinically validated data points.

 

·    The AI algorithm then produces a predictive wound healing assessment in the form of an objective, accurate, and immediate binary wound healing prediction. This prediction is graphically represented to the clinician through a coloured overlay of the original image that annotates the non-healing portion of the wound.

 

DeepView® is designed to allow clinicians to make a more accurate, timely and informed decision regarding the treatment of the patient's wound. In the case of DFUs, a non-healing assessment would provide the clinician with the appropriate justification to use an advanced wound care therapy on 'Day One' as opposed to waiting 30 days and potentially losing the patient to lack of patient follow-up or risking patient noncompliance with standard wound therapy. For burn wounds, the clinician can make an immediate and objective determination to identify appropriate candidates for surgery as well as determining what specific areas of the burn wound will require skin grafting. DeepView®'s current accuracy for determining the healing potential of burn wounds is 92 percent in adults and 88 percent in children, compared with current physician accuracy of 50 to 70 percent. The current clinical accuracy of DeepView® is 83 percent for DFUs.  Both of these accuracy percentages are expected to increase with additional R&D efforts, including clinical studies.

 

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