Virginia Based AMPEL BioSolutions' Machine Learning Breakthrough Predicts Chronic Disease Flares From A Blood Sample

CHARLOTTESVILLE, Va., July 9, 2019 /PRNewswire/ -- AMPEL BioSolutions today announces a breakthrough in precision and personalized medicine that could revolutionize the way doctors treat chronic diseases, like Lupus. Revealed in the peer-reviewed journal Nature's Scientific Reports, the paper details our breakthrough machine learning approach to predict disease activity from gene data obtained from patient blood samples. The lab test, only a concept for the last few years, is now ready for development for practical use. AMPEL's initial focus was Lupus, but the test can be used for many autoimmune or inflammatory diseases.

AMPEL's innovative machine learning approach, which is now ready to be developed as a decision support biomarker blood test, could greatly impact health care by allowing physicians to identify the cause of patient disease symptoms and select appropriate treatment more precisely.  The application of our machine learning approach could assist pharmaceutical companies in drug development and clinical trials.

Patients of chronic autoimmune diseases, like Lupus, often suffer from unpredictable flares that impact daily activities like work and family life. Since unpredictable flares in disease activity often result in trips to the Emergency Room, the ability to predict flares with a simple blood test has important health care and health economics implications.  Paired with our pipeline of tools to analyze very large and complex clinical datasets ("Big Data") AMPEL's machine learning program is a significant step towards implementing a routine blood test for monitoring disease activity and providing decision support for drugs prescribed based on a patient's genes. This will transform the way doctors treat chronic diseases by using the information gathered by the lab test and analyzed by machine learning to predict a flare and treat it before it even begins, saving patients from pain and inconvenience of a disease that otherwise drastically affects their lives.

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 blood test will help pharmaceutical companies identify which patients are most likely to respond to specific treatments, thereby helping improve outcomes in clinical trials.

Dr. Peter Lipsky, Chief Medical Officer and Co-Founder, AMPEL BioSolutions: "There is currently no other application that can precisely predict disease activity and propose appropriate treatments, and we are very encouraged by this breakthrough reported in Nature's Scientific Reports.  For those patients suffering with chronic diseases such as Lupus, meaningful innovation in treatments can't come soon enough.  Following the development of our machine learning concept, we can now move forward in working with our partners to develop this blood test that could transform the way doctors can help patients with chronic illness manage their disease by offering better and more precise treatments based on individual patient data rather than a general approach."

Dr. Donald Thomas, Rheumatologist, Former Chair, Medical/Scientific Advisory Council, Lupus Foundation of America, and Associate Professor of Medicine, Uniformed Services University of Health Sciences: "I am excited about AMPEL's work on a clinical genomic test that may accurately predict flares in lupus patients. Although there are numerous FDA-approved drugs that target different parts of the immune system, as a physician, I have no way of knowing which medications will work in which patients.  Management strategies often end up being 'trial and error' treatment decisions, and physicians and patients will greatly benefit from a tool like this that will allow for more precise treatments. Because not all medications work in all patients, currently, it can take many months and suffering before we are able to determine a treatment's effectiveness. When AMPEL's clinical genomic test is validated and we are able to quickly identify the best medications for each patient, it will change the game in taking care of our patients, allowing us to choose the correct medications immediately and obtain faster and safer control of their Lupus. This is very exciting and I look forward to the results of further studies."

Tyler Orion, co-founder, Precision Healthcare Ecosystem:  "The founders of Precision Healthcare Ecosystem and our Project Apollo patient cohort represent a range of patients with undiagnosed or hard-to-treat conditions.  We are excited about the prospect of having this breakthrough technology available.  We believe that the future of healthcare is patient-centric, and we applaud AMPEL's quest to enable this approach."

Jay Remley, Vice-Chair, LFNC (Lupus Foundation of Northern California) and former Executive Google Cloud: "With 1.4M Americans living with lupus and every patient's disease different, leveraging cloud computing with Machine learning and AI is critical to move patient treatment from clinical to personal medicine.  AMPEL's clinical genomic test will improve the lives for millions of Lupus patients globally."

Kathleen Arntsen, President and CEO, Lupus and Allied Diseases Association:  "I commend AMPEL for having the vision to utilize their innovative machine learning approach to address the critical unmet need of efficiently monitoring the ever-fluctuating disease activity in lupus.  As both the leader of a national patient-led organization and as a person struggling with multiple autoimmune diseases myself, I am thrilled that AMPEL's clinical genomic test provides the additional benefit of a physician support report that lists the most appropriate drugs for that individual.  This is not only groundbreaking, but has the potential to greatly enhance the clinical trials selection process as well as prove treatment efficacy and value to insurers which are two of the biggest challenges the lupus and autoimmunity communities face.  Furthermore, AMPEL's precision medicine platform is an example of the right drug for the right patient at the right time and couldn't be timelier since health care access and drug costs are major issues in the country." 

Angel Williams, Virginia Lupus Patient: "I am thrilled to learn about AMPEL's clinical gene test. It has the potential to truly ensure a better quality of life for patients like me. Not having to wait days for a doctor's appointment when I know a flare is coming on will save me from suffering and expedite my treatments, and this is game changing. I look forward to following this development."

Background Information

Machine learning is an analytic technique to train computers to assess information and make predictions.  AMPEL has used this approach in a novel way to train a computer to analyze data obtained from assessing a kind of "Big Data", namely that obtained by assessing gene expression information, to predict whether an individual living with lupus is experiencing a flare in disease activity. Gene expression analysis examines the number and pattern of the genes expressed at a given moment and can provide insight into the entire spectrum of genomic abnormalities.

Many chronic diseases have unexpected flares that dramatically affect patient quality of life. Further, treatments for chronic disease have been developed based on a patient population as a group, so some individuals will respond differently or not at all to available treatments.  For the past five years, the scientists and clinicians at AMPEL have been working on ways to address this problem, by designing concepts to personalize treatments for an individual patient as opposed to a patient population. Our paper published in Nature's Scientific Reports confirms the practicality of AMPEL's concept, which can now go into the development phase.

AMPEL's initial focus was lupus but the test can be used for many autoimmune or inflammatory diseases.  AMPEL's blood test will confirm whether the change in disease activity indicates a flare is approaching and provides decision support report for their physician with the top most appropriate drugs right for the patient at that moment in time.

Next steps include developing the physical lab test and rigorously examining the results in a clinical trial.  AMPEL'S goal is to have their test available for routine use by physicians within the next few years.

About AMPEL BioSolutions LLC (2013-present)

Harnessing Data to Improve Lives through Genomics
AMPEL BioSolutions is a technology company with CRO capabilities based in Charlottesville Virginia.  AMPEL has developed a clinical genomic test in the Immunology space to predict flares and the correct drug for a patient based on machine learning of gene expression.  Our proof-of-concept was Lupus and we are expanding into other autoimmune/inflammatory diseases.  AMPEL's markets are Patient/Physician, Payor and Pharma.

SOURCE AMPEL BioSolutions