Cancer screening today is inconvenient and invasive. Two leading cancers, colon and breast, use screening technologies developed 50 years ago, leading the New York Times to label colonoscopies the “Dreaded Turning 50 Test.”¹ As a result, these dated and uncomfortable cancer screening technology mammographs are on the decline.² ³
Yet, screening is critical. Cancer patients have a 90% chance of survival if cancer is detected at stage I versus only a 5% chance at stage IV4.
Over the past 10 years, the team of scientists at Laboratory for Advanced Medicine have used Artificial Intelligence and Machine Learning to identify unique and proprietary DNA signatures that predict the presence of cancer as early as Stage I. We are focused on developing simple, accurate and customer-friendly tests that can detect cancer early.
All from a simple blood draw.
“We are focused on developing simple, accurate and customer-friendly tests that can detect cancer early.”
– LAM CEO
PNAS July 11, 2017 114 (28) 7414-7419
Evaluation of the utility of DNA methylation profiles for differentiating tumors and normal tissues for four common cancers (lung, breast, colon, and liver). The authors found that they could differentiate cancerous tissue from normal tissue with >95% accuracy demonstrating the utility of methylation biomarkers for the molecular characterization, diagnosis, and prognosis of cancer.
Cell volume 172, issue 5, pages 1122-1131
Description of a diagnostic tool based on an artificial intelligence system using transfer learning techniques developed to effectively classified images for macular degeneration and diabetic retinopathy as well as accurately distinguished bacterial and viral pneumonia on chest X-rays.
Nature Materials volume 16, pages 1155–1161 (2017)
Identification of an HCC-specific methylation marker panel by comparing HCC tissue and normal blood leukocytes and showed that methylation profiles of HCC tumour DNA and matched plasma ctDNA are highly correlated with high specificity and sensitivity.
- Cheuk – Review – Methylation of ctDNA for Breast Cancer Detection
- Galanopoulos – Review – Abnormal ctDNA Methylation for Colon Cancer Detection
- Guo – Tissue of origin mapping using NGS and CpG methylation of DNA in plasma
- Hao – DNA Methylation Markers for Diagnosis and Prognosis of common cancers
Laboratory for Advanced Medicine Clinical Research Programs
To gain regulator approval to support our cancer test accuracy claims, Laboratory for Advanced Medicine is conducting extensive clinical study programs in the United States and China. Through collaborations with leading scientists, physicians, research institutions and regulators worldwide, we aim to validate our products and provide the most effective diagnostic technologies to patients and doctors.
Clinical Trial for the Liver Cancer Test (CLiMB)
CLiMB is a clinical trial to detect liver cancer through the quantification of cfDNA methylation in blood samples.
- The trial is designed to evaluate the performance of our liver cancer test versus the standard of care today – an ultrasound test.
- The study will enroll approximately 1,600 participants ages 21 to 84 years with a diagnosis of liver cirrhosis and hepatitis and who are currently recommended for liver cancer screening every six months by ultrasound. This study is expected to be completed in 2020.
- The trial is designed to evaluate the performance of our liver cancer test against the performance of ultrasound and Alpha Fetoprotein (AFP) test.
- The study will enroll approximately 1,000 participants with a diagnosis of primarily hepatitis. This study is expected to be completed by the first half of 2020.
LAM has patented its cfDNA methylation markers since 2014. The patents cover methylation markers, method of using methylation for early cancer detection, and our AI technology.