Autoimmune Disease Diagnostic Breakthrough

IQuity’s research reveals that autoimmune patients exhibit distinct RNA expression patterns in their blood. This is a critical breakthrough in the ability to detect autoimmune disease and related conditions as they present. Using the IQIsolate process, our tests can distinguish between difficult to diagnose diseases. For example, the Isolate tests can distinquish multiple sclerosis from other neurological diseases; IBS from Crohn’s and ulcerative colitis; and fibromyalgia from rheumatoid arthritis or lupus.

IQuity’s analytic process, IQIsolate™, uses machine learning to develop algorithms that analyze RNA gene expression in whole blood. IQIsolate™ measures the expression of RNA markers that are extracted from a patient’s blood sample. This RNA analysis distinguishes between healthy and diseased patients identified through our extensive research. IQIsolate™ accurately determines if the patient’s RNA expression pattern is consistent with a specific disease. IQuity’s ability to identify these patterns gives providers information to confirm a suspected diagnosis with analytical accuracy greater than 90%.

Answers. Not Clues.

For nearly 20 years, DNA has been used to craft associations for disease, but it cannot always identify the presence or absence of disease. For many autoimmune diseases, the presence of genetic risk factors does not guarantee that the patient will develop these conditions. IQuity has found that RNA gene expression patterns provide accurate information about real-time activity in immune cells within the blood.

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RNA Unlocks the Code

Accurate Results

Improved Outcomes

Our Autoimmune Research

Research efforts for this novel technology began at Vanderbilt University Medical Center more than a decade ago, with funding from the National Institutes of Health. It was clear that this RNA research would make a substantial impact on millions of patients long- suffering from autoimmune diseases and resulted in the formation of IQuity. The company continues to advance the Isolate test panels which are currently coming to market.

Using machine learning methods, researchers were able to distinguish specific autoimmune diseases and related conditions in three medical specialties – neurology, gastroenterology and rheumatology. The IQIsolate™ algorithms were built on patient samples enrolled from around the globe. These include:

Healthy control subjects
Patients prior to diagnosis who are then followed in their Electronic Health Record (EHR)
Patients with disease prior to treatment
Patients with established disease
Other diseases that are commonly seen by specialists treating these patients

Changing the Future for Providers and Patients Challenged by Autoimmune Disease

When we were launching IQuity, I made an intentional effort to talk with people who had been diagnosed with an autoimmune disease. I wanted to know what I couldn’t find out in the lab – how it feels to learn you have a life-altering, incurable disease. After all, how you feel about something determines what you do about it.

IQuity makes it possible to know quite quickly, and with a high degree of confidence, whether that tingling in your leg is simply because you sat with your legs crossed too long or is an early symptom of multiple sclerosis (MS).

At the core of IQuity’s research program is a firm commitment to translating bench innovations into clinical practice. IQuity was founded by scientists leveraging technology developed at Vanderbilt University Medical Center over the last decade with funding from the National Institutes of Health and private investment, IQuity is now bringing this new technology to communities that are desperately seeking advancements in diagnosis and treatment.

IQuity is committed to transparency. Our science, processes and analytic capabilities are an open book. Through our website, scientific presentations, and published papers, we are eager to share with you what we do, how we do it and ways we believe we can be of value to the healthcare community.

Chase Spurlock, PhD
Chief Executive Officer

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