LungLife AI — Early-stage lung cancer diagnostics

LungLife AI — Early-stage lung cancer diagnostics

LungLife AI is a medical diagnostics company focused on the development of AI-supported blood-based tests for the early detection of lung cancer. It has identified a significant medical need for non-invasive, sensitive and specific tests in early-stage lung cancer. The company’s core technology, the LungLB test, seeks to detect circulating tumour cells (CTCs) to identify malignant lung nodules. It aims to apply machine learning/AI (ML/AI) to derive algorithms to increase test accuracy. Following a 2021 pilot study showing 76% sensitivity and 71% specificity, LungLife AI is currently planning a large-scale validation study, with the aim of commercialising in 2023.

Harry Shrives

Written by

Harry Shrives

Associate Analyst

LungLife AI

Early-stage lung cancer diagnostics

Healthcare

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17 January 2022

Price

188p

Market cap

£48m

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Share details

Code

LLAI

Listing

AIM

Shares in issue

25.4m

Business description

LungLife AI is a medical diagnostic company focused on the application of AI in the early-stage detection of lung cancer. Its LungLB blood test uses CTCs as biomarkers to provide physicians with information to avoid unnecessary biopsies or risky ‘wait-and-see’ approaches in lung cancer diagnosis. The company is planning for a large-scale clinical validation study following results from its 2021 pilot study.

Bull

Unmet medical need for early diagnosis in lung cancer.

Clinical development supported by scientific expertise at Mount Sinai.

Quick, non-invasive diagnostic tool.

Bear

Early-stage product carries significant R&D risk.

Lung cancer diagnostics is a large and competitive market.

Delays to trials and/or commercialisation could necessitate a further capital raise.

Analysts

Harry Shrives

+44 (0)20 3077 5700

Jacob Thrane

+44 (0)20 3077 5700

LungLife AI is a medical diagnostics company focused on the development of AI-supported blood-based tests for the early detection of lung cancer. It has identified a significant medical need for non-invasive, sensitive and specific tests in early-stage lung cancer. The company’s core technology, the LungLB test, seeks to detect circulating tumour cells (CTCs) to identify malignant lung nodules. It aims to apply machine learning/AI (ML/AI) to derive algorithms to increase test accuracy. Following a 2021 pilot study showing 76% sensitivity and 71% specificity, LungLife AI is currently planning a large-scale validation study, with the aim of commercialising in 2023.

Early diagnosis is an unmet medical need

According to the World Health Organization, lung cancer accounted for 1.8 million deaths worldwide in 2020. Diagnosis and treatment at an early stage has a significant effect on lung cancer survival rates. Low-dose computed tomography (LDCT) scans are the standard method for lung cancer screening; however, these return a high rate of false positives when assessing indeterminate lung nodules. Consequently, a high percentage of lung biopsies are conducted on benign nodules, increasing the cost and the risk of adverse events. The alternative ‘wait-and-see’ approach results in delayed treatment, significant anxiety for the patient and a potentially worse prognosis.

FISH-ing for CTCs

The LungLB test uses a patient’s blood sample, which is shipped to the company’s Clinical Laboratory Improvement Amendments (CLIA) approved lab. Red cells and some white blood cells are removed from the sample and the remaining cells are stained with fluorescence in situ hybridization (FISH) probes, allowing the identification of cancerous DNA markers, if present. A computer-controlled microscope takes pictures and sorts the images of cancerous cells based on these FISH signals. Subsequently a technician reviews the images before the results are sent back to the physician. LungLife AI aims to develop and implement ML/AI-derived algorithms to increase the accuracy of the image sorting. The full process takes approximately five days.

Clinical validation trials planned

LungLife AI completed a pilot study of 149 participants with biopsy-confirmed cancerous and non-cancerous lung nodules. The LungLB test demonstrated a sensitivity of 76%, a specificity of 71% and a positive predictive value of 89%, leading to the company listing on the AIM section of the London Stock Exchange in July 2021. After raising £17m in July 2021, the company now intends to conduct a multi-centre, large-scale (425-participant) clinical validation study. If positive, a clinical utility study will follow to support reimbursement from US insurers. LungLife AI hopes this cash will take it to commercialisation in 2023. However, any delays may mean that it needs to raise extra capital.

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Frankfurt +49 (0)69 78 8076 960

Schumannstrasse 34b

60325 Frankfurt

Germany

London +44 (0)20 3077 5700

280 High Holborn

London, WC1V 7EE

United Kingdom

New York +1 646 653 7026

1185 Avenue of the Americas

3rd Floor, New York, NY 10036

United States of America

Sydney +61 (0)2 8249 8342

Level 4, Office 1205

95 Pitt Street, Sydney

NSW 2000, Australia

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This report has been prepared and issued by Edison. Edison Investment Research standard fees are £60,000 pa for the production and broad dissemination of a detailed note (Outlook) following by regular (typically quarterly) update notes. Fees are paid upfront in cash without recourse. Edison may seek additional fees for the provision of roadshows and related IR services for the client but does not get remunerated for any investment banking services. We never take payment in stock, options or warrants for any of our services.

Accuracy of content: All information used in the publication of this report has been compiled from publicly available sources that are believed to be reliable, however we do not guarantee the accuracy or completeness of this report and have not sought for this information to be independently verified. Opinions contained in this report represent those of the research department of Edison at the time of publication. Forward-looking information or statements in this report contain information that is based on assumptions, forecasts of future results, estimates of amounts not yet determinable, and therefore involve known and unknown risks, uncertainties and other factors which may cause the actual results, performance or achievements of their subject matter to be materially different from current expectations.

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No personalised advice: The information that we provide should not be construed in any manner whatsoever as, personalised advice. Also, the information provided by us should not be construed by any subscriber or prospective subscriber as Edison’s solicitation to effect, or attempt to effect, any transaction in a security. The securities described in the report may not be eligible for sale in all jurisdictions or to certain categories of investors.

Investment in securities mentioned: Edison has a restrictive policy relating to personal dealing and conflicts of interest. Edison Group does not conduct any investment business and, accordingly, does not itself hold any positions in the securities mentioned in this report. However, the respective directors, officers, employees and contractors of Edison may have a position in any or related securities mentioned in this report, subject to Edison's policies on personal dealing and conflicts of interest.

Copyright: Copyright 2022 Edison Investment Research Limited (Edison).

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Frankfurt +49 (0)69 78 8076 960

Schumannstrasse 34b

60325 Frankfurt

Germany

London +44 (0)20 3077 5700

280 High Holborn

London, WC1V 7EE

United Kingdom

New York +1 646 653 7026

1185 Avenue of the Americas

3rd Floor, New York, NY 10036

United States of America

Sydney +61 (0)2 8249 8342

Level 4, Office 1205

95 Pitt Street, Sydney

NSW 2000, Australia

Frankfurt +49 (0)69 78 8076 960

Schumannstrasse 34b

60325 Frankfurt

Germany

London +44 (0)20 3077 5700

280 High Holborn

London, WC1V 7EE

United Kingdom

New York +1 646 653 7026

1185 Avenue of the Americas

3rd Floor, New York, NY 10036

United States of America

Sydney +61 (0)2 8249 8342

Level 4, Office 1205

95 Pitt Street, Sydney

NSW 2000, Australia

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