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  • Professor Andrea M. Armani, University of Southern California
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  • Mohan Wang, Ph.D., University of Oxford
  • Professor Xuchen Wang, Harbin Engineering University
  • Professor Stefan Witte, Delft University of Technology

Know Labs to Present at the American Diabetes Association’s Scientific Sessions

Latest clinical research results demonstrate a stable MARD in an expanded dataset.

Know Labs, Inc. (NYSE American: KNW), a leading developer of non-invasive medical diagnostic technology, today announced further interim results from a clinical research study that assessed the accuracy of Know Labs’ proprietary non-invasive radiofrequency (RF) dielectric sensor in measuring blood glucose. Participants with prediabetes and Type 2 diabetes were studied and venous blood was used as a comparative reference. The study found that the accuracy of Know Labs’ proprietary sensor in estimating blood glucose values remained statistically stable, with an expanded dataset and a new machine learning (ML) model.

Dr. Virend K. Somers of the Mayo Clinic serves as an author and co-investigator on the clinical research protocol. Dr. Somers will present an abstract titled, “A New Machine Learning Model and Expanded Dataset for a Non-Invasive BGM” at the American Diabetes Association’s 84th Scientific Sessions (ADA) in Orlando, Florida during a general poster presentation session on Saturday, June 22 at 12:30 PM - 1:30 PM EDT.

This study reflects the latest results in Know Labs’ first clinical research protocol involving people with diabetes and using venous blood as a comparative reference. In March of this year, Know Labs presented early interim results from the same clinical research protocol at the 17th International Conference on Advanced Technologies & Treatments for Diabetes (ATTD), in which its non-invasive blood glucose monitor and ML model trained on data collected in a lab setting achieved a MARD of 11.1%. Compared to the previous study, which was based on 10 participants and 650 paired RF and reference blood glucose values, this study involved more than twice as much data collected from 22 participants yielding 1,430 paired values.

Study Design

The proprietary RF sensor employed in the study measures glucose levels using dielectric spectroscopy by rapidly scanning a large range of RF frequencies and recording voltage values detected at each frequency to quantify, with trade-secret ML algorithms, real-time continuous blood glucose levels. The sensor continuously scanned participants' forearms for up to three hours during a 75g Oral Glucose Tolerance Test. From the 22 participants, 1,430 venous blood samples were collected using a peripheral intravenous catheter and analyzed using an FDA-cleared blood glucose hospital meter as a reference device.

Data was preprocessed using smoothing techniques and an 80/20 split was performed to create model training and test datasets, respectively. Know Labs trained a ML model to estimate reference venous blood glucose values on 80% of the data consisting of 1,143 paired RF device and venous blood glucose values randomly selected from the total dataset and then tested on the remaining, held-out 20% of data (287 paired values).

Results

On the held-out test dataset, blood glucose was estimated with a MARD of 11.8% ± 1.5% relative to venous blood. It performed similarly on normoglycemic (12.1% ± 1.8%) and hyperglycemic (11.0% ± 2.3%) ranges.

Compared to the previous results presented in March, the MARD of 11.8% is not statistically significantly different, nor were the results in the hyperglycemic range (>180 mg/dL) and normoglycemic range (70 to 180 mg/dL), indicating stability in accuracy.

These interim results are part of a larger, now completed clinical study with over 30 participants, conducted September 2023 through February 2024. As the Company continues on the path toward FDA clearance, Know Labs will deploy the recently announced KnowU™ wearable non-invasive continuous glucose monitor in ongoing clinical and bench studies. The wearable form factor of the KnowU device allows these studies to evaluate the technology’s performance throughout continuous wear, in ‘real-world’ environments outside of the lab where new elements of interference are likely, and within more extreme glycemic ranges (below 70 mg/dL and above 350 mg/dL). As new data is collected in these areas and additional variables come into play, the Company will make necessary refinements to the device and accompanying algorithms. To stay updated on the latest clinical research results, visit www.knowlabs.co/research-and-development.

About Know Labs, Inc.

Know Labs, Inc. is a public company whose shares trade on the NYSE American Exchange under the stock symbol “KNW.” The Company’s platform technology uses spectroscopy to direct electromagnetic energy through a substance or material to capture a unique molecular signature. The technology can be integrated into a variety of wearable, mobile or bench-top form factors. This patented and patent-pending technology makes it possible to effectively identify and monitor analytes that could only previously be performed by invasive and/or expensive and time-consuming lab-based tests. The first application of the technology will be in a product marketed as a non-invasive glucose monitor. The device will provide the user with accessible and affordable real-time information on blood glucose levels. This product will require U.S. Food and Drug Administration clearance prior to its introduction to the market.

Safe Harbor Statement

This release contains statements that constitute forward-looking statements within the meaning of the Private Securities Litigation Reform Act of 1995 and Section 27A of the Securities Act of 1933, as amended, and Section 21E of the Securities Exchange Act of 1934, as amended. These statements appear in a number of places in this release and include all statements that are not statements of historical fact regarding the intent, belief or current expectations of Know Labs, Inc., its directors or its officers with respect to, among other things: (i) financing plans; (ii) trends affecting its financial condition or results of operations; (iii) growth strategy and operating strategy; and (iv) performance of products. You can identify these statements by the use of the words “may,” “will,” “could,” “should,” “would,” “plans,” “expects,” “anticipates,” “continue,” “estimate,” “project,” “intend,” “likely,” “forecast,” “probable,” “potential,” and similar expressions and variations thereof are intended to identify forward-looking statements. Investors are cautioned that any such forward-looking statements are not guarantees of future performance and involve risks and uncertainties, many of which are beyond Know Labs, Inc.’s ability to control, and actual results may differ materially from those projected in the forward-looking statements as a result of various factors. These risks and uncertainties also include such additional risk factors as are discussed in the Company’s filings with the U.S. Securities and Exchange Commission, including its Annual Report on Form 10-K for the fiscal year ended September 30, 2023, Forms 10-Q and 8-K, and in other filings we make with the Securities and Exchange Commission from time to time. These documents are available on the SEC Filings section of the Investor Relations section of our website at www.knowlabs.co. The Company cautions readers not to place undue reliance upon any such forward-looking statements, which speak only as of the date made. The Company undertakes no obligation to update any forward-looking statement to reflect events or circumstances after the date on which such statement is made.

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