LungLB® study published in peer-reviewed journal

LungLife AI, INC

06 June 2023

 

LungLife AI, Inc.
(the "Company" or "LungLife")

LungLB® study demonstrating high performance published in peer-reviewed journal

LungLife AI (AIM: LLAI), a developer of clinical diagnostic solutions for lung cancer, announces the publication of successful performance results for the Company's blood-based LungLB® test from a multi-site prospective study in patients with indeterminate pulmonary nodules. The study was performed in collaboration with MD Anderson Cancer Center (Houston, TX) and Icahn School of Medicine at Mount Sinai (New York, NY) and appears in the journal BMC Pulmonary Medicine.

The primary objective of the study was to compare the LungLB® test result with a lung biopsy diagnosis and assess performance in a patient cohort where commonly used nodule evaluation tools were not informative.

Key points from the study include:

·   151 study participants scheduled for CT-guided lung biopsy, 70% of whom were found to have "intermediate risk" nodules that represent the most challenging diagnostic subtype

·   The LungLB® test outperformed commonly used evaluation tools, including the Mayo Clinic risk model and PET scan

·   The test demonstrated robust performance in smaller nodules (<2 cm in diameter) and in early-stage cancer

·   The LungLB® biomarker was found to be the strongest independent predictor of cancer in this study, exceeding commonly known strong predictors such as nodule size and smoking status

·   The LungLB® test performed equally well in current, former, and never smokers

·   The data support potential clinical utility of LungLB® in reducing delays in treatment, in which positive LungLB® test results were available months ahead of lung cancer diagnosis in three highlighted cases

LungLB® is a blood-based liquid biopsy assay that uses fluorescence in situ hybridisation ("FISH") and image analysis to identify circulating genetically abnormal cells ("CGAC"), which include circulating tumour cells ("CTCs"). The technique incorporates an AI-derived image analysis strategy to identify unique cell populations reflective of the disease state under interrogation.

The current publication is an independent validation in the US population and informed the design of LungLife's larger, pivotal validation study that started in February 2022. The pivotal validation study results are expected later this year and are not included in this publication.

The publication can be found here: https://doi.org/10.1186/s12890-023-02433-4.

Commenting, Paul Pagano, Chief Executive Officer of LungLife, said: "Having the results of our study peer-reviewed is not only an independent confirmation of the scientific validity of our approach, but is also an important part of our strategic effort to build evidence for efficacy and utility in our efforts to increase access of our testing to those who need it most.

"We were excited to see that the LungLB® performance remained strong in people who never smoked, because evidence has shown that the incidence of lung cancer in never smokers is increasing, and it is important new technologies address this expanding group. Additionally, LungLB® was able to detect cancer in its earliest stages, which can be the most challenging to diagnose for doctors and most beneficial for patients."

BMC Pulmonary Medicine is in the Springer-Nature family of journals, and is an open access, peer-reviewed journal that considers articles on all aspects of the prevention, diagnosis and management of pulmonary and associated disorders. Studies must be scientifically valid; for research articles this includes a scientifically sound research question, the use of suitable methods and analysis, and following community-agreed standards relevant to the research field. Peer-review is the system used to assess the quality of a manuscript before it is published. Independent researchers in the relevant research area assess submitted manuscripts for originality, validity and significance to help editors determine whether the manuscript should be published in their journal.

For further information please contact:

LungLife AI, Inc.	www.lunglifeai.com
Paul Pagano, CEO	Via Walbrook PR
David Anderson, CFO
Investec Bank plc (Nominated Adviser & Broker)	Tel: [phone]
Virginia Bull / Cameron MacRitchie / Lydia Zychowska
Goodbody (Joint Broker)	Tel: [phone]
Tom Nicholson / Stephen Kane
Walbrook PR Limited	Tel: [phone] or [e-mail]
Stephanie Cuthbert / Alice Woodings / Phillip Marriage	Mob: [phone]

About LungLife

LungLife AI is a developer of clinical diagnostic solutions designed to make a significant impact in the early detection of lung cancer, the deadliest cancer globally. Using a minimally invasive blood draw, the Company's LungLB® test is designed to deliver additional information to clinicians who are evaluating indeterminate lung nodules. For more information visit www.lunglifeai.com

Our Purpose is to be a driving force in the early detection to lung cancer.  And our Vision is to invert the 20:80 ratio such that in years to come at least 80% of lung cancer is detected early.

 

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