AMPEL BioSolutions’ Precision Medicine Breakthrough Predicts Drug Options with RNA Analytics & Machine Learning

AMPEL BioSolutions today announces a breakthrough in precision and personalized medicine that could modernize the way doctors treat patients across a wide variety of diseases including autoimmunity, infectious disease and cancer. Revealed at the Precision Medicine World Conference in Silicon Valley California, the first-in-class platform technology utilizes RNA analytics and machine learning to characterize an individual’s gene expression and provide clinical decision support to physicians for treatment options for their patients.  The technology, only a concept for the last few years, is being utilized to launch a portfolio of 10+ clinical tests over the next five years to provide decision support for diseases that affect more than 50 million Americans.

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AMPEL’s innovative machine learning approach, which is now ready to be developed as a clinical decision support biomarker test, could greatly impact health care by allowing physicians to identify the cause of patient disease symptoms and select appropriate treatment more precisely.  AMPEL’s approach is sufficiently sensitive to detect early signs of disease and group patients by the severity of their condition. The application of AMPEL’s technology is already assisting 15+ pharmaceutical companies in drug development and clinical trials.

Patients with autoimmune and inflammatory diseases often suffer from unpredictable disease activity that impacts daily activities like work and family life. Since unpredictable symptoms often result in trips to the Emergency Room, the ability to predict worsening disease and systemic involvement with routine testing has important health care and health economics implications. AMPEL expects to bring it’s first two products to market in the next few years, LuGENE blood test for Lupus and DermaGENE skin biopsy test for Psoriasis, Atopic Dermatitis, Scleroderma and Lupus. In addition, AMPEL’s CovGENE blood test that predicts how severe a disease course a COVID patient may experience and may be applicable to “long COVID” is ready for licensing/co-development with a company already offering COVID diagnostic testing.

Paired with AMPEL’s pipeline of tools to analyze very large and complex clinical datasets (“Big Data”), AMPEL’s Genomic Platform technology with machine learning is a significant step towards implementing routine testing to monitor disease activity and provide decision support for treatment based on a patient’s gene expression. This will transform the way doctors treat patients by using the information gathered by the lab test and analyzed by machine learning to diagnose, characterize the precise molecular abnormalities and treat diseases before damage begins, saving patients from pain and inconvenience of diseases that otherwise drastically affect their lives.

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Pharmaceutical companies test drugs in clinical trials and face the challenge of enrolling patients that have the best potential to respond to the treatment being tested.  Enrolling the “wrong” patients can result in trial failure, often leading to cancellation of a drug’s development towards FDA approval that may have benefit in a sub-group of the overall patient population. AMPEL’s technology helps pharmaceutical companies proactively identify the patients most likely to respond to specific treatments, thereby helping improve outcomes in clinical trials and quality of life for patients in need. AMPEL’s Pharma work was highlighted by Dr. Peter Lipsky at the Precision Medicine World Conference in a panel discussing the use of machine learning in clinical trial patient selection and outcome prediction and by Dr. Amrie Grammer at a Google-Reuters webinar focused on machine learning approaches to select the right patient for the right trial at the right time.

Dr. Peter Lipsky, AMPEL Co-Founder, CEO and Chief Medical Officer: “It is very gratifying to see a concept develop into a reality that can help patients. When we began some years ago we thought that analyzing gene expression data could subset patients effectively and allow the molecular profile of each patient to be used to help identify the best treatment for each individual. By applying novel machine learning approaches, we are now ready to launch our first application that we believe should be a major step toward providing patients with autoimmune diseases true precision medicine.”

Dr. Amrie Grammer, AMPEL Co-Founder, President and CSO: “”Our team has developed a genomic platform technology with machine learning that supports clinical precision medicine tests that predict drug options based on gene expression.  AMPEL is changing the paradigm of treatment in autoimmune and inflammatory diseases.  We are proud to be doing this work in Virginia and will continue to recruit talent and grow our business here.”

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