With the results of the AMR Challenge quickly approaching, we wanted to take a moment to reflect on our amazing team’s development activities over an extremely aggressive timeline leading up to the final submission. It’s important to note that none of this would have been possible without our friends and collaborators over at Predigen.
Straight from the National Institutes of Health (NIH)...
The Antimicrobial Resistance Diagnostic Challenge (AMR) is a $20 million federal prize competition seeking innovative, rapid point-of-care laboratory diagnostic tests to combat the development and spread of drug resistant bacteria. A rising public health problem, antibiotic resistant bacteria cause at least 2.8 million infections and 35,000 deaths each year in the United States, according to the Centers for Disease Control and Prevention (CDC).
The Challenge called for new, innovative, and novel laboratory diagnostic tests that identify and characterize antibiotic resistant bacteria and/or distinguish between viral and bacterial infections (this is where we come in) to reduce unnecessary uses of antibiotics, a major cause of antibiotic resistance. With real-time detection, healthcare providers will be able to identify infecting pathogens and resistance factors in <1 hour, rather than days, and use the knowledge to tailor treatment to each individual.
The prize is sponsored by two groups within the U.S. Department of Health and Human Services: the National Institutes of Health and the HHS Office of the Assistant Secretary for Preparedness and Response (ASPR) in support of the National Action Plan for Combating Antibiotic Resistant Bacteria.
Our team is 1 of only 4 finalists that were able to submit and the only team focused on differentiating bacterial vs. viral infections. Up to 3 winners are set to be announced on July 31, 2020.
As Dr. Ephraim Tsalik from the Predigen team has said, discriminating between viral and bacterial infection is no easy task, which has contributed to the overuse of antibiotics and the rise of antibiotic-resistant organisms. Current tests, including those based on the detection of antigens or amplification of a DNA target, miss most cases of bacterial infection. And, while viral pathogens are readily detected via PCR-based tests, a negative result does not reliably exclude a viral infection. Adding even more complexity to this, studies have shown that a positive result is not particularly meaningful since it cannot distinguish an infection from colonization. For example, a person’s throat could be colonized with strep bacteria and have no issues but then become infected with a virus that gives them a sore throat. A positive strep test may lead their doctor to prescribe antibiotics and neglect the real issue: a viral throat infection.
Our alternative solution uses host gene expression signatures. Up until now, gene expression has mainly been used in the context of cancer because that’s where a large portion of the work characterizing transcriptomes has occurred. So, how does it work here in the context of infections?
Essentially, if you are believed to have an upper respiratory infection, your healthcare provider can test a fingerstick drop of your blood and tell rather quickly, based on your immune system’s response, whether you have a bacterial infection or a viral infection. We’re not detecting the specific pathogen but your body’s response to that pathogen because our bodies respond differently to a bacterial infection than they do a viral infection, which is something our test can detect.
It’s our intention for such a test to be administered prior to prescribing antibiotics using our 27-target multiplex quantitative RT-PCR assay in combination with a mobile point of care instrument, such as the Franklin™ Real-Time PCR Thermocycler.
The process of discovering a host gene expression signature requires several key steps. First is recruiting thousands of patients with the relevant medical condition, which itself requires a very careful effort to identify the presence of a bacterial or viral infection. Then, we agnostically measured the expression of tens of thousands of genes. Machine learning algorithms then learn from this data to find patterns (signatures) that are characteristic of bacterial or viral infection. This gene expression information then feeds into a mathematical equation that tells the provider whether the patient is responding to a bacterial or viral infection. Originating at Duke University, the Predigen team has spent nearly 20 years developing these processes and applying them to a variety of medical conditions. In this case, our first test focuses on determining whether an acute respiratory infection is bacterial (and might need antibiotics) or viral (which doesn’t need antibiotics).
Within a year, the Biomeme R&D team was able to...
Many of you reading this blog post may not fully understand the technical tasks listed above, but what our team was able to achieve in such a short time is pretty incredible and for that we are super proud.
But in all seriousness, regardless of whether or how much we win, we’re convinced that Gene Expression Profiling of Host Response is an ideal human health application for curbing the unnecessary uses of antibiotics. And, much of our future development will involve this, in addition to, our continued fight against COVID-19.
We’ll be sure to post an update once the results are announced so stay tuned!
If you have any questions, or wish to learn more, please do not hesitate to reach out to contact us.
Thanks for reading!