nference and the Bill & Melinda Gates Foundation Enter Into Multi-Year Collaboration to Advance Health Equity

nference has been featured in major publications including Bloomberg, New York Times and Scientific America. For media inquiries contact media@nference.net

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nference’s federated AI platform is being leveraged to provide access to the deepest clinical data to generate insights and better inform decision-making

nference, a company dedicated to transforming healthcare by making biomedical data computable, today announced a multi-year licensing agreement with the Bill & Melinda Gates Foundation. This collaboration provides the Gates Foundation access to nference's nSights platform, where researchers can access a repository of extensive clinical data and expertise from top-ranked medical institutions. 

The nSights platform, leveraging nference’s federated network, will provide resources to help the Gates Foundation more easily visualize and investigate pressing issues affecting world health today. The platform offers data-driven insights to help research teams learn more about healthcare, diseases, and treatments relevant to the Foundation’s interests. This knowledge will contribute to informed decision-making and the development of impactful treatments.

"At the heart of this collaboration lies our commitment to supporting humanitarian causes with our cutting-edge technology platform, driving near-term tangible impact in health equity,” said Maulik Nanavaty, President of Ventures at nference & CEO at Anumana. “Through access to nference’s federated AI – with its depth of multimodal and unprecedented longitudinal data – we aim to accelerate the contribution of modern and innovative healthcare solutions on a global scale.”

nference is unlocking the potential of healthcare data with AI, delivering real-world evidence, insights, and solutions informed by the most comprehensive multimodal data across all therapeutic areas. Our extensive de-identified, longitudinal data includes decades of clinical notes along with rich patient histories, vitals, lab tests, radiology images, digital pathology, genomics, and electrophysiology waveforms. Our federated data platform, comprised of premier healthcare organizations, including Mayo Clinic, Duke Health, Banner Health, Vanderbilt University Medical Center, and Emory Healthcare, enables advanced research and custom AI model development. With unprecedented access to data from over 40 million patient journeys, our partners can accelerate target discovery, optimize clinical trial design, and enhance lifecycle management. Follow nference on LinkedIn. Visit us at www.nference.com.

About the Bill & Melinda Gates Foundation

The Bill & Melinda Gates Foundation is a nonprofit fighting poverty, disease, and inequity around the world. For over 20 years, the Bill & Melinda Gates Foundation has been committed to tackling the greatest inequities in our world. It focuses on improving people's health and giving them the chance to lift themselves out of hunger and extreme poverty. Based in Seattle, Washington, the foundation is led by CEO Mark Suzman, under the direction of Co-chairs Bill Gates and Melinda French Gates and the board of trustees. https://www.gatesfoundation.org/

nference Announces Multi-Year Funding from Global Foundation to Advance Health Equity

Based on pioneering research from Mayo Clinic, ECG-AI LEF aims to aid physicians in identifying low ejection fraction in patients at risk of heart failure.

CAMBRIDGE, Mass. – Oct. 2, 2023 – Anumana, Inc., a leading AI-driven health technology and nference portfolio company working in collaboration with Mayo Clinic, today announced U.S. Food and Drug Administration (FDA) 510(k) clearance for ECG-AI LEF, a breakthrough artificial intelligence (AI)-powered medical device to detect low ejection fraction (LEF) in patients at risk of heart failure.

LEF, or a weak heart pump, is a significant, at times asymptomatic, and commonly undiagnosed indicator of heart failure.1 The increasing prevalence of heart failure and its associated morbidity, mortality, rehospitalizations, and societal costs2,3 underscores the need to identify and manage patients with LEF.

“Anumana’s ECG-AI LEF fills an important unmet need – the lack of an easily accessible point-of-care, noninvasive, and inexpensive tool to screen for a weak heart pump,” said Paul Friedman, M.D., chair of the Department of Cardiovascular Medicine at Mayo Clinic in Rochester, Minn. and chair of Anumana’s Board of Advisors. “It allows identification of otherwise hidden disease, for which many effective, lifesaving treatments are available – once the presence of the disease is known.”

Developed in partnership with Mayo Clinic, Anumana’s ECG-AI LEF is an innovative software-as-a-medical device (SaMD) designed to screen for LEF in adults at risk for heart failure using data from a routine 12-lead electrocardiogram (ECG), a rapid and common test used in both primary and specialty care. Based on pioneering research from Mayo Clinic,4 the algorithm has been developed utilizing over 100,000 ECG and echocardiogram data pairs from unique patients and has been clinically tested in more than 25 studies involving more than 40,000 patients in the U.S. and internationally.5

Anumana’s ECG-AI LEF was clinically validated in a multi-site, retrospective clinical study of 16,000 racially diverse patients, achieving its primary endpoint with an 84.5% sensitivity and 83.6% specificity.6 ECG-AI LEF achieved an AUROC7 of 0.932, demonstrating an ability to differentiate between LEF and ejection fraction (EF) >40% extremely well (a score ≥0.90 is considered excellent8) and better than most tests currently used in heart failure standard of care.9

Additionally, the EAGLE study, a groundbreaking prospective, randomized, controlled clinical trial by Mayo Clinic evaluated the use of an investigational version of the algorithm in routine clinical care of 22,641 adults by 120 primary care teams from 45 clinics or hospitals, demonstrating that ECG-AI LEF implementation improved clinician’s ability to diagnosis of LEF by 31% versus standard of care without increasing the overall rate of echocardiogram usage.10

ECG-AI LEF is one of Anumana’s broad pipeline of algorithms, including three additional FDA breakthrough device designation algorithms (pulmonary hypertension, cardiac amyloidosis, and hyperkalemia), and is founded on more than six years of pioneering ECG-AI research and development at Mayo Clinic, including nearly 100 peer-reviewed publications to date.

“Anumana was established in 2021 by nference in partnership with Mayo Clinic to unlock the electrical language of the heart through deep learning and improve disease diagnosis and patient care,” said Murali Aravamudan, co-founder and CEO of Anumana and nference. “In the short time of two years we have secured multiple FDA breakthrough device designations, entered multi-year agreements with three pharma partners, successfully established two new medical procedure codes for ECG AI technology, and now achieved our first FDA breakthrough medical device clearance. This is a significant milestone, and we are excited about the next phase of the journey, deploying our technology in the U.S. and globally to empower clinicians and enhance real-world clinical care.”

Anumana is focused on driving fast-paced adoption of the new ECG-AI category, clinically developing and commercializing its novel technologies in healthcare. The newly FDA-cleared ECG-AI LEF can be easily integrated with various ECG information management systems or directly with a patient’s electronic health record via Anumana’s web-based ECG Viewer to support clinical decision-making.

Anumana spearheaded the effort to bring reimbursement to ECG-AI, receiving approval for two Category III CPT® codes from the American Medical Association in 2022. These codes are now available and designed to facilitate the use, adoption, and potential reimbursement of emerging technologies in clinical workflows.

To learn more about ECG-AI LEF and schedule a demo, visit us at ECG-AI LEF.

Anumana is a leading AI-driven health technology company leveraging cutting-edge AI and industry-leading translational science to unlock the electrical language of the heart as never before. The company was founded by nference in partnership with Mayo Clinic to leverage the clinical and technical expertise of both organizations to develop innovative ECG-AI technology from an investigational resource to a clinically meaningful tool for clinicians to advance patient care. Anumana’s software-as-a-medical device (SaMD) solutions aim to detect hidden diseases using ECG-AI algorithms to enhance and improve interventional procedures through real-time AI insights.

Anumana was named one of Fierce MedTech’s Fierce 15 companies for 2022. Follow Anumana at anumana.ai and on LinkedIn and Twitter.

Dr. Friedman and Mayo Clinic have a financial interest in the technology referenced in this press release. Mayo Clinic will use any revenue it receives to support its not-for-profit mission in patient care, education, and research.

1.     Jaskanwal D Sara, Takumi Toya, Riad Taher, Amir Lerman, Bernard J Gersh, Nandan S Anavekar. Asymptomatic Left Ventricle Systolic Dysfunction. European Cardiology Review 2020, 15:e13; https://doi.org/10.15420/ecr.2019.14.

2.     Tsao, C.W., Aday, A.W., Almarzooq Z.I., et al. Heart Disease and Stroke Statistics—2023 Update: A Report From the American Heart Association. Circulation Vol. 147, No. 8; https://www.ahajournals.org/doi/10.1161/CIR.0000000000001123#d330256e1.

3.     Khazanie P, Allen LA. Systematizing Heart Failure Population Health. Heart Fail Clin. 2020 Oct;16(4):457-466. Doi: 10.1016/j.hfc.2020.06.006. Epub 2020 Jul 21. PMID: 32888640; PMCID: PMC7737815; https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7737815/.

4.     Attia, Z.I., Kapa, S., Lopez-Jimenez, F. et al. Screening for cardiac contractile dysfunction using an artificial intelligence–enabled electrocardiogram. Nat Med 25, 70–74 (2019); https://doi.org/10.1038/s41591-018-0240-2.

5.     Anumana data on file and published studies.

6.     Anumana data on file (NCT04963218).

7.     Area Under the Receiving Operating Characteristic curve (AUROC) is a performance metric commonly used to evaluate the ability of a model to distinguish between two classes. An AUROC of 0.5 suggests that the model is no better than random and an AUROC of 1.0 indicates a perfect classifier; https://en.wikipedia.org/wiki/Receiver_operating_characteristic.

8.     Muller MP, Tomlinson G, Marrie TJ, Tang P, McGeer A, Low DE, et al. Can routine laboratory tests discriminate between severe acute respiratory syndrome and other causes of community-acquired pneumonia? Clin Infect Dis. 40:1079–86 (2005); https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8831439/.

9.     Such as NT-proBNP, a common blood test used to help identify LEF today with an AUROC of 0.83; Koschack, J., Scherer, M., Lüers, C. et al. Natriuretic peptide vs. clinical information for diagnosis of left ventricular systolic dysfunction in primary care. BMC Fam Pract 9, 14 (2008); https://doi.org/10.1186/1471-2296-9-14h.

10.   Yao, X., Rushlow, D.R., Inselman, J.W. et al. Artificial intelligence–enabled electrocardiograms for identification of patients with low ejection fraction: a pragmatic, randomized clinical trial. Nat Med 27, 815–819 (2021); https://doi.org/10.1038/s41591-021-01335-4.

Pazanga Health Communications for Anumana

Anumana Receives U.S. FDA 510(k) Clearance for ECG-AI Algorithm to Detect Low Ejection Fraction

Banner Health and nference, a science-first software company transforming healthcare by making biomedical data computable, today announced a partnership to accelerate scientific discovery to improve treatment, diagnosis, and care.

CAMBRIDGE, Mass., Aug. 22, 2023 – Banner Health and nference, a science-first software company transforming healthcare by making biomedical data computable, today announced a partnership to accelerate scientific discovery to improve treatment, diagnosis, and care.

By incorporating nference’s state-of-the-art analytics capabilities, Banner Health and its researchers can gain valuable insight into diseases and treatments, adapting the practice of medicine to meet the needs of its communities. 

“We’re excited to embark on this innovative partnership that will unlock the insights from our data to further personalize the ways we deliver care to our patients,” said Scott Nordlund, Executive Vice President Chief Strategy and Growth Officer at Banner Health. “This partnership will support our own efforts to improve the care patients receive in our diverse clinical settings and benefit other researchers with global impact on diagnosis and treatment.” 

nference’s Federated Analytics Platform enables researchers and clinicians to derive meaningful insights from proprietary longitudinal clinical datasets, transforming discovery and accelerating development while preserving patient privacy. The platform provides insights from the deepest, de-identified, multimodal (electronic health record, imaging, electrocardiogram) dataset available across therapeutic areas. These include cardiology, oncology, immunology, neuroscience, metabolic diseases, and infectious diseases by leveraging the company’s Federated AI network.

“Our collaboration with Banner Health is an exciting addition to our unique federated network,” said Murali Aravamudan, co-founder and CEO of nference. “Banner Health brings comprehensive, multimodal data from a geographically and ethnically diverse patient population to our network that will provide more potent insight generation, offering researchers the option to examine more inclusive data.”

nference’s agreement with Banner Health builds on recent collaborations with other leading academic medical centers, accelerating nference’s mission to expand its federated network, which is scalable and structured to encourage and facilitate collaboration among healthcare systems and biopharmaceutical researchers.

Through its powerful technology platform and software, nference is transforming healthcare by making biomedical knowledge computable. Its partnerships with major academic medical centers empower nference to synthesize decades of institutional knowledge, producing real-world evidence (RWE) in real time by converting large amounts of de-identified data into deep insights to advance discovery and development of diagnostics and therapeutics. Its proprietary AI-enabled software platform, nSights, harnesses the power of federated learning to accelerate life sciences research, development, and clinical care in significant ways, including biomarker discovery and validation, RWE generation leveraging real-world data, early disease detection, public health policy generation and validation, and more. nference is headquartered in Cambridge, Mass. Follow nference on LinkedIn and Twitter. Visit us at www.nference.com.

Banner Health is one of the largest, secular nonprofit health care systems in the country. In addition to 30 acute-care hospitals, Banner also operates an academic medicine division, Banner – University Medicine, and Banner MD Anderson Cancer Center, a partnership with one of the world’s leading cancer programs, MD Anderson Cancer Center. Banner’s array of services includes a health insurance division, employed physician groups, outpatient surgery centers, urgent care locations, home care and hospice services, retail pharmacies, stand-alone imaging centers, physical therapy and rehabilitation, behavioral health services, a research division and a nursing registry. To make health care easier, 100% of Banner-employed doctors are available for virtual visits and patients may also reserve spots at Banner Urgent Care locations and can book appointments online with many Banner-employed doctors. Headquartered in Arizona, Banner Health also has locations in California, Colorado, Nebraska, Nevada and Wyoming. For more information, visit bannerhealth.com.

Andrea Sampson, Sampson Public Relations Group

Banner Health Partners with nference to Accelerate Scientific Discovery for Patient Care

Anumana acquires NeuTrace, a medical technology company advancing novel in-procedure AI applications for Electrophysiology (EP)

CAMBRIDGE, Mass., Nov. 7, 2022 – Anumana, an AI-driven health technology company and portfolio company of nference, announced today it has acquired NeuTrace, a medical technology company advancing novel in-procedure AI applications for electrophysiology (EP). The acquisition includes the NeuTrace EP Data Biome platform and a portfolio of AI-enabled EP software applications in development. As part of the transaction, nference acquired rights to the Data Biome platform for uses outside of the cardiovascular field.

The acquisition positions Anumana as a leader in AI medical software development for cardiac electrophysiology, with a combined development capability - powered by nference’s nSights real world evidence generation platform - that can integrate a patient’s entire electronic medical record (EMR) with corresponding electrocardiograms (ECG) taken from the surface of the body and cardiac electrograms (EGM) taken from within the heart.

Rooted in deep data science and covered by more than 35 pending and registered patents, the NeuTrace EP Data Biome is a proprietary and device-agnostic platform for holistic in-procedure data integration and novel real-time AI applications. A portfolio of EP applications is under development with the potential to increase procedure accuracy, reduce procedure time, and improve patient safety and outcomes. Advanced deep learning techniques on in-procedure EGM and ECG data feeds, combined with pre- and post-procedure ECG and EMR data records, will enable new and improved ECG-AI based diagnostic and pre-diagnostic algorithms for early disease detection and treatment.

“Anumana is pioneering new ground in cardiology AI software solutions that span the entire patient journey,” said David McMullin, chief business officer of Anumana. “With its deep learning models detecting patterns too subtle for the human eye to see, from undiagnosed disease in routine ECGs to real-time EGM signals during critical EP procedures, Anumana is on a mission to improve patient care by unlocking the electrical language of the heart as never before.”

“We’ve been impressed by the complementary depth, breadth, and strength of the Anumana and nference teams and are excited by the transformative potential of the combined organizations,” said Srijoy Mahapatra, M.D., president and chief operating officer of NeuTrace. “Combining the power of NeuTrace’s EP Data Biome with EMR and other data modalities of nference’s nSights platform has the potential to unlock game-changing AI applications in early cardiovascular disease detection, rhythm management, and EP procedure safety, efficacy, and effectiveness, for improved long-term outcomes.”

"NeuTrace promises to significantly improve care through applied AI in both expert and non-expert EP labs,” said Pierre Jais, M.D., LYRC-Bordeaux and NeuTrace medical advisor. “As new tools come on-line in the EP lab, we will need artificial intelligence more than ever. By pairing these intraprocedural data with ECGs and full medical records, Anumana has the opportunity for AI-tailored recommendations patient-by-patient, which would be true precision medicine.”

"Electrophysiology and other cardiology procedures are extremely rich in data that has largely remained untapped when it comes to machine learning and deep learning techniques,” said K. Shivkumar, M.D., Ph.D., Director of UCLA Cardiac Arrhythmia Center & Interventional Cardiovascular Programs.* “The techniques and products that Anumana and nference are developing, especially when integrated with NeuTrace’s in-procedure technology, are groundbreaking not only in cardiology, but also when applied to other organs such as the brain and kidney. I look forward to the next-gen technologies that Anumana and nference’s combination with NeuTrace will produce.”

NeuTrace was founded by Dr. K.Shivkumar and his colleagues, and molded with the business vision and guidance from Raghu Mendu and NC Murthy, along with leading AI/ML and Data technology experts. NeuTrace’s mission is to democratize clinical practice, starting with cardiac electrophysiology, by applying its agnostic technology platform and AI in clinical procedures, to greatly improve the efficiency, effectiveness, and safety of patient care and outcomes.

Anumana, an AI-driven health technology company and portfolio company of nference and Mayo Clinic Platform, is harnessing industry-leading AI and translational science to unlock the electrical language of the heart as never before. Anumana algorithms have been developed, trained, and validated using clinical data from Mayo Clinic and other leading institutions to detect hidden diseases using ECG-AI and enhance and improve EP procedures through real-time AI techniques. Multiple Anumana algorithms have received FDA Breakthrough Device Designation and are currently undergoing rigorous clinical trial validation. Anumana software devices are designed for real-world physician use, integrating into existing workflows at the point-of-care, thereby reducing costs and enhancing quality of life. Anumana algorithms are investigational medical devices and have not yet received regulatory approval or clearance. For more information, visit anumana.ai and follow Anumana on LinkedIn and Twitter.

Through its powerful technology platform and software, nference is transforming health care by making biomedical knowledge computable. Its partnership with Mayo Clinic and other renowned academic medical centers has given nference an opportunity to synthesize decades of institutional knowledge, producing real-world evidence in real-time by converting large amounts of de-identified data into deep insights to advance discovery and development of diagnostics and therapeutics. Its proprietary AI-enabled software platform, nSights, has been used to accelerate life sciences research, development, and clinical care in significant ways, including biomarker discovery and validation, real-world evidence generation leveraging real-world data, early disease detection, public health policy generation and validation, and more. For more information, visit www.nference.com and follow nference on LinkedIn and Twitter.

*Dr. Shivkumar is a founder of NeuTrace, and the views expressed by him are his own and do not represent the views of UCLA.

Anumana Acquires NeuTrace, Establishing a Comprehensive Electrophysiology Deep-Learning Development Platform and Product Pipeline

nference co-founder and chief scientific officer discusses a novel approach to assessing variants of concern regionally with CBS News.

How is the BA.5 COVID-19 variant different from other strains?

Duke Health has teamed up with nference to utilize the software company’s analytics platform to bolster medical research and patient care.

Duke Health partners with nference to reveal EHR insights, improve care

A retrospective comparative study confirmed that both vaccines provide strong protection against symptomatic SARS-CoV-2 infection.

CAMBRIDGE, Mass., Dec. 15, 2021 /PRNewswire/ -- nference, the AI-driven health technology company, announced today publication of a peer-reviewed study in Med that analyzed Mayo Clinic based data with nference artificial intelligence (AI) software to determine that both the Moderna and Pfizer/BioNTech vaccines were over 70% effective at preventing symptomatic COVID-19 between December 2020 and September 2021, including periods of Alpha and Delta variants of concern circulation.

The authors of "Comparative effectiveness of mRNA-1273 and BNT162b2 against symptomatic SARS-CoV-2 infection" used a test-negative case-control design to assess the odds of symptomatic infection after full vaccination against COVID-19 with either mRNA-1273 (the Moderna vaccine) or BNT162b2 (the Pfizer/BioNTech vaccine).

The data from Minnesota, Wisconsin, Arizona, Iowa and Florida was retrospectively collected at Mayo Clinic between December 2020 and September 2021, and retrospectively reviewed to examine the ongoing real-world effectiveness of each vaccine. The results indicated that over the whole study duration, the Moderna and Pfizer/BioNTech vaccines were 84% and 76% effective against symptomatic COVID-19, respectively. Their effectiveness was lower during the recent Delta variant-dominated months, but both vaccines have continued to offer strong protection against symptomatic disease in this period, with effectiveness estimates of 76% and 64%, respectively. The authors note that the reduced effectiveness in later months could be due to less efficient neutralization of the Delta variant, waning of vaccine-elicited immunity over time, changes in nonpharmaceutical interventions (e.g., masking policies, physical distancing, and travel restrictions), or a combination of these factors.

Med is Cell Press's flagship medical journal, improving global health and facilitating the exchange of knowledge and ideas among researchers, clinicians, biotech and pharma scientists, and health policy experts.

"This study further supports the effectiveness of both mRNA vaccines in preventing COVID-19 despite the evolution  and spread of multiple variants of concern during the study period," said AJ Venkatakrishnan, PhD, Vice President of Scientific Research at nference and co-author of the study.

The innovative and powerful AI technology implemented by nference during the COVID-19 pandemic has enabled discoveries with a wide range of implications that contribute to a greater understanding of the virus, which are ultimately advancing patient care.

Comparative effectiveness of mRNA-1273 and BNT162b2 against symptomatic SARS-CoV-2 infection

Duke Health has partnered with data analytics company nference to advance the academic health system's research and medical discoveries.

Durham, N.C.-based Duke Health has partnered with data analytics company Nference to advance the academic health system's research and medical discoveries.

Nference has previously collaborated with Rochester, Minn.-based Mayo Clinic on artificial intelligence-powered disease diagnosis and treatment and received funding from its venture capital arm, Mayo Clinic Ventures.

"The average time for life-saving research to get from the bench to bedside, and then to our communities, can take up to 17 years," said Jeffrey Ferranti, MD, senior vice president and chief digital officer of Duke Health, in a joint Jan. 4 news release. "During this time many patients miss out on access to next-generation cures, and we have a responsibility to lead in bringing these cures to patients faster."

The two entities said the collaboration will grow and evolve in the coming years.

Duke Health, Nference partner on analytics research, medical discoveries

EHR data verifies the Ad26.COV2.S vaccine – known publicly as the Johnson and Johnson COVID-19 vaccine – was over 73 percent effective against SARS-CoV-2 infections during the first five months after initial rollout.

CAMBRIDGE, Mass., November 2, 2021 –– nference, the AI-driven health technology company, today announced publication of a study in JAMA Network Open that analyzed Mayo Clinic data with nference augmented intelligence (AI) software to determine that the Ad26.COV2.S vaccine was over 73 percent effective at reducing the spread of SARS-CoV-2 during the study period (February to July, 2021).

Authors of “Analysis of the Effectiveness of the Ad26.COV2.S Adenoviral Vector Vaccine for Preventing COVID-19” conducted a preliminary assessment of the effectiveness of the Ad26.COV2.S vaccine based on the electronic health record (EHR) data of 8,889 vaccinated patients and 88,898 unvaccinated patients. The data was captured by the Mayo Clinic between February 27 and July 22, 2021 and was used to establish a retrospective baseline for the vaccine’s efficacy. The results show that the Ad26.COV2.S vaccine’s overall effectiveness was 73.6 percent and that the Ad26.COV2.S facilitated a 3.73-fold reduction in SARS-CoV-2 infections during this time period.

JAMA Network Open is an open access medical journal published by the American Medical Association and covering all aspects of the biomedical sciences.

“As COVID-19 vaccinations continue to be administered more broadly, it has become critical for researchers and scientists to continuously assess the safety and effectiveness data for each of the vaccines,” said Tyler Wagner, PhD, vice president of biomedical research at nference. “Using nference’s state-of-the-art AI technology, we were able to quickly and accurately process and analyze the data collected by our partners at the Mayo Clinic, and these findings conclude that the Ad26.COV2.S vaccine was effective against the spread of SARS-CoV-2 during the study period.”

In the process of conducting this study, nference employed its leading-edge augmented intelligence software, nferX™, which uses proprietary natural language processing technology to rapidly synthesize vast amounts of biomedical data from disparate sources in previously incompatible formats. nference’s real-time software will continue to monitor and enable rapid up-to-date safety assessments of vaccines as new and updated patient information becomes available. A follow-on study examining the durability of the Ad26.COV2.S vaccine with the Delta variant will be forthcoming. 

This innovative, powerful augmented intelligence technology implemented by nference during the COVID-19 pandemic has enabled several significant discoveries with a wide range of implications that contribute to a greater understanding of the virus, which are ultimately advancing patient care. 

Through its powerful augmented intelligence software nferX®, nference is transforming health care by making biomedical knowledge computable. Its partnership with Mayo Clinic has given nference an opportunity to synthesize more than 100 years of institutional knowledge, producing real-world evidence in real time by converting large amounts of data into deep insights to advance discovery and development of diagnostics and therapeutics. nference is headquartered in Cambridge, Massachusetts. Follow nference on LinkedIn and Twitter. Visit us at nference.ai.

nference and Mayo Clinic Study Confirms Efficacy of Ad26.COV2.S Vaccine in Reducing COVID-19 Infections

Mayo Clinic has expanded its relationship with artificial intelligence-driven health tech company Nference to use deidentified patient data to help research and discover disease diagnoses and treatments.

Rochester, Minn.-based Mayo Clinic has expanded its relationship with artificial intelligence-driven health tech company Nference to use deidentified patient data to help research and discover disease diagnoses and treatments.

As part of the project, the academic health system's data analytics hub, Mayo Clinic Platform, has launched its own version of Nference's nSights platform, called Mayo Clinic Platform_Discover. The project will allow biotech, medical device and diagnostic companies access to the EHR data, which Mayo notes is anonymous and never leaves its system.

"Over the past year, our collaboration with Nference, leveraging nSights, has accelerated clinical decision support and care in significant ways," Mayo Clinic Platform COO Maneesh Goyal said in a Sept. 21 health system news release. "Data-derived insights and knowledge help us accelerate and enhance innovation and meet the unmet needs of patients everywhere."

Mayo Clinic expands partnership with AI firm on disease diagnosis, treatment discovery

New company to create and commercialize innovative digital sensor diagnostics.

Mayo Clinic and AI-driven health technology company nference launched Anumana, Inc.™ to create and commercialize innovative digital sensor diagnostics by harnessing industry-leading AI and clinically-driven insights that decipher electrocardiograms (ECGs) in ways never before possible. Anumana will initially focus on designing and bringing to market state-of-the-art neural network algorithms based on billions of relevant pieces of heart health data in Mayo Clinic's Clinical Data Analytics Platform, including millions of raw ECG signals, unlocking hidden biomedical knowledge aimed at enabling early detection of heart disease and accelerating treatments. Anumana makes it possible to see signs of illness that were once invisible and predict disease before specific symptoms appear, empowering healthcare providers, accelerating patient treatments, reducing costs and enhancing quality of life.

“Signs of illness are often invisible, even to the most trained eye. Now, for the first time, we will make it possible to see them,” said Murali Aravamudan, CEO of nference and Anumana. “Our deep learning neural networks, in the hands of scientific and clinical experts, will enable a comprehensive translation of the language of the heart. We think of it as the Rosetta Stone for cardiac medicine.”

Mayo Clinic and nference Launch Anumana, Inc. to Develop Novel Artificial Intelligence Algorithms that Advance Disease Diagnostics and Prediction

Michael Pencina, PhD, has been named the inaugural chief data scientist of Duke Health in Durham, NC. His role will focus on advancing AI in healthcare and leveraging partnerships with Microsoft and Nference.

Duke Health's 1st chief data scientist to focus on AI

nference has been named to Fast Company’s prestigious annual list of the 2023 World’s Most Innovative Companies for its AI-driven software platform delivering insights to accelerate development of therapeutics and diagnostics for life sciences companies.

nference Named to Fast Company’s Annual List of the World’s Most Innovative Companies for 2023

The Duke University Health System and School of Medicine partnered with Nference, a biotechnology software company, to launch a precision medicine study called OneDukeGen.

Duke, nference partner on precision medicine study

Robert Groebel, vice president at software company nference, provides an Expert View on the value of federated AI in ensuring achievement of critical milestones, accelerated time to market and delivery of improved patient outcomes.

Data-driven clinical trials: the value of federated data networks

Duke Health is building upon its longstanding history of innovative research by joining with nference, a science-first software company, to transform healthcare by making biomedical knowledge computable.

Duke Health Joins with nference to Advance Medical Research and Patient Care

Agreement deepens access to diverse, high-quality, longitudinal clinical data for research across multiple areas, including cardiovascular, pulmonary, and oncology

Agreement deepens access to diverse, high-quality, longitudinal clinical data for research across multiple areas, including cardiovascular, pulmonary, and oncology.

nference and Vanderbilt University Medical Center Sign Agreement to Advance Real-World Evidence Generation in Complex Disease Populations

A partnership between Banner Health and nference will offer more 'potent insights generation, offering researchers the option to examine more inclusive data'.

Banner Health partners with nference offering potent insights to further personalize patient care

Banner Health partnered with Nference, a biotechnology software company, for better access to analytics focused on driving scientific discoveries to improve treatment, diagnosis and care.

How Banner Health is adapting patient care using analytics

Physicians and researchers, working with external partners such as Google, nference and others, have used vast data resources to develop algorithms that help predict and identify early cardiovascular disease, breast cancer, pancreatic cancer, neuromuscular disease and anxiety/depression with the goal of changing the course of the disease for individual patients.

Mayo Clinic President and CEO discusses the importance of nference and Anumana's work in transforming healthcare at the World Economic Forum '22

Novartis Pharmaceuticals Corporation to collaborate on development of new medical device software for earlier detection and intervention in cardiovascular disease.

Anumana Collaborates with Leading Global Health Care Company to Detect Heart Disease Using Artificial Intelligence

Companies initiate research agreement supporting development of new AI-ECG algorithm to help identify patients who may be at risk of cardiac amyloidosis

Companies initiate research agreement supporting development of new AI-ECG algorithm to help identify patients who may be at risk of cardiac amyloidosis

Anumana, Inc., an AI-driven health technology company and portfolio company of nference, has entered into a multi-year agreement with Pfizer, Inc. for Anumana to develop an artificial intelligence electrocardiogram algorithm (AI-ECG) designed to enable the early suspicion of cardiac amyloidosis. Anumana will conduct a clinical validation trial and pursue De Novo classification for the algorithm as a Software-as-a-Medical-Device (SaMD) and aims to gain regulatory approval for the algorithm as an SaMD for the detection of cardiac amyloidosis in the U.S., Europe and Japan.

Cardiac amyloidosis is a serious, progressive, and underdiagnosed rare disease that leads to heart failure.1 In patients with cardiac amyloidosis, the heart walls become stiff, making it difficult for the left ventricle to properly relax and fill with blood, while at the same time hampering its ability to squeeze and pump blood out of the heart. Symptoms and comorbidities associated with cardiac amyloidosis, such as shortness of breath, knee pain, bilateral carpal tunnel syndrome, kidney disease, and gastrointestinal issues, can vary and seem unrelated, making diagnosis difficult.2,3

“The challenge in diagnosing cardiac amyloidosis can prevent patients from getting treatment while the disease continues to progress,” said David McMullin, chief business officer of Anumana. “We believe this collaboration will demonstrate the power of Anumana’s AI-ECG algorithms to help clinicians intervene earlier, giving them greater ability to improve patient outcomes and prolong lives.”

The research agreement with Pfizer will help deepen Anumana’s efforts to implement AI-enabled early detection software that can reveal signals from ECGs that humans cannot interpret. The ubiquitous nature of the painless, non-invasive 100-year-old ECG test gives AI-ECG algorithms the potential to reach a larger number of patients earlier.

“AI-ECG solutions alert clinicians to humanly imperceptible patterns in ECG signals, providing an early warning for serious occult or impending disease,” said Paul Friedman, M.D., Chair of the Department of Cardiovascular Medicine at Mayo Clinic and Chair of Anumana’s Mayo Clinic Board of Advisors. “This stands to improve the lives of people with cardiac amyloidosis by improving the speed of triage and care of this group.”

Anumana was founded in 2021 in collaboration with the Mayo Clinic Platform. Anumana has licensed Mayo Clinic AI-ECG algorithms for low ejection fraction, pulmonary hypertension, and hyperkalemia, all of which have received Breakthrough Device Designation from the U.S. FDA. These algorithms have been validated by over 75 peer-reviewed publications, including a first of its kind prospective clinical impact study on low ventricular ejection fraction that was published in Nature Medicine in 2021, and another first of its kind batch enrolled prospective clinical impact study that demonstrated the effectiveness of AI-ECG to screen for undetected atrial fibrillation in normal sinus rhythm that was published in The Lancet in 2022.

Anumana and Pfizer Partner to Enable Early Detection of Underdiagnosed Cardiovascular Disease

Joint efforts will deepen clinical insights across a spectrum of research, diagnoses, and treatment areas

nference and Emory Healthcare Collaborate, Adding Another Top-Ranked Medical Center to Federated Data Network

Collaboration Brings DICOM, AI, Image Analysis, and Digital Pathology in Single, Streamlined, Comprehensive Offering.

Gestalt and Pramana Announce Availability of Integrated Digital Pathology Solutions and AI-Powered Platform

nference is the sole founding partner of a new initiative aimed at joining viral sequencing with electronic health records to prepare for the next pandemic

A machine learning company pitches its plan to get ahead of the next pandemic

nference researchers introduced a new approach to viewing viral evolution that could help predict whether and when a new coronavirus variant is likely to outcompete currently dominant versions.

Impact of coronavirus variants is location-dependent

Published in PNAS Nexus, this study has the ability to impact future research and inform more proactive and sustainable pandemic preparedness.

nference and the NIH Identify Which Mutations Enable Highly Transmissible Viruses, Like SARS-CoV-2, to Persist in Human Circulation

Developed in collaboration with Janssen and Mayo Clinic, this technology has the potential to aid physicians in earlier detection of pulmonary hypertension, a progressive, life-threatening disease

FDA Grants Breakthrough Device Designation to Anumana’s ECG Pulmonary Hypertension Early Detection AI Algorithm

Funding broadens nference portfolio to accelerate development of novel diagnostics and therapies based on nferX™ software

nference Completes $60M Series C to Accelerate and Expand Augmented Intelligence for Life Sciences

A new crop of companies is reshaping the health data economy

To interpret ECG signals generated from the single lead on an Apple Watch, researchers modified an established 12-lead algorithm for low ventricular ejection fraction — the weak heart pump — that is licensed to Anumana, an nference and Mayo Clinic company.

Mayo researchers leverage Anumana algorithm to detect weak heart pump via patients’ Apple Watch ECGs

The ability to harness vast amounts of health data using advanced AI technology will lead to new discoveries and insights needed to improve patient care.

SUNNYVALE, Calif.--(BUSINESS WIRE)--Cerebras Systems, the pioneer in high performance artificial intelligence (AI) compute, and nference, an AI-driven health technology company, today announced a collaboration to accelerate natural language processing (NLP) for biomedical research and development by orders of magnitude with a Cerebras CS-2 system installed at the nference headquarters in Cambridge, Mass.

The vast amounts of health data that lie within patient records, scientific papers, medical imagery, and genomic databases could be critical to advancing health outcomes. Unfortunately, this information is nearly impossible for data scientists and machine learning (ML) researchers to access, as it exists in unstructured, siloed, and incompatible forms, forcing researchers to sift through it manually. While data accessibility is a fundamental challenge in healthcare today, newer AI architectures such as transformer models can assist by processing data from various sources, de-identifying it, and converting it into structured, usable intelligence.

nference uses transformer AI models to employ self-supervised learning from large volumes of unstructured data without labels, translating vast amounts of health data into information that can be used to discover insights and drive research. However, training large models is complex, computationally intensive, and time-consuming, often requiring large clusters of conventional processors. A key feature of the Cerebras CS-2 architecture is the ability for data scientists and ML researchers to use data of longer sequence lengths than is practical using smaller, conventional processors – this is particularly relevant to research being conducted at nference.

“nference was founded to help solve complex medical problems and improve health outcomes by unlocking insights contained within biomedical data while protecting individual patient privacy,” said Ajit Rajasekharan, Chief Technology Officer, nference. “Our solution uses transformer models to help researchers and clinicians make sense of siloed and inaccessible health data, leading to new discoveries and findings that can impact patient outcomes. With Cerebras’s powerful CS-2 system, we can train transformer models with much longer sequence lengths than we could before, enabling us to iterate more rapidly and build better, more insightful models.”

“AI is driving an exponential increase in demand for compute,” said Andy Hock, Vice President of Product, Cerebras Systems. “As we have recently demonstrated across multiple customers and published work, the Cerebras CS-2 is orders of magnitude faster than legacy alternatives. This orders-of-magnitude performance advantage comes from the Cerebras Wafer Scale Engine (WSE-2), the world’s largest and most powerful AI processor. The WSE-2 is purpose built with 850,000 AI-optimized cores to accelerate the models of today and unlock future models not practical or possible on legacy infrastructure. The partnership and our work with nference is a great example of this, where their team – equipped with a CS-2 – is pushing the boundaries of AI to accelerate biomedical research and discovery to improve health outcomes.”

The Cerebras CS-2 system delivers the deep learning compute performance of hundreds of graphics processing units in a cluster, with the programming ease and efficiency of a single system. Powered by the largest and fastest processor ever built – the 2.6 trillion transistor second-generation Cerebras Wafer-Scale Engine (WSE-2) – the CS-2 delivers more AI-optimized compute cores, fast memory, and fabric bandwidth than any other deep learning processor in existence. A CS-2 delivers the wall-clock compute performance of many tens to hundreds of GPUs with the programming ease and efficiency of a single device.

Through its powerful augmented intelligence software, nference is transforming health care by making biomedical knowledge computable. Our partnership with Mayo Clinic has given us the opportunity to synthesize more than 100 years of institutional knowledge, producing real-world evidence in real time by converting large amounts of data into deep insights to advance discovery and development of diagnostics and therapeutics. nference is headquartered in Cambridge, Mass. Follow nference on LinkedIn and Twitter. Visit us at nference.ai.

nference Accelerates Self-Supervised Language Model Training with Cerebras CS-2 System

Pramana, Inc., an AI-enabled health-tech company modernizing the pathology sector, launched its Digital Pathology as a Service (DPaaS) solution for creating digital pathology repositories and also announced its first commercial agreement. The DPaaS platform offers a first-of-its-kind service to efficiently digitize pathology slides to meet the needs of pathologists, researchers, and clinicians.

CAMBRIDGE, Mass.--(BUSINESS WIRE)--Pramana, Inc., an AI-enabled health-tech company modernizing the pathology sector, launched its Digital Pathology as a Service (DPaaS) solution for creating digital pathology repositories and also announced its first commercial agreement. The DPaaS platform offers a first-of-its-kind service to efficiently digitize pathology slides to meet the needs of pathologists, researchers, and clinicians.

Despite the potential value and impact of digitizing pathology archives, few pathology labs have achieved large scale digital libraries. Due to the vastly different slide preparation methods over the years as well as the deterioration of slides in storage, the highly labor-intensive process often results in poor quality and inconsistent images. Pramana’s vertically integrated solution offers a completely automated means for digitization at scale, enabling significant operational efficiencies by limiting human intervention.

“It is often misconstrued that the challenges with going digital for tissue and body fluid slides end with the purchase of a scanner,” said Prasanth Perugupalli, Chief Product Officer at Pramana. “We realized that the greater pain and costs lie in the human capital needed to operate the scanners, which includes making the correct parametric selections and qualifying each whole slide image for any errors after the scanning is completed. Pramana’s DPaaS solution overcomes these challenges with minimal burden on the labs and delivers quality-assured whole slide images with standardized and open data formats.”

Pramana uses its intelligent whole slide image acquisition system, fed by a robot and analyzed by proprietary algorithms, to achieve 100% real-time, fully automated quality assessment. A single scanning cluster is capable of scanning over 1,000 slides per day, and Pramana can scale up or down efficiently to achieve customer-desired throughput.

Pramana’s first commercial agreement with Mayo Clinic is a multi-year collaboration that includes an industry-leading initiative to digitize 5 million slides – one of the largest digitization efforts in the world to date, at an unprecedented rate.

Pramana will introduce its DPaaS solution at the United States and Canadian Academy of Pathologists (USCAP) Annual Meeting in Los Angeles, March 19–24 (booth #728). For more information or to schedule a meeting with Pramana, contact uscap@pramana.ai.

Pramana, Inc., a health-tech company founded by nference, inc., enables seamless digital adoption by pathology labs and medical centers. Built upon extensive industry experience and patented technological innovation, Pramana is a gateway for pathologists and physicians to utilize AI-enabled decision support. The company is headquartered in Cambridge, Mass., and backed by Matrix Capital, a global leader in customized investment solutions, and NTTVC, a leading firm backing diverse founders within the technology spectrum. For more information, visit www.pramana.ai.

Andrea Sampson, Sampson Public Relations Group 

Pramana Launches Digital Pathology as a Service Platform, Offering Comprehensive and Scalable Glass Slide Digitization for Health Systems

nference, the biomedical technology company, today announced publication in Scientific Reports of a study that analyzes Mayo Clinic data with nference artificial intelligence software and reveals potential cross-protective effects of existing vaccines against Covid-19 infection.

ROCHESTER, Minn. and CAMBRIDGE, Mass., Feb. 26, 2021 /PRNewswire/ -- nference, the biomedical technology company, today announced publication in Scientific Reports of a study that analyzes Mayo Clinic data with nference artificial intelligence software and reveals potential cross-protective effects of existing vaccines against Covid-19 infection. The analysis indicates that individuals who previously received a number of traditional vaccines, such as for polio, measles, and flu, have a reduced risk of testing positive for SARS-CoV-2, likely as a result of "immune training," whereby innate immune cells are retrained so that when they encounter a subsequent challenge they have a more robust response.

Scientific Reports is an online multidisciplinary, open access journal from the publishers of Nature.

"Mayo Clinic and nference researchers applied our technology to produce results that previously would have taken months if done manually," said Venky Soundararajan, PhD, co-founder and chief scientific officer of nference. "What we discovered represents compelling evidence that vaccinations are a critical element in prevention of disease, even diseases one doesn't anticipate. We know now, more than ever, that greater acceptance of inoculations can have enormous health benefits all over the world."

The publication "Exploratory Analysis of Immunization Records Highlights Decreased SARS-CoV-2 Rates in Individuals with Recent Non-COVID-19 Vaccinations'' compares matched pairs of vaccinated and unvaccinated patients using state-of-the-art nference augmented intelligence software. Immunization records were examined of 137,037 patients tested in the Mayo Clinic health system for coronavirus infection. The results indicate that people who received childhood vaccinations for diseases like measles and polio, as well as adult flu shots and other recent vaccinations, have lower coronavirus infection rates than those who had not been similarly vaccinated.

"If you've received a number of different vaccines previously, your risk of having a positive SARS-CoV-2 diagnosis was about 60-to-80 percent of the rate of positive tests in unvaccinated patients," said Andrew Badley, MD, of Mayo Clinic, Enterprise Chair of COVID-19 Task Force. "If you think of your immune system as a muscle, the more often you exercise that muscle, the stronger it is."

New approaches like that of the collaboration between Mayo Clinic and nference are expected by the biomedical community to play an increasingly vital role in advancing diagnostic and therapeutic research and development and clinical care.

About nference
Through its powerful augmented intelligence software nferX®, nference is transforming health care by making biomedical knowledge computable. Its partnership with Mayo Clinic has given nference an opportunity to synthesize more than 100 years of institutional knowledge, producing real-world evidence in real time by converting large amounts of data into deep insights to advance discovery and development of diagnostics and therapeutics. nference is headquartered in Cambridge, Massachusetts. Follow nference on LinkedIn and Twitter. Visit us at nference.ai.

nference and Mayo Clinic Study Shows Childhood and Adult Vaccinations May Provide Defense Against COVID-19

nference, a Cambridge-based company founded by Indian scientists Venky Soundararajan and Murali Aravamudan, is making biomedical data computable to solve real life complex medical problems. Ikyatha Yerasala delves into this AI marvel.

Last year, when the Corona virus hit its peak in China and created absolute pandemonium, scientists in the country identified one of the two receptors by which the SARS-CoV-2, enters cells. Called the ACE2 receptor, it was the same gateway that the original SARS virus used. ACE2 intrigued scientists across the globe who delved into studying the receptor which would lead to remarkable discoveries and one of the significant ones would be the study done by nference, whose team decided to do a deep profiling of the ACE2 receptor using their company’s nferx software. The discoveries made by nference about how COVID-19 affects the gut, respiratory system and how the virus brings about anosmia (loss of smell) were path-breaking.

How did they do it?  By using the nferX software, a cloud-based platform that enables users to dynamically query the universe of possible conceptual associations from over 100 million biomedical documents, including the COVID-19 Open Research Dataset announced by the White House. The team at nference combed these documents from published papers to genomic and other -omics databases, and uncovered multiple tissues and cell types with ACE2 receptors, and made a detailed report about it. “nferX is a powerful software platform. It synthesizes biomedical knowledge in a very comprehensive way. The idea is to replace a manual time-consuming and inefficient process, to produce real-world evidence in real-time by rapidly converting all these masses of data into insights that can advance the discovery and development of diagnostics and therapeutics,” shares Anita Kawatra, Chief Corporate Affairs Officer, nference. 

nference, headquartered in Cambridge, MA is a company that’s using augmented intelligence to transform healthcare by making biomedical knowledge computable. Founded by entrepreneur, scientist and inventor Venky Soundararajan, and serial entrepreneur, scientist and engineer Murali Aravamudan, the company makes biomedical data accessible to solve real-world life sciences problems in real time. “We see ourselves as a science first software company that uses advanced deep learning and augmented intelligence to transform healthcare by making biomedical knowledge computable. We have a strategic exclusive partnership with Mayo Clinic, which is one of the world's top academic medical centers, to synthesize more than 100 years of institutional knowledge. Because the world has seen such a massive digitization of healthcare information, from scientific literature on molecular data, real-world evidence, coupled with advances in next generation sequencing, we have large scale initiatives. There’s siloed information - from the UK Biobank with 500,000 patients to clinical genomic data and also medical health records, which have created an incredible amount of real-world data about human health. There are also adverse event reporting systems to intellectual property records, SEC filings about what companies do - all this data creates incredible opportunity to solve complex medical problems. The data has to be made computable and then synthesized and curated in order to really solve problems and im-prove the lives of people on a global scale. Even with teams of experts, it would literally take decades to digest all this genomic data, molecular data and clinical and regulatory filings. And that's just what's in the public domain,” explains Anita.

Nference ties up strategically with various organisations to use their nferX software to solve chal-lenges globally. Their collaboration with the Mayo Clinic is a significant one. “We are doing pio-neering work with de-identification, and the deidentification system is created by Indian tech-nologists. It adds electronic health records that have been deidentified using the system, labora-tory records, pathology, images, physician notes, other data representing the collective wisdom of thousands of physicians and millions of patients. This is rich data because it talks about biological context, therapeutic outcomes etc. We apply our algorithms to this data, and that can translate into earlier and better diagnosis, treatments, care, therapeutics and cures,” states Kawatra. 

With about 150 team members in India, nference is looking to expand extensively this year. The company also has offices in Rochester, Minnesota, as part of their collaboration with the Mayo Clinic as well as in Toronto, Canada. They will continue to look at more strategic collaborators and partners.

nference’s scientists are part of the section of medical experts globally that’s fervently studying the SARS-Cov2 and discovering intriguing information about how it functions, enters the human system and the areas it affects human beings in. The Washington Post, which recently called nference the ‘Google of Biomedicine’, reported how AJ Venkatakrishnan, Director of Scientific Research and Partnerships at nference, made an accidental discovery about the new coronavirus, when he took genetic data from 10,967 samples and fed it into a machine. The scientist discov-ered that the virus had the DNA code — “RRARSVAS” — distinct from its predecessor coro-naviruses. With this sequence mimicking a protein that helps the human body regulate salt and fluid balance, it started various discussions about the virus. “We applied nference technology working with our own internal technologists and biomedical scientists, as well as all the clinicians at the Mayo Clinic to aid understanding of the SARS-COV2 virus – its transmission, symptoms and progression. Our platform really enabled some major discoveries from a molecular and clini-cal perspective. This work is really advancing the development, because it's advancing the way organizations can develop therapies and vaccines to curtail the burden of  the virus - from your childhood immunizations to your ordinary immunizations that you would have over the course of your lifetime – we discovered that those have some level of protective benefit.”

A recent report reveals that an nference COVID-19 study and online tracker is the first to pro-duce evidence of increased COVID-19 vaccinations on decreased viral incidence by US coun-ties. Another interesting discovery made by nference about COVID treatment in the West, which resulted in discussions about how patients are treated is when they discovered racial disparities in anticoagulant treatment. “Through our data, we've seen that white patients were given a different version of an anticoagulant that actually is more effective than black patients. Our data showed that different versions of blood thinners heparin were given to white patients and black patients overall. The one that was more effective was given more often to white patients, and the one that was less effective to black patients. These discoveries are important to bring up because a lot of times they're reflecting unconscious bias. We noticed that the drug that was given to white pa-tients was actually more expensive. It's important that all patients have access to the treatment, that actually works better. We can identify what treatments work better, but we can also identify things like racial disparity in care that is worthy of examination,” reveals Kawatra. 

The team at nference was also one of the earliest to identify loss of sense of taste and smell brought on by the coronavirus, which have now led to tests like the sniff test because taking one’s temperature isn't really an indicator of whether or not you have the virus. “These are ways we've enabled biopharmaceutical research to advance academic and scientific research by con-tributing to this understanding of every aspect of the virus. All of these enable both researches and clinical care to advance so that doctors and those on the frontline can use this information to advance care and scientists can use information as well, in the long-term,” she adds.

The company’s research on a life-threatening chronic condition - pulmonary hypertension, which is hard to diagnose, is commendable. “The average patient waits four to six years, from the first presentation of the symptoms to diagnosis because the symptoms are often mistaken for the symptoms of other diseases that are more common like asthma. The diagnosis itself is done by a very invasive, costly procedure. It's called right heart catheterization. We can predict the onset of hypertension in patients on an average of 18 months ahead of diagnosis, with more than 80% ac-curacy, and five years ahead of diagnosis with 75% accuracy.  There are numerous other diseases that we will be able to apply our technology and algorithms  to - various kinds of cardiac disease, different kinds of amyloidosis, heart failure and atrial fibrillation. We hope this will benefit a huge number of patients in the long-term.”

When it comes to data analytics and third-party partnerships, there’s always the concern about patient privacy. How does nference ensure the protection of patients’ personal data? “We're centered around protecting patient privacy. We didn't create a solution and tweak it to protect patient privacy. We built the absolute best in protecting patient privacy and then built the system around that. We’ve established a secure privacy protecting environment, that is empowering researchers and clinicians to derive important insights that can accelerate research, the development of diagnostics, therapeutics and accelerate cures. Our goal is to improve patient outcomes, unlock these insights and biomedical data, and also protect patient privacy. It's not based on one person's data, it's based on the collective wisdom and experience of millions of scientists, physicians and patients. As for our collaboration with Mayo, that data never leaves the Mayo cloud. It's never sold to anyone, shared with anyone or copied. Researchers can only go in there, apply their output, apply the nference algorithms or apply their own algorithms. It's called a federated architecture where the data never leaves the cloud. The only thing you remove from the cloud is meaningful and clinical insights that can advance treatments, diagnosis care, and never any data itself,” shares Kawatra, explaining nference’s Clinical Data Analytics Platform, which is their collaboration with The Mayo Clinic. 

By strategically using AI to make biomedical data computable and tapping into electronic health records and unstructured data, nference is revolutionizing healthcare and their partnerships with biopharma companies will only enable them to solve more complex global problems in the future. 

Making Biomedical Data Computable through Augmented Intelligence

nference has struck up a partnership with Mayo Clinic to build a massive de-identified database that allows its caregivers to answer specific questions about patient care, including treatment approaches and how well different drugs work.

An analysis at the intersection of human genetic variation and SARS-CoV-2 evolution found identical peptide suggesting a potential for autoimmunity and molecular mimicry.

CAMBRIDGE, Mass., Nov. 30, 2021 /PRNewswire/ -- nference, the AI-driven health technology company, today announced publication of a preprint study in bioRxiv that found the genetic alteration of some linear peptides expressed specifically in the human heart are mimicked by the SARS-CoV-2 polyprotein (replicase). The study has been submitted for peer-review.

Authors of "Genetic alteration of human MYH6 is mimicked by SARS-CoV-2 polyprotein: mapping viral variants of cardiac interest" compared genetic variations encoded by the exomes from 141,456 individuals across the globe against SARS-CoV-2 genomes. By comparing peptides of human cardiac proteins and SARS-CoV-2 proteins, researchers found 21 identical 8-mer peptides between the virus and humans. In addition, a specific genetic variant of myosin heavy chain (MYH6) that is observed in rare instances in African American, Eastern Asian and South Asian populations was identical to a peptide of the SARS-CoV-2 replicase protein. The study's authors suggest that SARS-CoV-2 variants harboring peptides identical to human cardiac proteins should be investigated as "viral variants of cardiac interest."

bioRxiv is an open access preprint repository for the biological sciences hosted by the Cold Spring Harbor Laboratory.

"There is something fundamental about this striking instance of molecular mimicry that we believe sets the stage for focussed experimental evaluation," said Venky Soundararajan, PhD, co-founder and chief scientific officer of nference. "Cardiac injury is a complication that is associated with severe COVID-19. Our unexpected molecular findings offer a potential mechanistic pathway for guiding the medical community towards better understanding of the nexus between autoimmunity, genomics, viral infections, and myocarditis that affects severe COVID-19 patients."

In the process of conducting this study, nference employed its augmented intelligence software platform, which combines deep biological and molecular insights with powerful clinical knowledge synthesis at unprecedented resolution.

The innovative and real-time AI technology implemented by nference during the COVID-19 pandemic has enabled multiple scientific discoveries that are advancing patient care and helping inform public health policy across nations.

nference Study Produces First Molecular Hypothesis Explaining COVID-19-Induced Myocarditis

Results validate the company’s methodology and provide insight about the rapid evolution of future variants of concern.

CAMBRIDGE, Mass., Jan. 18, 2022 – nference, an AI-driven health technology company, today announced the publication of a preprint study in medRxiv, validating the company’s methodology for characterizing SARS-CoV-2 evolution. The study provides the first compelling genomic signal showing how highly transmissive and immuno-evasive variants, such as Omicron and Delta, emerge as dominant variants of concern. The study, titled “Continuous genomic diversification of long polynucleotide fragments drives the emergence of new SARS-CoV-2 variants of concern,” has been submitted for peer review.

Using methodology developed by nference, the study examined 100,000 repetitions of an iterative sampling experiment and compared the number of distinctive 9-unit strings of molecules called nucleotides (9-mers) in the most common strains of SARS-CoV-2. Results showed that each new variant (except for Beta, which did not circulate rapidly worldwide) had more unique strings than the variant that immediately preceded it. The original strain of the virus had 45 unique 9-mers, while Alpha had 109, Beta 69, Gamma 122, Delta 181, and Omicron 295. 

While it is generally expected that a virus will accumulate more mutations over time, the unique characteristics of variants of concern at the polynucleotide level provide additional context beyond the number of mutations acquired. This is further demonstrated by the new IHU variant but has not spread rapidly across the globe. Despite having a higher mutational load than Delta, these variants have similar characteristics at the polynucleotide level, demonstrating that an increased mutational load does not imply an increase in distinctiveness. This newly identified pattern may help predict which strains will become variants of concern and inform future vaccine design.  

“As the COVID-19 pandemic continues to evolve, it is extremely important for our scientific community to begin to understand how a virus like SARS-CoV-2 manages to adapt its genome over time,” said Venky Soundararajan, Ph.D., Co-Founder and Chief Scientific Officer at nference. “With this level of insight, we can begin to predict which dominant variants are likely to emerge in the future. This methodology can also be applied to retrospectively study the genomic history of human pathogens to give us a clearer picture of infectious viruses. This latest breakthrough is a testament to our commitment to moving this promising era of data science into meaningful cures for patients.”

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