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IQuity's IsolateMS test is now available. IsolateIBS-IBD will be available in late fall and IsolateFibromyalgia by the end of this year. Please join our community to stay up-to-date on our test release dates and new research efforts underway.

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Innovation in Autoimmune Diagnostics

IQIsolate is a proprietary process utilizing machine learning methods to develop a suite of algorithms that analyze expression of RNA markers detected in a simple blood sample. The suite of algorithms is the foundation of the Isolate test panels that can rule in or rule out a suspected autoimmune disease at the earliest onset of symptoms – in as little as 7 days.

The Isolate test panels give healthcare providers a new tool to confirm suspected diagnoses across three medical disciplines – neurology, gastroenterology, and rheumatology. This new process can identify disease much sooner than traditional diagnostic methods, which can take months to years. By confirming the suspected autoimmune disease faster, doctors can initiate treatment of autoimmune patients earlier in the disease progression. Earlier treatment can help slow the illness and allow better management of its long-term physical, emotional and financial effects.

Groundbreaking Technology

IQuity’s proprietary process, IQIsolate analyzes RNA expression data from a blood sample to identify the presence or absence of disease at the cellular level. RNA expression is representative of the presence of disease in real time, while changes in DNA indicate the potential risk of disease. IQIsolate is the foundation of the Isolate test panels that can distinguish among diseases in a given specialty – the gastroenterology panel can distinguish between irritable bowel syndrome (IBS) and inflammatory bowel disease (IBD). Within IBD, this technology can accurately distinguish Crohn’s from ulcerative colitis. The IQIsolate process takes one week and delivers results with greater than 90% accuracy.

IQuity is firmly committed to data transparency and scientific peer review and invites you to review our peer-reviewed publications.

IQIsolate - The Foundational Process

IQIsolate is a proprietary process utilizing machine learning methods to develop a suite of algorithms that analyze the expression of RNA markers detected in a simple blood sample. IQuity has applied this approach to neurology, gastroenterology, and rheumatology, three specialties that serve a majority of autoimmune patients.

IQIsolate, which powers IQuity's Isolate tests: IsolateMS™, is now available; the IsolateIBS-IBD™ panel will be available by fall 2017, and the IsolateFibromyalgia™ panel by the end of the year. These tests will support providers in earlier diagnosis for conditions, such as:

  • Multiple Sclerosis
  • IBS
  • Crohn’s Disease
  • Ulcerative Colitis
  • Fibromyalgia
  • Lupus
  • Rheumatoid Arthritis
  • Other challenging autoimmune and related conditions

Our Research

Research efforts for this novel technology began at Vanderbilt University Medical Center more than 12 years ago, with funding from the National Institutes of Health. The scientists involved realized the impact this discovery would make on millions of patients suffering from autoimmune disease and formed IQuity to commercialize the research. IQuity is validating the Isolate test panels which will be available for clinical use in 2017.

The IQIsolate suite of algorithms was built on patient samples from around the globe. Using machine learning methods, researchers were able to distinguish specific autoimmune diseases and related conditions in three medical specialties of neurology, gastroenterology, and rheumatology, among these enrolled subjects:

  • Healthy control subjects
  • Patients prior to diagnosis who are then followed in the EMR
  • Patients with disease prior to treatment
  • Patients with established disease
  • Other diseases that are commonly seen by the specialists treating the diseases in our three medical specialties

Peer-Reviewed Articles

Identification of Molecular Biomarkers for Multiple Sclerosis

Quantitative real-time polymerase chain reaction analysis was used to identify a minimum number of genes of which transcript levels discriminated multiple sclerosis patients from patients with other chronic diseases and from controls.

Gene-expression signatures: biomarkers toward diagnosing multiple sclerosis

Results indicate that gene-expression differences in blood accurately exclude or include a diagnosis of MS and suggest that these approaches may provide clinically useful prediction of MS.

Using biomarkers to predict progression from clinically isolated syndrome to multiple sclerosis

Using machine learning techniques, including support vector machines, this study demonstrates that gene expression signatures can accurately identify subjects with a clinically isolated syndrome who later progress to multiple sclerosis.