RCS - LungLife AI, INC - Data Supporting LungLB to be Presented at the AMP

LungLife AIAnnouncement

02/09/2024 07:00

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RNS Number : 3508C  LungLife AI, INC  02 September 2024

LungLife AI, Inc.

(the "Company" or "LungLife")

 

 Data Supporting LungLB to be Presented at the Association for Molecular
Pathology

 

LungLife AI (AIM: LLAI), a developer of clinical diagnostic solutions for lung
cancer, is pleased to announce that our two abstract submissions to the
Association for Molecular Pathology(1) (AMP) have been accepted for both
presentation at their flagship 2024 Annual Meeting & Expo in Vancouver,
BC, Canada from November 19-23(rd), and also for publication in the November
2024 issue of The Journal of Molecular Diagnostics.

The acceptance of our abstracts for both presentation and publication is a
recognition of the interest in, and significant potential of, our LungLB®
test. They provide us with an exciting opportunity to further raise market
awareness and understanding of the LungLB® test as we highlight the results
of two important LungLB® studies demonstrating the analytic and clinical
validity of the test to a broad range of clinical laboratories, healthcare
providers, and industry representatives.

In addition, the data presented serve to expand the clinical evidence for the
LungLB® test which is important to encourage and support adoption of the test
by centres.

Commenting on the acceptance, Paul Pagano, Chief Executive Officer of
LungLife, said:

"We are excited to have these two abstracts accepted for both presentation and
publication by the AMP and believe this marks another important step in the
pathway to commercialisation.

AMP brings together a diverse community of physicians, scientists, and
laboratory professionals from academic and community medical centres,
government, and industry. We are looking forward to furthering discussions
that allow us to demonstrate our commitment to advancing early detection of
lung cancer and making a significant impact in this critical area of
healthcare."

Full details of the abstracts are as follows:

 

Abstract Title: Analytical Validation of the LungLB test: a blood-based
4-color FISH assay for the evaluation of indeterminate pulmonary nodules

Presenter: Eric Vail, MD, Cedars-Sinai Medical Center

Abstract # 1874291

 

Abstract Title: Clinical Validation of LungLB: a Circulating Genetically
Abnormal Cell-based Classifier for Indeterminate Lung Nodule Evaluation

Presenter: Paul Pagano, PhD

Abstract # 1874647

 

For further information please contact:

 

 LungLife AI, Inc.                                   www.lunglifeai.com (https://www.lunglifeai.com/)
 Paul Pagano, CEO                                    via investors@lunglifeai.com
 David Anderson, CFO

 Investec Bank plc (Nominated Adviser & Broker)      Tel: +44 (0)20 7597 5970
 Virginia Bull / Lydia Zychowska/ Sara Wallace

 Goodbody (Joint Broker)                             Tel: +44 (0) 20 3841 6202
 Tom Nicholson / Cameron Duncan

 

 

 

Notes

1.    Originally founded in 1995, AMP advances the clinical practice,
science, and excellence of molecular and genomic laboratory medicine through
education, innovation, and advocacy to enable highest quality health care, and
is the primary resource for expertise, education, and collaboration in one of
the fastest growing fields in healthcare. AMP members influence policy and
regulation, and develop practice guidelines on the national and international
levels, ultimately serving to advance innovation in the field and protect
patient access to high quality, appropriate testing.

 

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
(http://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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