CBS19 News 5:00 & 6:00 Broadcast June 12, 2020

CBS19 News 5:00 & 6:00 Broadcast June 12, 2020

  • June 15, 2020
  • News

Charlottesville-based company develops COVID-19 test
CHARLOTTESVILLE, Va. (CBS19 NEWS) — A Charlottesville-based precision medical company has developed a new approach to predicting the severity of the coronavirus. Link to the full broadcast: https://www.cbs19news.com/clip/15082777/ample-biosolutions-test

AMPEL BioSolutions has developed technology to determine how severely a person will react to coronavirus and identify the best, FDA-approved treatment options. The company has been working since March to develop a new test amid the COVID-19 pandemic.

“AMPEL’s goal is to accelerate getting effective treatments to COVID patients to be able to blunt that serious illness that leads to lung damage and death,” said  Dr. Amrie Grammer, Co-Founder, COO, and CSO of AMPEL BioSolutions.

Grammer, a double University of Virginia-graduate, said the company began work quickly to get results, publishing a paper in just five weeks.

“We started working around the clock and were able to get some results in five weeks to be able to suggest drugs that would blunt that very serious illness that leads to lung damage,” she said.

The genomic test, CovGENE, uses bodily fluids from a nasal swab or blood for testing. A partnership with a diagnostic company could expedite the test’s timeline.

“To partner with an existing diagnostic company that has a test on the market for COVID, to be able to license that, and they could very quickly bring this to market, with the right company it could be available in a matter of months,” Grammer said.

AMPEL’s focus has shifted slightly over the past few months.

“Our goal was bringing new drugs to patients with serious illness, initially Lupus, a very serious auto-immune disease that affects women,” Grammer said.

Amidst the coronavirus pandemic, she felt an obligation to focus on COVID-19 research.

“A contribution to the scientific community and we felt an obligation to bring that forward, especially in these very difficult COVID-19 pandemic times,” Grammer said.

AMPEL BioSolutions is working to get its lupus treatment, LuGENE, a gene-based diagnostic for patients to determine disease status, predict flares ups, and match patients with the best drug options, to market by 2022. The company is currently securing funding.

News Radio WINA Interview

News Radio WINA Interview

  • June 10, 2020
  • News

Charlottesville Based Companies Technology Predicts Severity of COVID-19 Illness in Patients and Identifies Treatments. Aired June 9, 2020

Les Sinclair talks with Dr. Amrie Grammer about AMPEL BioSolutions, a Charlottesville Virginia company that has reengineered the gene-based technology they developed for lupus to COVID19.

Link to full interview: https://soundcloud.com/1070wina/local-companies-technology-predicts-severity-of-covid-19-illness-in-patients-identifies-treatments

RadioIQ Interview – Cville Company Develops New COVID Test

RadioIQ Interview – Cville Company Develops New COVID Test

  • June 10, 2020
  • News

Aired June 10, 2020 – Virginia Public Radio’s Sandy Hausman
A Charlottesville biotech company says it’s come up with a test that predicts the most severe cases of COVID-19 and could guide doctors in their choice of medications to save lives.

Scientists at AMPEL Biosolutions had been studying lupus – an auto-immune disease in which the body’s white blood cells cause inflammation of joints and organs.  What they heard about the most serious cases of COVID-19 sounded familiar.

“There are certain white blood cells that normally would fight off the COVID that are out of control and are actually propagating damage to the lungs and other organs,” says Amrie Grammar, AMPEL’s Chief Scientific Officer. “These uncontrolled white blood cells are secreting a variety of inflammatory compounds that are driving the severe symptoms and the lung damage.”

Not everyone who gets COVID suffers that symptom, but those who do may end on a ventilator and many will die.  So AMPEL developed a test that identifies those at greatest risk for serious complications and could guide doctors to use certain medications that would reduce or prevent inflammation of the lungs.  The company hopes it can collaborate with a firm that makes diagnostic kits for the coronavirus, so that doctors can identify patients and plan treatment strategies with just one test.  

Link to full interview: https://www.wvtf.org/post/cville-company-develops-new-covid-test#stream/0

Virginia Based AMPEL BioSolutions’ Technology Predicts Severity Of Illness In COVID19 Patients And Identifies Treatments

Virginia Based AMPEL BioSolutions’ Technology Predicts Severity of Illness in COVID19 Patients and Identifies Treatments

Charlottesville, Virginia. June 9, 2020. AMPEL BioSolutions announces genomic analysis and findings that could improve treatment of COVID19 patients with approved drugs such as Embrel and Stelara. Published on bioRxiv as a preprint, the study reveals a gene-based test that will be able to determine those patients who may progress to severe illness with increased likelihood of morbidity. In addition, AMPEL’s CovGENE approach identifies FDA-approved drugs that may be appropriately repositioned to interfere with mechanisms that cause lung damage in severe COVID19 patients. The paper describes gene expression measured in three body compartments (lung, airway and blood) and integrates information from the blood and lung for a “whole body” understanding of the effects of SARS-CoV2 virus.

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Machine Learning, After Fine-tuning, May Be Useful for SLE Classification, Study Suggests

  • January 20, 2020
  • News

Machine Learning, After Fine-tuning, May Be Useful for SLE Classification, Study Suggests

Lupus News Today
By Marisa Wexler, MS
July 12, 2019

Machine learning analysis strategies can help predict disease status in people with systemic lupus erythematosus (SLE), a study shows. Still, technical variability inherent to each clinical analysis method can represent a roadblock in this process.

Fine-tuning of machine learning algorithms and parameter sets may help reduced technical “noise” caused by such variability, the researchers suggest. They said this would generate “sufficient accuracy to be informative as a standalone estimate of disease activity.”

Titled “Machine learning approaches to predict lupus disease activity from gene expression data,” the study was published in Nature Scientific Reports

Diagnosing and classifying SLE is a challenge for clinicians because the disease is so varied in how it presents. One proposed way to classify this type of lupus is based on gene expression levels, which evaluate which genes are “turned on” and by how much.

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