Company's Data Analytics Platform Prepared to Immediately Combat the Invisible Healthcare Epidemic Head On
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NASHVILLE, Tenn., May 13, 2019 /PRNewswire/ -- IQuity , the industry's only autoimmune disease-focused data analytics platform to address the fixable risk hidden in health plans, today announced that the company was published in a peer-reviewed article in the Journal of Clinical Medicine. This work is one of the first comprehensive overviews of prevalence, clinical characteristics, challenges, and financial impacts of autoimmune diseases and related disorders (multiple sclerosis, ulcerative colitis, Crohn's disease and rheumatoid arthritis, irritable bowel syndrome and fibromyalgia syndrome). These six conditions alone affect approximately 60 million people at an estimated cost to diagnose and treat of $90B annually. Contrasting the prevalence of autoimmune diseases (50M people) and related syndromes (40M people) with cancer and COPD which affect 15 million and 24 million people respectively highlights the importance of focusing on these diseases even further. In the article titled, "Illuminating an Invisible Epidemic: Addressing Cost Drivers in Diagnosis and Treatment of Autoimmune Diseases and Disorders," IQuity determined after an extensive review of the literature four critical factors that impact cost in autoimmune disease:
Treatment
Promotion of treatment adherence
For the inflammatory diseases and related conditions examined, the health system cost-savings potential is estimated to be greater than $18 billion. "Almost everyone knows someone who is affected by an autoimmune disease or related syndrome," said Chase Spurlock , PhD, CEO at IQuity. "Most people don't understand what an autoimmune disease is or the impact these conditions have on patients and the overall healthcare system. IQuity is committed to working with care management companies, self-insured employers, health plans and their partners to directly address this hidden health epidemic that's wreaking havoc on the industry's bottom line." The peer-reviewed article can be read in full here . IQuity is Poised to Combat the Invisible Health Epidemic Today
As evidenced by the research findings, the impact autoimmune diseases pose to U.S. healthcare spending is severe. With the availability of IQuity's autoimmune disease-focused data analytics platform, client insurance claims data are being analyzed to proactively find the addressable financial risk. Insights are produced that stakeholders can use to positively impact patient care and simultaneously reduce healthcare expenditures on these complex, chronic patients. IQuity recently performed an analysis on a three-payer dataset using over three years of claims data for 2.2 million lives which further validated the ability of the company's commercial platform to generate highly accurate predictions for these target conditions. The proven impact of IQuity's platform is illustrated through two specific examples related to delayed disease diagnosis and undetected risk. In a population of Crohn's patients predicted with the disease in 2015, IQuity averaged their spend before and after a conventional diagnosis and found that a three-year delay increases the average annual cost of treatment by more than $13,000/year. If patients were diagnosed and treated earlier based on the predictions delivered, the average savings would be $9,000 per patient annually. Additionally, IQuity's platform identified a member with a Crohn's prediction in 2015. The patient received related gastrointestinal diagnoses over time, but a formal treatment plan for Crohn's was not prescribed until 2017. Over the course of three years, the total healthcare spend for the patient was over $1 million. $385,000 was spent in various hospital settings. "Predictive analytics in healthcare is a crowded space, often with little competitive differentiation," said Damian Mingle , chief data scientist at SwitchPoint Ventures , an IQuity partner. "While many groups claim to have access to large amounts of data, this information alone cannot deliver clinical value unless these groups have the requisite expertise to deliver meaningful insights. IQuity stands out because they are combining a deep knowledge of autoimmune diseases and related syndromes with best in class data science approaches to generate actionable insights. These insights give clients and providers information to improve outcomes and lower costs." "When it comes to autoimmune diseases, IQuity illustrates that time is of the essence," said Julia Polk , chief strategy officer and CFO at IQuity. "With our proven predictive analytics model, we are well positioned to pave the way towards faster, more accurate identification and more efficient management of the conditions. This approach can replace the potentially months or even years spent on the traditional patient diagnostic journey." To learn more about how IQuity is working with healthcare organizations today to identify undetected, uncontrolled or misdiagnosed autoimmune conditions and help reduce associated financial risk please visit iquity.com. About IQuity
IQuity is a Nashville-based analytics company offering the only autoimmune disease-focused data analytics platform to enhance care management for payers who are pressured to find new ways to lower the cost of healthcare. Contact: Kathy Gill, 615-481-6646, kathy@iquity.com
SOURCE IQuity

IQuity Research Unveils Potential $18 Billion in Health Plan Cost-Savings and Demonstrates...

IQuity builds first data analytics platform to help payers find and fix their addressable autoimmune disease risks
on April 17 th, 2019 by Tom Ballard
By Tom Ballard, Chief Alliance Officer, PYA
On the heels of commercializing a third test focused on autoimmune diseases in 2018, Chase Spurlock of Nashville start-up IQuity says he and his team asked themselves a key question: “How can we leverage our data science knowledge and disease experience in a bigger way?”
After all, the company that Spurlock founded is built on more than a decade of machine learning expertise with genomic data across multiple autoimmune diseases. The answer was to build the first data analytics platform to help payers – insurance companies, self-insured enterprises, and their Third-Party Administrators – find and fix their addressable autoimmune disease risks. Unlike the genomic blood data that IQuity studied previously, this platform requires only insurance claims data to produce insights that providers can use to positively impact patient care. How costly is the population that includes autoimmune diseases like multiple sclerosis, rheumatoid arthritis, Crohn’s disease, and ulcerative colitis? Spurlock, IQuity’s Chief Executive Officer, cites data from the National Institutes of Health that says autoimmune diseases affect more than 23.5 million Americans and cost the healthcare system more than $100 billion annually. That’s more than either cancer or heart disease, both in terms of individuals impacted and the resulting diagnosis and treatment costs. IQuity’s platform will also target fibromyalgia and irritable bowel syndrome. These disorders are not autoimmune diseases, but mimic the symptoms of autoimmune disease – presenting an opportunity for IQuity to help alleviate diagnostic confusion. Collectively, these six conditions can impact up to 16% of a given population. “Every one of these diseases affects you or someone you know,” Julia Polk, IQuity’s Chief Strategy Officer and Chief Financial Officer, adds. For the company that recently moved its corporate offices into Nashville’s iconic Cummins Station, the singular focus is to help individuals that might have an undetected autoimmune disease, one that is misdiagnosed, or one that goes uncontrolled. IQuity’s genomics lab is still in the nearby Cumberland Emerging Technologies facility. “The treatments for autoimmune disease are expensive,” Spurlock says, adding, “Our past experience with our genomics tests suggest that doctors are using our tools to correct misdiagnoses.”
Why is that important? He and Polk cite several reasons. Establishing an early, accurate diagnosis lessens disability, improves quality of life, and can save millions in avoidable medical expenses. Patients who are misdiagnosed are receiving therapies that cost tens of thousands of dollars each year. “The drugs used to treat autoimmune disease carry certain risks,” Spurlock says, emphasizing the importance of getting the diagnosis right. Someday Spurlock and Polk hope the platform will be able to connect patients with optimal treatments. “You have patients that might not be on the best drug,” Spurlock stated. Polk amplified this point, explaining that “the patient’s disease might be controlled this month but uncontrolled the next month.” For now, IQuity hopes that its monitoring approach will allow providers to have an ‘early warning system’ that enables care teams to be proactive and make the necessary changes to a patient’s treatment plan. To help with implementation, IQuity recently partnered with SwitchPoint Ventures , itself a Nashville start-up led by Ray Guzman. It is important to note, as Spurlock did in this late 2017 teknovation.biz article , that IQuity is providing a tool, not a test. “The doctors are making the diagnosis and treatment decisions,” he said at the time. So, how does the process that IQuity utilizes actually work? The client sends healthcare claims and other structured data to IQuity. That data is enriched with IQuity’s proprietary data and social determinants of health – socio-economic, crime, environmental, etc. – based on zip code. The data are analyzed for trends. IQuity delivers insights from the analysis to the plan provider and individual results to the providers or patients. From there, the plans are able to better identify and understand the risks and to recommend actions to improve patient outcomes while also reducing medical care expenditures. “We are the only people doing this level of analytics in autoimmune diseases,” Spurlock says, adding, “This is a framework that can be applied to any disease. IQuity has a remarkable opportunity to impact clinical outcomes and costs.”
For Polk, a long-time player in the Nashville start-up and corporate scene, it’s exciting seeing the progress that IQuity has made. “We’ve come a long way in a short period of time and our entire team is committed to never losing sight that patients are the ultimate beneficiaries of any technology we develop,” she says.

IQuity builds first data analytics platform to help payers find and fix their addressable autoimmune disease risks

November 16th, 2018
Losing one’s memories, and therefore one’s identity, must be a terrifying experience. With a global estimate of almost 50 million people living with dementia, predicted to rise to more than 130 million by 2050, the burden of Alzheimer’s and dementia are indisputable. While there are still no approved drugs for the treatment of Alzheimer’s, there is an urgency for developing diagnostic tests and the identification of biomarkers that enable the early detection of the disease. In light of this need, diagnostic technology company IQuity (pronounced I-Q-witty) has recently received a grant from the National Institutes of Health (NIH) to build a platform around the early detection of Alzheimer’s. We sat down with IQuity’s Founder and CEO, Dr. Chase Spurlock, to talk about this effort and the company’s progress with other diseases they have tackled. Mohammad Saleh, Medgadget: Tell us about yourself and how you came to be a part of this work. Chase Spurlock, IQuity:  I’m the CEO of IQuity, a tech company based in Nashville using data science to detect and monitor disease. At IQuity, we can use a variety of data sources – ranging from blood samples to large, population-level healthcare datasets including insurance claims or electronic health records to identify disease and help optimize patient journeys. A large portion of my work has focused on autoimmune diseases through research initiated at IQuity and through my faculty position at Vanderbilt. Autoimmune diseases affect you and someone you know – these are conditions like multiple sclerosis, rheumatoid arthritis, Crohn’s disease and others where the immune system harms the body’s tissues and organs. We can’t cure these diseases, but we can treat them. If we can detect the disease early, we have the best chance for optimal long-term outcomes including reduced disability and longer life expectancy. The first demonstration of our use of data science to build tools to help providers diagnose and treat these illnesses was to create blood-based tools that doctors can use to make fast, accurate diagnoses. We created a platform that looks at RNA data, a real-time snapshot of what’s taking place inside the patient’s blood cells, and then builds computer models to allow us to examine new patient samples and ask if they look like patients with specific diseases we may have seen before. To date, we have commercialized three tests leveraging our technology for multiple sclerosis, IBS (irritable bowel syndrome) and IBD (Crohn’s disease and ulcerative colitis), and fibromyalgia syndrome. Apart from our blood-based studies, we began using our disease knowledge and data science expertise to look at large, population-level datasets to see if we could craft similar insights that enable early disease detection and patient monitoring. Layering claims data with datasets that help us understand the social determinants of health, we have been able to mirror our blood testing work and create a technology that enables faster disease detection, correction of misdiagnosis and the ability to monitor patient disease at scale. Monitoring is critical to ensure that treatment plans remain effective and prevent adverse events. Our approach makes it possible to alert care teams so that interventions can occur faster than is conventionally possible today. As we look to the future and the broad applicability of our technology, we began exploring whether we could use our blood-based approach or population analytics platform to tackle new disease indications. Alzheimer’s disease quickly rose to the top of the list because this fatal neurodegenerative disease affects over five million Americans and often goes unnoticed until symptoms manifest 15-20 years after the damage to the brain starts. We feel that our approach using blood-based technology for population-level analytics holds extraordinary potential to make an indelible mark on how clinicians can approach Alzheimer’s care in the years ahead. Medgadget: Can you give our readers a quick overview of what the current status of Alzheimer’s early detection and drug research is? Spurlock: We need tools that can accelerate the diagnosis of Alzheimer’s disease – whether these innovations come in the form of biomarker development, digital technologies, or a combination of the two. Both approaches will allow us to understand how the disease develops and progresses, the patient populations affected by Alzheimer’s and provide opportunities to refine future clinical trials by enhancing patient recruitment efforts. There are no approved treatments that can slow the progression of Alzheimer’s disease – they are primarily used to treat symptoms and are useful for only a short window of time. In the future, approved drugs for Alzheimer’s will be most effective when administered early. The diagnostic tools we have proposed to develop through our NIH-funded studies seek to identify patients at the earliest stages of the disease and could potentially be used in clinical trials to assess treatment responses. If we can identify patients early and include them in clinical trials, we will have a better chance of finding therapeutics that can alter the trajectory for this devastating condition. Medgadget: What makes IQuity uniquely adept at​ tackling this problem? Spurlock: At IQuity, we have successfully commercialized tools that can be used to identify disease. Using multiple sclerosis (MS) as an example, we have shown that we can identify patterns in blood at the time of a clinically isolated syndrome, which is the major clinical precursor to MS. In MS and fibromyalgia, have shown us that these long non-coding RNAs (lncRNAs) exhibit high levels of disease-type specificity meaning that lncRNA patterns measured in blood are often specific for one disease and can be used to differentiate among similar conditions and healthy individuals. The preliminary studies that we outlined in our recent Alzheimer’s grant highlight the utility of these biomarkers to distinguish Alzheimer’s disease from other neurological illnesses. As an expansion of our work in genomics, we are eager to explore the use of the longitudinal health records in our population datasets (insurance claims data or electronic health records) to assess whether our existing data science approaches could be applied to identify early patterns for Alzheimer’s. These efforts will help us understand environmental, racial or other social factors that can explain how this disease may arise and could lead to opportunities for early intervention. Across both areas of our business, I believe IQuity is uniquely poised to make discoveries that can improve diagnostic tools, inform pharmaceutical development and enhance the quality of life for patients living with many diseases. While autoimmune conditions have traditionally been our focus, the opportunities to help patients with a variety of medical conditions, including Alzheimer’s, are possible with the infrastructure we have put in place. Medgadget: Can you tell us about​ the technology driving the Alzheimer’s detection efforts? How does it work and where does machine learning factor in? Spurlock: The funding we recently received will support our work to identify and measure lncRNA found in blood and build software capable of detecting specific RNA patterns for Alzheimer’s disease. RNA-sequencing will allow us to identify candidate RNAs we will then validate in a larger cohort of Alzheimer’s patients, disease controls and age-matched healthy controls. Data derived from this expanded cohort will then be used to train machine learning models to determine if these biomarkers can be used to construct a specific blood-based pattern for Alzheimer’s. Independent blood samples not included in the training will be used to test if the model can accurately and reproducibly distinguish among these groups. This work will consist of patients from across the United States, allowing us also to examine if geography can influence the expression of the RNAs we identify. What’s interesting about this approach is that machine learning helps us identify the RNAs present in a blood sample that hold the highest level of ‘predictive power’ and determine among those we select which RNAs are more or less important in determining the presence of Alzheimer’s or any other disease we choose to study. While we are explicitly using our approach to build diagnostic strategies to identify presence or absence of disease, use of these methods could uncover novel targets for therapeutic intervention if these biomarkers are found to change as a consequence of intervention. Medgadget: Can you maybe share some specific success stories? How accurate has the platform been so far? Spurlock: Pilot funding from the NIH will be used to launch our Alzheimer’s work. It will allow us to expand our focus beyond the company’s traditional emphasis on autoimmune disease to test if our approach can be used to detect Alzheimer’s accurately. What we have documented thus far is that our blood tests are more than 90 percent accurate for the autoimmune and related conditions that we’ve examined. Medgadget: Do you think work like IQuity’s early detection efforts for Alzheimer’s can lead to a renewed interest in searching for therapeutics for Alzheimer’s? Spurlock: Absolutely. If we can identify these diseases early using genomics or population-level analytics, we will have a series of useful tools that can help determine the right patients for clinical trials. Identifying these patients at the earliest moment means they can take an investigational drug and have the best chance to reap the benefit of these new therapeutics. As Bill Gates and the Alzheimer’s Drug Discovery Foundation have correctly stated many times, the new drugs currently under development will be most successful in slowing early Alzheimer’s. All too often, patients who develop Alzheimer’s are caught many years after the disease has already caused damage to the brain. If we can identify diagnostic biomarkers, we can better understand the genetics of how these diseases manifest and begin to understand, at a molecular level, the mechanistic underpinnings of the disease and create targeted assays that can look for these changes. Using population-level analytics to ask these same types of questions, we can begin pinpointing the social determinants of disease and from these studies further refine the inclusion and exclusion criteria for clinical trials. The combination of molecular and population analytics, I believe, will enable us to understand better the types of patients who ultimately arrive at an Alzheimer’s diagnosis and create a window for early intervention. Medgadget: Where do you see IQuity in the next 5-10 years with your work in Alzheimer’s and other areas? Spurlock:  IQuity’s future is very bright. We’re at a significant inflection point in healthcare where we are starting to see artificial intelligence/machine learning tools implemented more often for clinical use. At IQuity, we are creating a series of platform technologies that we can apply to many areas of human health and disease. While we have focused on autoimmunity and related disorders, we have found that our blood-based and population-level analytics can affect many conditions. The work we’ve done has shown that we can predict oncoming diagnoses, spotlight misdiagnoses, and stratify severity of disease. A unique aspect of our approach is the ability to trigger not only an alert, but embed a context or reasoning into each alert that helps those receiving this information understand how our tools arrived at a result. I think this level of insight is going to be at the heart of how we can positively shape healthcare to make the patient experience better, improve outcomes and lower healthcare costs. Medgadget: When should we expect to be hearing more data about IQuity’s Alzheimer’s efforts? Spurlock:  The focus of this project hits close to home for many on our team. My own family has witnessed firsthand the negative consequences of early Alzheimer’s and dementia. We often wondered if we could have done something differently to recognize or treat the underlying causes of the disease – but it just wasn’t possible. There remains so much work to be done to make this a reality. At IQuity, the second we received funding we immediately began work. Our laboratory efforts are underway to refine the biomarkers we have already identified, and I would expect data to emerge in the next several months that we intend to share at conferences or in peer-reviewed journals. For more information, check out IQuity’s website or read our previous interview .

Tackling Alzheimer’s Biomarkers Using Machine Learning: Interview with IQuity CEO, Dr. Chase Spurlock

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NASHVILLE, Tenn., Sept. 25, 2018 /PRNewswire/ --  IQuity , a Nashville-based data analytics company that specializes in predicting, detecting and monitoring chronic disease, today announced it has received a $320,000 grant from the National Institute on Aging (NIA), part of the National Institutes of Health (NIH). The grant will allow the company to expand its focus to include Alzheimer's disease and apply its genomic expertise to develop new diagnostic tools to help providers identify disease early. As part of its research, IQuity will use its new machine learning-based data mining and analytics platform – which analyzes many types of information, including genomic and other healthcare datasets – to predict and detect Alzheimer's. IQuity launched its analytics platform in July. Alzheimer's is the sixth leading cause of death in the U.S., with 5.7 million people suffering from the disease. The Alzheimer's Association estimates the cost of healthcare and long-term care for individuals with Alzheimer's and dementias will total $277 billion in 2018. "This grant further validates the promise our genomics research and data analytics capabilities holds for people suffering from this debilitating disease," said IQuity CEO Dr. Chase Spurlock. "IQuity's advances in RNA testing and data science have potential to create predictive diagnostic tools that will lead to an earlier diagnosis of Alzheimer's. New therapies that emerge for Alzheimer's will be most effective when administered early, which is difficult with today's diagnostic approach." IQuity has received four grants totaling $2.62 million from the NIH through its Small Business Innovation Research (SBIR) program, one of the country's largest sources of early-stage capital for technology commercialization. Each grant is awarded through an intensive peer review process. "All of us at IQuity are excited and honored that the NIH supports our approach to developing innovative technology that can facilitate early detection and treatment responses for people affected by Alzheimer's," said Spurlock. "We are proud to be part of a global community of researchers and data scientists who are committed to discovering new early detection methods, prevention plans, treatments and, hopefully, a cure for Alzheimer's." About IQuity:
IQuity is a data analytics company leveraging machine learning to predict, detect, monitor, and stratify severity of disease for healthcare stakeholders, thereby improving patient outcomes and lowering costs. We bring value by automating the process of creating tailored models for disease management at scale, resulting in a collection of comprehensive customer insights and data science approaches to solve complex problems. For more information, visit iquity.com and find IQuity on Facebook and Twitter at @iquityinc. About the National Institute on Aging:
The NIA leads the federal government effort conducting and supporting research on aging and the health and well-being of older people. The Institute's broad scientific program seeks to understand the nature of aging and to extend the healthy, active years of life. For more information on research, aging, and health, go to the NIA website at https://www.nia.nih.gov/ . CONTACT:

NIH Awards IQuity $320K Grant to Identify Alzheimer's Disease Early

NEW YORK (GenomeWeb) — IQuity said today it has received a $320,000 grant from the National Institutes of Health to develop its data analytics technology for use in diagnosing Alzheimer's disease. Nashville-based IQuity's technology uses RNA expression data to predict, detect, and monitor disease, as well as stratify patients by severity of disease. The firm currently offers tests for multiple sclerosis and fibromyalgia, and for differentiating irritable bowel syndrome from inflammatory bowel diseases, through its CLIA lab. To read the full story....

IQuity Wins $320K NIH Grant to Develop Alzheimer's Diagnostic Tech

Diatherix Laboratories provides clinical laboratory services on a multiplexing platform for the detection of infectious diseases. The testing is based upon molecular differential diagnostics (MDD) for the identification of DNA/RNA for bacteria and viruses. The primary area of focus in infectious disease includes pathogens associated with respiratory infections, Staphylococcus differentiation including MRSA and healthcare associated infections (HAI).

Diatherix

This strategic partnership presents Diatherix , which carries both CAP-accreditation and high-complexity CLIA certification , with the opportunity to incorporate new product offerings supported by IQuity Labs 's proprietary results algorithm .

IQuity Labs Enters Into Strategic Partnership With Diatherix Laboratories

IQuity Labs

Nashville Entrepreneur Center

Vanderbilt University

XOi Technologies

Launch Tennessee

Change Healthcare

Morgan Stanley

Decode Health is a company that utilizes AI and analytics in the healthcare sector. The company provides a platform for healthcare teams to implement machine learning and advanced analytics projects aimed at disease detection, monitoring, and treatment. Decode Health works with the pharmaceutical, diagnostic, and technology sectors within the life sciences industry. It is based in Nashville, Tennessee.

Date	Round	Amount	Investors	Valuation Valuations are submitted by companies, mined from state filings or news, provided by VentureSource, or based on a comparables valuation model.	Revenue	Sources
5/17/2017	Seed - II	$2.35M	Undisclosed Investors	$XXM	0 FY undefined	2
10/16/2015	Seed	$XXM	Subscribe to see more	$XXM	0 FY undefined	10

Date	5/17/2017	10/16/2015
Round	Seed - II	Seed
Amount	$2.35M	$XXM
Investors	Undisclosed Investors	Subscribe to see more
Valuation	$XXM	$XXM
Revenue	0 FY undefined	0 FY undefined
Sources	2	10

Date	1/1/2019
Exit	Spinoff / Spinout
Companies	Decode Health
Valuation	$XXM
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