PathAI Launches MET Predict on AISight to Enhance NSCLC Assessments

Boston, MA – September 10, 2024 – PathAI, a global leader in artificial intelligence (AI) and digital pathology solutions, today announced the launch of MET Predict on the AISightⓇ† Image management system (IMS). MET Predict is an AI-powered algorithm designed to help pathologists identify non-small cell lung cancer (NSCLC) tumors that may be more likely to have MET exon 14 skipping (METex14) or MET amplification, directly from an H&E whole slide image.

Figure - MET Predict highlights morphological features of the cancer epithelium area associated with MET dysregulation.
Figure - MET Predict highlights morphological features of the cancer epithelium area associated with MET dysregulation.


NSCLC accounts for approximately 85% of lung cancers1, with 3–4% of these cases involving METex142. Today, approved targeted therapies are available for patients with NSCLC who harbor METex14 mutations. Additionally, MET amplification occurs in 1–6% of NSCLC cases3 and is emerging as a potential biomarker in lung cancer.

Traditional molecular testing for MET alterations such as exon 14 skipping or amplification is often hindered by high costs, time- and tissue-consuming procedures, and the need for specialized equipment and trained personnel. These factors limit its accessibility and scalability, prompting the need for more efficient and cost-effective methods to assess MET alterations.

“The integration of MET Predict into AISight marks a significant leap forward in utilizing AI to enhance the efficiency of NSCLC tumor assessments, particularly in identifying those with potential genetic alterations,” said Andy Beck, MD, PhD, co-founder and CEO of PathAI. “By providing rapid and precise biomarker insights directly from H&E images, MET Predict equips pathologists with the essential information needed to drive timely and accurate NSCLC evaluations.”

MET Predict has the potential to significantly improve the efficiency of biomarker evaluation and molecular testing paradigms. The algorithm identifies >90% of MET altered tumors while additionally providing insights that may preserve tissue in 30% of cases where the likelihood of MET alteration is low.

With the addition of MET Predict, AISight expands its toolset with the latest technology to assist pathologists in lung cancer assessments. This innovation addresses a crucial gap in pathology labs — the need for accessible, rapid, and comprehensive molecular tools that provide actionable insights from biopsy samples.

About PathAI
PathAI is a leading provider of integrated AI and digital pathology solutions, dedicated to transforming diagnostic accuracy and operational efficiency in pathology labs worldwide. Through innovative technologies and strategic partnerships, PathAI aims to enhance patient outcomes and drive the future of medical diagnostics.

Footnote
:MET Predict and AISight are for Research Use Only. Not for use in diagnostic procedures.

References:
1. American Cancer Society. Key Statistics for Lung Cancer. https://www.cancer.org/cancer/lung-cancer/about/what-is.html​

2. Frampton, G. M., et al. Activation of MET via diverse exon 14 splicing alterations occurs in multiple tumor types and confers clinical sensitivity to MET inhibitors. Cancer discovery, 5(8), 850-859.​

3. Wolf J., et al. Capmatinib in MET Exon 14-Mutated or MET-Amplified Non-Small-Cell Lung Cancer. N Engl J Med. 2020 Sep 3;383(10):944-957. doi: 10.1056/NEJMoa2002787. PMID: 32877583

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