OneMedNet Corp

Company Overview

OneMedNet is a global provider of clinical imaging innovation and curator of regulatory-grade Imaging Real-World Data or iRWDTM. OneMedNet’s innovative solutions connect healthcare providers and patients satisfying a crucial need within the Life Sciences field offering direct access to clinical images and the associated contextual patient record. OneMedNet’s innovative technology proved the commercial and regulatory viability of imaging Real-World Data, an emerging market, and provides regulatory-grade image-centric iRWDTM that exactly matches OMN’s Life Science partners Case Selection Protocols and paves the way for Real World Evidence.

OneMedNet was founded to solve a deficiency in how clinical images were shared between healthcare providers. This resulted in OMN’s initial product BEAMTM image exchange that enabled the successful sharing of images for more than a decade with OMN’s largest customer being the Country of Ireland.

OneMedNet continued to innovate by responding to the demand for and utilization of Real-World Data and Real-World Evidence, specifically data that focused on clinical images with its associated contextual clinical record. We were able to leverage internal technological competencies along with OneMedNet’s formidable healthcare provider installed base from its first product with BEAMTM to become the first RWD solution for Life Science companies with its launch of iRWDTM in 2019.

OneMedNet provides innovative solutions that unlock the significant value contained within clinical image archives. With a growing federated network of 95+ healthcare facilities, OneMedNet has the immediate ability to quickly search and extensively curate multi-layer data from a Federated group of healthcare facilities. The term “healthcare facilities” refers specifically to the hospitals, integrated delivery networks (“IDNs”) and imaging centers that provide imaging to OneMedNet, which represent the core source of our data. At present, OneMedNet works with more than 95 facilities who provide regulatory grade imaging to us. OneMedNet has access to these more than 95 facilities because these 95+ contracted facilities have more than 200 locations among them including offices and clinics, which in total generates regulatory grade imaging from more than 200 customers. Among these customers, all are data providers and some are data purchasers.

OneMedNet is ahead of the curve when it comes to providing fast and secure access to curated medical images. Initially, it was all about solving the diverse access needs of patient care providers. This focus systematically evolved to addressing the rapidly growing needs of image analysis and researchers, clinicians, regulators, scientists and more.

Real-world data is any data that is collected in the context of the routine delivery of care, in contrast to data collected within a clinical trial where study design controls variability in ways that are not representative of real-world care and outcomes.

A key component driving its mission is that OneMedNet believes we have a unique opportunity to affect a material positive impact on the lives of tens of millions of people while improving our customers’ business productivity. First and foremost, OneMedNet’s iRWDTM offering plays a significant role in enabling Life Science companies to bring safer and more effective patient care to market sooner. Using our highly curated de-identified clinical data in our iRWDTM offering in Life Science product development, validation, and regulatory approval processes, they contribute to patient care advancements in more meaningful ways. Moreover, Life Sciences improve their product development and validation processes, which benefits all parties.

Significant documentation exists that shows that Real-World Data can provide expanded insights across broader and more representative patient populations. For this reason, the Food and Drug Administration (“FDA”) has instituted Real-World Data guidelines for regulatory approvals. Utilization of highly reliable and quality Real-World Data that strictly adheres to all of the very specific data stratification requirements can supplement or supplant clinical trials.

OneMedNet covers the complete value chain in imaging Real-World Data; it begins with our 10+ year federated network of providers and is supported by a multi-faceted data curation process managed by an expert in-house clinical team. Additionally, we work hand-in-hand with our Life Science partners regarding the Case Selection Protocol and when required producing Case Report Forms for regulatory clearance. We are focused on delivering value by supporting Life Science Advancements with OneMedNet’s iRWDTM which holds the key to unlocking boundless patient care advances. We unleash the power of research-grade image-centric iRWDTM that is highly curated to painstakingly meet every cohort requirement and stand up to all of the rigors of prospective clinical trials.

Today, life science companies, including pharmaceutical companies, artificial intelligence (AI) developers, medical device businesses, and clinical research organizations share the same widespread challenge in obtaining insight-rich, high-quality patient data that explicitly matches their precise cohort specifications. A substantial portion of patient diagnosis involves clinical imaging and approximately 90% of healthcare data, by size, is associated with imaging. Historically, much of imaging value has been derived from its initial review and further gains from the image archives have been very limited.

We help providers to “Unlock the Value in Imaging Archives”. TM By utilizing OneMedNet’s iRWDTM offering, providers can greatly improve their research efforts with streamlined data access. Health care providers such as hospitals, clinics, and imaging centers can also accelerate life science patient care innovations by sharing de-identified data in a well-defined and de-identified and secure manner. In return for doing so, income is generated and applied to critical and possibly unfunded provider projects.

The OneMedNet Difference

OneMedNet has been a leader in the business of extracting, securing, and transferring medical data for 12+ years. Doing so requires specialized expertise in:

Attaining in-house expertise in all essential elements is quite a challenge and deters many organizations from even attempting such a venture. We take pride in this ambitious achievement – while continually working to maintain state-of-the-art expertise. OneMedNet strictly adheres to the highest level of professional and ethical standards and applicable regulations throughout all interactions and activities.

We believe there is a reason OneMedNet is the leader in an uncrowded field of regulatory-grade imaging RWD curators. Doing so requires specialized expertise in AI/ML technology, data privacy/security, as well as expertise in clinical patient condition(s) and healthcare record keeping. Having, or achieving, expertise in all essential disciplines is a challenging achievement. OneMedNet had a significant head start with our clinical image exchange solution which served to launch the Company nearly a decade ago. All data remains “native” within the federated OneMedNet iRWDTM provider network – meaning all the data remains locally onsite until specific de-identified data is licensed for a particular Life Science research opportunity.

OneMedNet’s Competitive Advantages

We believe that OneMedNet iRWDTM offers the best of advanced technology, clinical expert curation, and service. Medical imaging and associated clinical data is indexed at each network site using state-of-the-art AI/ML technology. This typically includes electronic health records (“EHR”), radiology, cardiology, lab, path and more. Our in-house clinical team performs intensive curation of the data ensuring that results meet the exact specification and requirements of Life Science Data Collection Protocol (“DCP”) – regardless of the complexity.

We believe that OneMedNet unlocks the value in imaging and electronic health records data in the following three principal ways:

OneMedNet’s data is fully de-identified using a multi-step quality control process and goes beyond PHI to include PII (personally identifiable information), SII (Site Identifiable Information), and more. Importantly, Life Science users receive the data in the exact format that they require. No data sifting or manipulation is needed. The data is simply ready for use. Moreover, OneMedNet has the unique combination of knowledge, tools, and experience to:

Finally, OneMedNet has the most experienced and clinically trained data curators in the industry. This team appreciates the complexity and criticality of clinical data and can effectively communicate with both Provider and Life Science specialists.

Industry Background

A 2016 analysis published in the Journal of Health Economics and authored by the Tufts Center for the Study of Drug Development placed the cost of bringing a drug to market, including post-approval research and development, at a staggering $2.87 billion. Meanwhile, a 2018 study from the Tufts Center noted that the timeline for new drug development ranged from 12.8 years for the average drug to 17.2 years for ultra-orphan drugs that only affect several hundred patients. This places the onus on life science organizations to find ways to deliver treatments to patients faster — especially those who cannot wait 17 years for a potentially life-saving treatment. Knowing how a medicinal product is actually used by patients can help stakeholders across the healthcare ecosystem make important and potentially life-saving real-time decisions.

Real-World Data is observational data typically gathered when an approved medical product is on the market and used by “real” patients in real life, as opposed to clinical trials or real world images for real patients. The FDA cites several potential sources of Real-World Data, including electronic health records (“EHRs”), claims, disease and product registries, there are multiple types of data including structured and unstructured data, clinical and billing data, transactional and claims data, patient-generated data, and data gathered from additional sources that can shed light on a patient’s health status and more. As reliance on healthcare data grows exponentially, OneMedNet has observed that the reliance on information has increased coming from multiple additional sources including EHRs, claims, registries, clinical trials, patient and provider surveys, wearable devices and more. These additional sources include the internet of things (“IoT”), social media forums and blogs. Real-World Data has the potential to break down inefficiencies and fill gaps in information silos among stakeholders throughout the healthcare ecosystem of providers, payers, manufacturers, government entities and patients. This information sharing, in turn, enables all parties to derive new insights, support value-based care and deliver better health outcomes.

Commercializing a drug requires its developer to harness various sources of Real-World Data to identify patient populations and refine sales and marketing strategies for those populations among many other undertakings. Historically, this practice involved purchasing large amounts of data from data aggregators or data platforms, if not directly from the source itself, sometimes without much knowledge about the quality of the data. Preparing this data for analysis is both expensive and time-consuming thus many organizations would outsource the process to consultants or third-party vendors; moreover, the process of preparing this data for analysis by untrained consultants can yield a static analysis that is difficult to modify or rerun in response to follow-up questions or potential discrepancies.

Definitions of Real-World Data and Real-World Evidence

Real-World Data has become a powerful tool in the life sciences industry. After decades of relying on clinical data as the gold standard for decision making, industry leaders now recognize how data collected in the real world adds valuable context and insight to their efforts. From identifying unmet medical needs and defining the patient journey, to supporting regulatory submissions, proving value to payers, and shaping market strategies, Real-World Data adds value at every stage of the drug development lifecycle. Real-World Data also sets the foundation for Real World Evidence, and while the terms are often used interchangeably, they are distinct and they are changing health care. Here’s how it happens:

The availability of medical imaging in Real-World Data such as that provided by OneMedNet is facilitated by the development of digital image analysis to increase the accuracy of diagnostics and conduct passive screening on large databases of medical images using artificial-intelligence (“AI”) algorithms such as those applied by OneMedNet. Algorithms can also help identify additional diagnostic tests of value from medical images with pathology.

Real-World Evidence is the clinical evidence regarding the usage and potential benefits or risks of a medical product derived from analysis of Real-World Data, as defined by the Food and Drug Administration. Real-World Evidence can be generated by different study designs or analyses, including but not limited to, randomized trials, including large simple trials, pragmatic trials, and observational studies (prospective and/or retrospective). The difference in Real World Evidence and Real World Data focuses on the end use case. Real World Data can take the form of claims, electronic health records, labs, data etc. Often this insight is used to better understand a patient’s journey or a natural history of a disorder (how does a disease progress if left untreated.)

Real World Evidence in contrast builds upon many of these data sets and prepares them for submission, as part of regulatory review such as to the Food and Drug Administration or the European Medicines Agency, for example, in support of a customer’s clinical trial application. When data and in particular imaging data is submitted to the FDA the agency requires the following:

One area where Real World Evidence has been relief on heavily relates to oncology approvals. Food and Drug Administration’s Oncology Center of Excellence actually presented an analysis of this at American Society of Clinical Oncology in 2021, looking at oncology applications containing Real-World Data and Real-World Evidence. That analysis looked at 94 applications that were submitted from 2011-2020 and showed that inclusion of Real-World Data to support regulatory decision-making has increased dramatically over that period. In 2020 alone, there were 28 submissions for oncology products that contained Real-World Data. Outside of the oncology context, probably the most notable recent example of an approval relying on Real World Evidence is the July 2021 approval of a new indication for Astellas’ drug Program (or tacrolimus) for the prevention of organ rejection in lung transplant patients. The approval there was based on a non-interventional study providing Real-World Evidence of effectiveness. FDA’s press release announcing the approval noted that the approval was “significant because it reflects how a well-designed, non-interventional study relying on fit-for-purpose real-world data, when compared to a suitable control, can be considered adequate and well-controlled under FDA regulations.”

An additional recent approval of note was the December 2021 approval of the supplemental BLA for Orencia to prevent graft versus host disease. The application included data from a randomized clinical trial, with additional evidence of effectiveness provided by a registry-based clinical study that was conducted using real-world data from the Center for International Blood and Marrow Transplant Research. And that registry study analyzed outcomes of 54 patients treated with Orencia for the prevention of graft versus host disease, in combination with standard immunosuppressive drugs, versus 162 patients treated with the standard immunosuppressive drugs alone, and showed efficacy in that indication.

AI is employed in Real-World Data to enhance data anomaly detection, standardization, and quality checking at the pre-processing stage. AI is expected to offer pharma and biotech companies the ability to increase meaningful Real World Evidence output, decrease time to insights, and make the most of the available vast data sources. A Real World Evidence technology platform that delivers smart data processing, analysis, and outcomes offers an unparalleled opportunity to capitalize on these computing advancements.

When used as part of an overall comprehensive Real World Evidence strategy, AI innovations can enhance drug development, improve patient treatment and access, and drive valuable new business opportunities.

In post-marketing studies, adverse events reporting is an area where AI is used, creating greater automation and efficiency in historical data sets. Techniques like natural language processing (“NLP”) enable AI to scan tens of thousands of records and quickly find adverse event details. AI integrated analytics and automation provide access to crucial insights from historical clinical trial Real-World Data and Real World Evidence, expanding end-to-end clinical trial capabilities:

AI is driving ground-breaking leaps in protein structure identification, and advances in regulations are providing healthcare research organizations with access to real-world data to accelerate clinical trial processes. We believe that AI-enabled technologies have unparalleled potential to offer innovative trial design and collection, organizing, and analyzing the increasing amount of data generated by clinical trials. AI has many applications in clinical trials, both short and long-term. AI technologies make possible innovations crucial for transforming clinical trials, such as seamlessly combining Phases I and II, developing novel patient-centered endpoints, and collecting and analyzing Real-World Data.

OneMedNet believes that AI tools also have wider benefits for hospitals and health systems. Professor Alexander Wong, University of Waterloo Canada Research Chair in AI and Medical Imaging, points out that AI benefits include the potential to ease the burden on radiology departments in terms of assessing scans and predicting upcoming demand for general hospital and intensive care beds, and demand for equipment such as respirators and ventilators, medicines, masks, and ventilator mouthpieces, as well as aiding workforce planning.

Across a diverse set of imaging modalities, digital images typically include metadata and/or annotations that may include protected health information (e.g., patient name, date of birth). Although diagnostic images generally do not warrant the same level of privacy concerns as genomic data, researchers must also remove facial characteristics or other features that could identify a patient.

Digital image analysis can be used to support research and development by analyzing large volumes of tissue specimens or other medical images to run molecular screens that model biomarkers and treatment responses by transplanting a portion of a patient’s tumor into humanized mice or 3D tissue cultures derived from stem cells that resemble miniature organs. These models allow researchers to conduct controlled laboratory experiments that can inform treatment approaches and link predicted treatment response to actual clinical outcomes by linking this data to EHR, claims, and other sources of Real-World Data. Similarly, preclinical studies can be informed by safety assessments conducted in animal models or studies of animal molecular biomarkers or anatomic abnormalities to minimize the burden on human study participants. Findings can also inform clinical trial optimization by stratifying participants according to predicted response and determining appropriate eligibility criteria.

Evaluating Real-World Evidence in the context of regulatory decision-making depends not only on the evaluation of the methodologies used to generate the evidence but also on the reliability and relevance of the underlying Real-World Data; these constructs may raise different types of considerations. Real-World Evidence refers to evidence about the risks and benefits of a product derived from analysis of the Real-World Data. For example, the FDA has used Real-World Data and Real-World Evidence, derived from its Sentinel system for monitoring the safety of regulated products, in place of post-marketing studies. It has carried this out for nine potential safety issues involving five products.

Real-World Evidence is the clinical evidence regarding the usage and potential benefits or risks of a medical product derived from analysis of Real-World Data. Real World Evidence can be generated by different study designs or analysis, including but not limited to, randomized trials, including large simple trials, pragmatic trials, and observational studies (prospective and/or retrospective).

Unlike traditional clinical trials, where necessary data elements can be curated and collection mandated, the creation of Real World Evidence requires assessing, validating and aggregating various, often disparate, sources of data available through routine clinical practice. Real-world evidence is used by different stakeholders in many different ways.

From Real-World Data to Real World Evidence

The creation of Real World Evidence requires a combination of high-powered analytics, a validated approach and a robust knowledge of available Real-World Data sources (e.g., what data is captured within existing quality registries, what data can be captured through electronic health records and case report forms or claims, which patient organizations capture data on relevant patient cohorts). This process includes several steps, which are summarized here:

Real World Evidence has been proven to fill a gap between research (what we learn) and everyday practice (what we do) in healthcare, and it creates a difference between what is expected to happen and what really happens. Driving measurable improvements in healthcare requires us all to be rooted in the reality of what actually happens before, during, and after clinical procedures, interventions, and office visits. Real World Evidence fill those gaps and documents the truth by establishing definitively what really happens when doctors treat a wide range of patients that do not look like the homogeneous patient groups in a clinical trial. Because of this, Real World Evidence serves many uses and provides many benefits across the healthcare ecosystem.

As more countries battle to contain healthcare costs, and as the population ages and the number of patients with chronic diseases increases, the need to remove inefficiencies and upgrade the delivery of coordinated care that improves outcomes is more pressing. At the same time, life sciences companies are facing tumultuous times. Industry globalization, the end of the blockbuster era, and an increasingly complex regulatory environment all add to the difficulty of bringing products to market. And across the board, companies are moving toward a patient-centric and outcome-focused model. In this environment, Real World Evidence can be transformative for the industry when Real-World Data is combined with the right technology framework and the regulatory intelligence to make sense of it. As data is consumed across life sciences in different ways and by different stakeholders, it can provide valuable insights and “evidence” across the product life cycle. In addition, stakeholders across the healthcare ecosystem use this new knowledge to support decision-making and improve safety and effectiveness, and ultimately, patient outcomes.

Uses of Real World Evidence in Life Sciences, Among Regulators, Clinicians, Researchers and Healthcare Systems

According to repeated studies by Deloitte, the importance of Real World Evidence continues to rise as it promises to accelerate regulatory decision-making and support the approval of new indications for drugs already on the market. Life Sciences, pharmaceutical and medical device companies are significant consumers of Real World Evidence because it can provide value across the entire product lifecycle from pre-trial design to clinical studies and trials to post-market surveillance. Medical product developers are using Real World Evidence to support clinical trial designs (e.g., large simple trials, pragmatic clinical trials) and observational studies to generate innovative, new treatment approaches.

Real World Evidence can be used to make clinical trials more effective and efficient, for example in patient recruitment or label extension, Real World Evidence gathered from other studies or from currently marketed products in a similar category, for example, can have a positive effect on the product portfolio by exposing positive side effects as new potential indications. The most famous example is Viagra, which was initially studied as a drug to lower blood pressure, but an unexpected side effect led to the drug ultimately being approved for erectile dysfunction.

The benefits of Real World Evidence derived from Real-World Data are increasingly being recognized by regulatory authorities. The FDA released a framework for using Real World Evidence to support the process of drug regulation and submission. This is a major step toward recognizing that clinical trials, while still relevant, are not the only way to assess the efficacy and safety of a product. Indeed, the FDA is soon expected to conduct its first full post-market safety approval using only Real World Evidence.

Real World Evidence is now accepted as a reliable source of information for regulatory decision making in certain circumstances. A primary rationale for the FDA to use Real World Evidence E is to help support the approval of a new or extended use for a drug approved under the FD&C Act and to help support or satisfy post-approval study requirements always with the condition that the data quality is up to the standard required. In a recent statement, the FDA even noted how new tools for capturing data in the post-market period, including more sophisticated use of Real-World Data and Real-World Evidence are providing new approaches to address important questions about the safety and benefits of new drugs in real world settings and that these approaches have the potential to do to so more rapidly and with greater efficiency than traditional methods.

Why Do We Need Real-World Evidence?

There is a gap between research (what we learn) and everyday practice (what we do) in healthcare, and it creates a difference between what is expected to happen and what really happens. But it is what really happens that matters. Driving measurable improvements in healthcare requires us all to be rooted in the reality of what actually happens before, during, and after clinical procedures, interventions, and office visits. Real-World Evidence is here to fill those gaps and root us in truth. It tells us what really happens when doctors treat a wide range of patients that don’t look like the homogeneous patient groups in a clinical trial. Because of this, Real-World Evidence serves many uses and provides many benefits across the healthcare ecosystem.

Uses of Real-World Evidence in Pharmaceutical and Device Companies

Pharmaceutical and medical device companies are major consumers of Real-World Evidence, as it can provide value across the entire product lifecycle. Real-World Evidence plays an important role for research across the product lifecycle for both pharmaceutical and device companies. It can inform pre-trial study design by helping researchers identify potential patients and create proper inclusion criteria for clinical trials. Much of medical innovation is driven by traditional clinical trials, where new pharmaceuticals and devices are rigorously studied and tracked before they can be sold and widely distributed.

Although clinical trials are incredibly important to determine the safety and efficacy of new technologies, when compared to real-world evidence they do have some limitations. For example, traditional clinical trials can have strict inclusion criteria that makes it challenging for providers to accurately extrapolate the results of a clinical trial to a broader population. Clinical trial participation is often limited by who the study administrators are able to recruit, and various demographics are often not able to participate. This again challenges the generalizability of clinical trial results across patient populations. Real-world evidence can help overcome the limitations of clinical trials by providing information about a broader cross-section of society. This can help clinicians, researchers, and industry partners better understand their products and how they work.

Once a product is approved and marketed, Real-World Evidence assists pharmaceutical or medical device company understand their products’ relative safety, effectiveness, value, off-label use and more. This post-market surveillance, or post-marketing surveillance, is valuable to stakeholders across the healthcare industry.

The AI-enabled patient enrichment and recruitment process can improve suitable cohorts and increase clinical trial effectiveness, data management, analysis, and interpretation of multiple Real-World Data sources, including EHRs and medical imaging data. This presents a unique opportunity for NLP to perform the sophisticated analysis necessary to combine genomic data with electronic medical records (“EMRs”) and other patient data, present in various locations, owners, and formats — from handwritten paper copies to digital medical images — to surface biomarkers that lead to endpoints that can be more efficiently measured, and thereby identify and characterize appropriate patient subpopulations. AI-enabled systems can help to improve patient cohort composition and aid with patient recruitment.

AI technologies can help biopharma companies identify target locations, qualified investigators, and priority candidates and collect and collate evidence to satisfy regulators that the trial process complies with good clinical practice (“GMP”) requirements. One of the most important elements of a clinical trial is a selection of high-functioning investigator sites. Site qualities such as resource availability, administrative procedures, and experienced clinicians with in-depth knowledge and understanding of the disease can shape study timelines and data quality, accuracy, completeness, and consistency.

AI integrated clinical trial programs can help monitor and manage patients by automating real-world data capture, sharing data across systems, and digitalizing standard clinical assessments. AI technologies and wearable technologies can help enable continuous patient monitoring and generate real-time insights into the safety and effectiveness of treatment while predicting the possible risk of dropouts, thereby enhancing patient engagement and retention. To comply with trial adherence criteria, patients must keep detailed records of their medication intake and other data points related to their bodily functions, response to medication, and daily protocols. This can be an overwhelming and tedious task, leading to 40% of patients becoming non-adherent after 150 days into a clinical trial. Wearable devices/sensors and video monitoring are used to collect patient data automatically and continuously, thereby relieving the patient of this task. In combination with wearable technology, AI techniques offer new approaches to developing real-time, power-efficient, mobile, and personalized patient monitoring systems.

Among regulators, clinicians, academic researchers and healthcare systems, the reliance on curated Real World Evidence has grown significantly because of the value it can provide, which is unique relative to each parties’ objectives and mandates. It also helps that the FDA has also sharpened its focus on Real-World Data and Real World Evidence. For example, late last year, the FDA published proposed guidance related to data standards for product submissions with Real-World Data and also weighed in on the use of Real-World Data and Real World Evidence to support regulatory decision-making for drugs and biological products with specific advice for data from electronic health records and medical claims. In addition, the FDA uses Real-World Data and Real World Evidence to monitor post-market safety and adverse events and to make regulatory decisions. The health care community is using these data to support coverage decisions and to develop guidelines and decision support tools for use in clinical practice.

AI with deep-learning capability is also helpful in organizing and translating a vast amount of structured and unstructured data to RWE. The human mind can possibly manage 4-5 variables, therefore, AI-enabled data mapping and integration and their normalization into a common data model according to disease pathway and workflow will likely be useful for both quality management in clinical trials and generating meaningful insight for human disease by providing a broader perspective based on real-world data.

Market Size

The global real world evidence solutions market size was estimated at USD 2.6 billion in 2023 and is expected to grow at a compound annual growth rate (CAGR) of 8.4% from 2024 to 2030. The market growth is driven by rising demand for enhanced Real-World Evidence (RWE) capabilities within the life science industry, reflecting an increasing market shift from volume to value-based care. Advancements in data analytics and real-world evidence (RWE) contribute to supporting regulatory compliance, research, and solution development efforts in medical device and life sciences organizations. For instance, the increased demand for Real-World Evidence solutions is prompting players to introduce new products, fostering market growth. In October 2023, Maxis Clinical Sciences launched Real-World Evidence Solutions, providing diverse real-world data capture and analysis to improve clinical research and care.

Government initiatives supporting Real-World Evidence programs, evolving regulations, and actionable Real-World Data enable organizations to conduct outcomes-based analyses, contributing to the overall market expansion. For instance, in December 2022, the FDA launched the Real-World Evidence Program. This program aims to raise awareness that Real-World Evidence can support regulatory decisions, identify approaches for generating Real-World Evidence to meet post-approval study requirements or effectiveness labeling and develop agency processes that foster consistent decision-making and shared learning regarding Real-World Evidence.

The COVID-19 pandemic further accelerated the adoption of Real-World Evidence solutions, with governments collaborating with market players to implement these solutions. For instance, in June 2021, ConcertAI and the FDA initiated a five-year collaborative research program,Evaluation of Real-World Outcomes and Safety in the Treatment of Cancer. The partnership leverages ConcertAI’s oncology Real-World Data and advanced AI technology solutions to generate Real-World Evidence for various clinical and regulatory use cases.

The global real world evidence solutions market is projected to grow from $16.13 billion in 2023 to $36.24 billion by 2030, at a CAGR of 12.3%. The drug development and approvals segment accounted for the highest revenue share of around 28.9% in 2020. Real-world evidence solutions services allow pharmaceutical companies and healthcare providers as well as payers for efficient management of operations and accelerate the process of drug development and its approval, which fuels market growth. Support from regulatory bodies for using Real World Evidence solutions and an increase in research and development spending are anticipated to boost the market growth.

The RWE solution providers are increasingly forming strategic partnerships with AI solution providers to offer integrated solutions. For instance, in April 2023, ConcertAI, a player in AI SaaS technology and RWE solutions for healthcare and life sciences, partnered with PathAI, an AI-powered pathology provider, to introduce a first-in-class quantitative histopathology and curated clinical Real-World Data solution. This collaboration integrates ConcertAI’s Patient360 and RWD360 products with PathAI’s PathExplore tumor microenvironment panel. Based on end user, the global Real World Evidence solutions market is segmented into pharmaceutical, biotechnology, and medical device companies; healthcare payers; healthcare providers; and other end-users (academic research institutions, patient advocacy groups, regulators, and health technology assessment agencies). The large share of this segment is primarily attributed to the increasing importance of Real World Evidence studies in drug development and approvals and the growing need to avoid costly drug recalls and assess drug performance in real-world settings.

With the growing need for evidence generated from Real-World Data, the increasing importance of epidemiological data in decision making, and a shift from volume to value-based care, there has been an increased focus on patient registries, a rise in the adoption of EMR in hospitals, and exponential growth in mobile health data and social media which have resulted in the generation of huge amounts of medical data. In 2021, the real-world datasets segment is estimated to account for the larger share of 51.2% of the global real-world evidence solutions market. According to Coherent Market Insights, the global Real-World Data market is estimated to be valued at $1.59 billion in 2023 and is expected to exhibit a CAGR of 14.4% during the forecast period (2023-2030).

Our Long-Term Growth Strategies

Our long-term growth strategy is anchored on the following key pillars:

Corporate Information

We were originally incorporated in Delaware on February 8, 2021 under the name “Data Knights Acquisition Corp” as a special purpose acquisition company, formed for the purpose of effecting a merger, capital stock exchange, asset acquisition, stock purchase, reorganization or similar business combination with one or more businesses. On November 7, 2023, we held the Closing of the previously announced Merger whereby Merger Sub merged with and into OneMedNet Solutions Corporation (formerly named OneMedNet Corporation), with OneMedNet Solutions Corporation continuing as the surviving entity, which resulted in all of the issued and outstanding capital stock of OneMedNet Solutions Corporation being exchanged for shares of the Company’s Common Stock upon the terms set forth in the Merger Agreement.

The Merger and other transactions that closed on November 7, 2023, pursuant to the Merger Agreement, led to Data Knights changing its name to “OneMedNet Corporation” and the business of the Company became the business of OneMedNet Solutions Corporation. We are located at 6385 Old Shady Oak Road, Suite 250, Eden Prairie, MN 55344 and reachable by telephone on 800-918-7189.

The information contained on our website is not incorporated by reference into this prospectus, and you should not consider any information contained on, or that can be accessed through, our website as part of this prospectus or in deciding whether to purchase our Common Stock.

OneMedNet Corporation a Delaware corporation (the “Company,” “we,” “us,” or “OneMedNet”) together with its wholly-owned subsidiary OneMedNet Solutions Corporation, a Delaware corporation, founded on October 13, 2009 in the State of Hawaii and later incorporated in the State of Delaware on November 20, 2015 and its wholly-owned subsidiary, OneMedNet Technologies (Canada) Inc., incorporated on October 16, 2015 under the provisions of the Business Corporations Act of British Columbia whose functional currency is the Canadian dollar. All refences in this prospectus to the “Company,” “we,” “us,” or “OneMedNet” include OneMedNet Solutions Corporation and its wholly-owned subsidiary, OneMedNet Technologies (Canada) Inc., incorporated on October 16, 2015 under the provisions of the Business Corporations Act of British Columbia whose functional currency is the Canadian dollar.

Recent Developments

Closing of Business Combination

OneMedNet Corporation, a Delaware corporation (the “Company,” “we,” “us” or “OneMedNet”) together with its wholly-owned subsidiary, OneMedNet Solutions Corporation, a Delaware corporation, and its wholly-owned subsidiary, OneMedNet Technologies (Canada) Inc., incorporated under the provisions of the Business Corporations Act of British Columbia whose functional currency is the Canadian dollar. All references in this prospectus to the “Company,” “we,” “us,” or “OneMedNet” include OneMedNet Corporation and both OneMedNet Solutions Corporation and OneMedNet Technologies (Canada) Inc., except that references to the “Company” “we,” “us,” or “Data Knights” in this Item 7 refer to OneMedNet Corporationf/k/a Data Knights Acquisition Corp.

We were originally incorporated in Delaware on February 8, 2021 under the name “Data Knights Acquisition Corp” as a special purpose acquisition company, formed for the purpose of effecting a merger, capital stock exchange, asset acquisition, stock purchase, reorganization or similar business combination with one or more businesses. On May 11, 2021, we consummated an initial public offering.

On November 7, 2023, following the approval at the special meeting of the shareholders of Data Knights Acquisition Corp., a Delaware corporation held on October 17, 2023 (the “Special Meeting”), Data Knights Merger Sub, Inc., a Delaware corporation (“Merger Sub”) and a wholly-owned subsidiary of Data Knights Acquisition Corp., a Delaware corporation (“Data Knights”), consummated a merger (the “Merger”) with and into OneMedNet Solutions Corporation (formerly named OneMedNet Corporation), a Delaware corporation (“OneMedNet”) pursuant to an agreement and plan of merger, dated as of April 25, 2022 (the “Merger Agreement”), by and among Data Knights, Merger Sub, OneMedNet, Data Knights, LLC, a Delaware limited liability company (“Sponsor” or “Purchaser Representative”) in its capacity as the representative of the stockholders of Data Knights, and Paul Casey in his capacity as the representative of the stockholders of OneMedNet (“Seller Representative”). Accordingly, the Merger Agreement was adopted, and the Merger and other transactions contemplated thereby (collectively, the “Business Combination”) were approved and completed.

At the closing, on November 7, 2023, of the Business Combination pursuant to the Merger Agreement, Merger Sub merged with and into OneMedNet with OneMedNet surviving the Merger, as a wholly-owned subsidiary of Data Knights, and Data Knights changed its name to “OneMedNet Corporation.”

The Business Combination was accounted for as a reverse recapitalization in accordance with U.S. GAAP. Under this method of accounting, Data Knights was treated as the acquired company and OneMedNet Corporation was treated as the acquirer for financial statement reporting purposes.

Lock-up Agreements

Effective April 25, 2022, in connection with the execution of the Merger Agreement, certain stockholders of OneMedNet and certain of OneMedNet’s officers and directors (such stockholders, the “Company Holders”) entered into a lock-up agreement (the “Lock-up Agreement”) pursuant to which the Company Holders will be contractually restricted, during the Lock-up Period (as defined below), from selling or transferring any of (i) their shares of OneMedNet common stock held immediately following the Closing and (ii) any of their shares of OneMedNet common stock that result from converting securities held immediately following the Closing (the “Lock-up Shares”). Effective November 7, 2023, the newly appointed officers and directors of OneMedNet Corporation have entered into a Lock-Up Agreement.

The “Lock-up Period” means the period commencing at Closing and end the earliest of: (a) six months from the Closing, and (b) the date after the Closing on which the Purchaser consummates a liquidation, merger, capital stock exchange, reorganization, or other similar transaction with an unaffiliated third party that results in all of the Purchaser’s stockholders having the right to exchange their shares of the Purchaser Common Stock for cash, securities, or other property: (i) lend, offer, pledge, hypothecate, encumber, donate, assign, sell, contract to sell, sell any option or contract to purchase, purchase any option or contract to sell, grant any option, right or warrant to purchase, or otherwise transfer or dispose of, directly or indirectly, any Restricted Securities, (ii) enter into any swap or other arrangement that transfers to another, in whole or in part, any of the economic consequences of ownership of the Restricted Securities, or (iii) publicly disclose the intention to do any of the foregoing, whether any such transaction described in clauses (i), (ii), or (iii) above is to be settled by delivery of Restricted Securities or other securities, in cash or otherwise (any of the foregoing described in clauses (i), (ii), or (iii), a “Prohibited Transfer”).

In addition, the Sponsor is subject to a lock-up pursuant to a letter agreement (the “Sponsor Lock-up Agreement”), entered into on May 6, 2021, at the time of the IPO (as defined below), among Data Knights, the Sponsor and each of the individuals who were a member of Data Knights’ board of directors and/or management team (each, an “Insider” and collectively, the “Insiders”), who agreed that it, he or she shall not transfer any founder shares which means the 2,875,000 shares of Data Knights Class B common stock, par value $0.0001 per share, initially held by the Sponsor, or shares of OneMedNet’s Common Stock issuable upon conversion thereof) until the earlier of (A) six months after the date of Data Knights’ initial Business Combination or (B) subsequent to the initial Business Combination, (x) if the reported last sale price of the Common Stock equals or exceeds $12.00 per share (as adjusted for stock splits, stock dividends, right issuances, reorganizations, recapitalizations and the like) for any 20 trading days within any 30-trading day period commencing at least 150 days after the Company’s initial Business Combination, or (y) the date on which the Company completes a liquidation, merger, capital stock exchange, reorganization or other similar transaction that results in all of our stockholders having the right to exchange their shares of common stock for cash, securities or other property. Further, the Sponsor and each of the Insiders agreed further in the Sponsor Lock-Up Agreement that he, she or it shall not transfer any private placement units, the private placement shares, the private placement warrants or shares of Common Stock issued or issuable upon the exercise of the private placement warrants, until 30 days after the completion of the initial Business Combination.

Registration Rights Agreements

At the Closing of the Business Combination and funding of the PIPE, the PIPE Investors each executed a PIPE Note and a PIPE Warrant in the amount corresponding to each PIPE Investor’s investment amount and in accordance with the terms set forth in the PIPE SPA as well as a registration rights agreement (the “PIPE Registration Rights Agreement”). We are registering the offer and sale of these securities to satisfy the registration rights we have granted in the PIPE Registration Rights Agreement. At the Closing of the Business Combination, OneMedNet, Data Knights and the Sponsor entered into a registration rights agreement (the “Registration Rights Agreement”), pursuant to which, among other things, the Company is obligated to file a registration statement to register the resale of certain securities of the Company held by the holders, as defined in the Registration Rights Agreement and the Sponsor. The Registration Rights Agreement also provides the holders and the Sponsor with “piggy-back” registration rights, subject to certain requirements and customary conditions.

Voting Agreement and Sponsor Support Agreement

In connection with entry into the Merger Agreement, the Company entered into voting agreements (the “Voting Agreements”) with certain stockholders of OneMedNet representing approximately 55% of the outstanding voting power of OneMedNet’s equity securities (the “OneMedNet Stockholders”) pursuant to which OneMedNet Stockholders agreed to vote their securities in favor of the approval of the Merger Agreement and the Business Combination, be bound by certain covenants and agreements related to the Business Combination and to take other customary actions to cause the Business Combination to occur.

In connection with entry into the Merger Agreement, the Company, the Sponsor and OneMedNet entered into a sponsor support agreement (the “Sponsor Support Agreement”) pursuant to which the Sponsor agreed to vote its Data Knights securities in favor of the approval of the Merger Agreement and the Business Combination and to take other customary actions to cause the Business Combination to occur.

Executive Employment Agreements

In connection with the Closing of the Business Combination, the Company has entered into employment agreements (the “Employment Agreements”) with executive officers: Aaron Green (President), Lisa Embree (Chief Financial Officer), and Paul Casey (Chief Executive Officer). The Employment Agreements provide for at-will employment that may be terminated by the Company with or without cause, by the executive with or without good reason, or mutually terminated by the parties.

The Employment Agreement for Mr. Green provides for $350,000 annual salary, eligibility to receive an annual cash performance bonus of $175,000 upon his achievement of the performance goals set by the Company’s CEO and Board of Directors, and eligibility to receive 600,000 of the Company’s outstanding shares at closing, as part of the Company’s Restricted Stock Unit Plan, subject to the approval of the Company’s Board of Directors. In the event that his employment is terminated by the Company without Cause (as defined in the Employment Agreement), or is terminated by Mr. Green for Good Reason (as defined in the Employment Agreement), after six months of employment, and he signs and does not revoke a standard release of claims with the Company in a form reasonably satisfactory to the Company’s Board of Directors (a “Release”), which Release becomes irrevocable no later than sixty (60) days (the “Release Deadline”), after the date of his termination of employment (the “Termination Date”) he will be entitled to the following severance payment, as follows: (a) if the Termination Date is after six (6) months’ of employment, but before he has completed 12 months’ of employment, he will receive three (3) months’ salary; and (b) if the Termination Date is after 12 months’ employment he will receive six (6) months’ salary. If the Release does not become effective and irrevocable by the Release Deadline, he will forfeit any right to severance.

The Employment Agreement for Ms. Embree provides for $225,000 annual salary, eligibility to receive an annual cash performance bonus of twenty-five percent (25%) of her annual salary upon her achievement of the performance goals set by the Company’s CEO and Board of Directors, and eligibility to receive 260,000 of the Company’s outstanding shares, as part of the Company’s Restricted Stock Unit Plan, subject to the approval of the Company’s Board of Directors. In the event that her employment with the Company is terminated by the Company without Cause (as defined in the Employment Agreement) or is terminated by Ms. Embree for Good Reason (as defined in the Employment Agreement) she will receive six (6) months’ salary as a Severance Payment.

The Employment Agreement for Mr. Casey provides for $144,000 annual salary, eligible to receive 147,000 shares of stock upon the successful fundraising of an amount equal to or greater than $5,000,000 and, as part of the Company’s Restricted Stock Unit Plan, further equity will be rewarded to Mr. Casey subject to the approval of the Company’s Board of Directors. In the event that his employment with the Company is terminated by the Company without Cause (as defined in the Employment Agreement) or is terminated by Mr. Casey for Good Reason (as defined in the Employment Agreement) he will receive six (6) months’ salary as a Severance Payment.

Stock Purchase Agreement

On June 28, 2023, the Company and Data Knights entered into a Securities Purchase Agreement (the “PIPE SPA”) with certain investors (collectively referred to herein as the “Purchasers”) for PIPE financing in the aggregate original principal amount of $1,595,744.70 and the purchase price of $1.5 million. Pursuant to the Securities Purchase Agreement, Data Knights will issue and sell to each of the Purchasers, a new series of senior secured convertible notes (the “PIPE Notes”), which are convertible into shares of Common Stock at the Purchasers election at a conversion price equal to the lower of (i) $10.00 per share, and (ii) 92.5% of the lowest volume weighted average trading price for the ten (10) Trading Days immediately preceding the Conversion Date. The Purchasers’ $1.5 million investment in the PIPE Notes closed and funded contemporaneous to the Closing of the Business Combination. Effective immediately prior to the Closing, Data Knights issued the PIPE Notes to the Purchasers pursuant to the private offering rules under the Securities Act of 1933, as amended (the “Securities Act”).

Government Regulation

Many aspects of our businesses are regulated by federal and state laws, rules and regulations. Accordingly, we maintain a robust compliance program aimed at ensuring we operate our business in compliance with all existing legal requirements material to the operation of our businesses. There are, however, occasionally uncertainties involving the application of various legal requirements, the violation of which could result in, among other things, fines or other sanctions.See “Risk Factors” for additional detail.

Regulation of Patient Information. Our information management services relate to the processing of information regarding patient diagnosis and treatment of disease and are, therefore, subject to substantial governmental regulation. In addition, the confidentiality of patient-specific information and the circumstances under which such patient-specific records may be released for inclusion in our databases or used in other aspects of our business is heavily regulated. Federal, state and foreign governments are contemplating or have proposed or adopted additional legislation governing the possession, use and dissemination of personal data, such as personal health information and personal financial data, as well as security breach notification rules for loss or theft of such data. Additional legislation or regulation of this type might, among other things, require us to implement additional security measures and processes or bring within the legislation or regulation deidentified health or other data, each of which may require substantial expenditures or limit our ability to offer some of our services.

In particular, personal health information is recognized as a special, sensitive category of personal information, subject to additional mandatory protections. Violations of data protection regulations are subject to administrative penalties, civil money penalties and criminal prosecution, including corporate fines and personal liability.

Data Privacy

Certain of our operations are subject to regulation under the administrative simplification provisions of the Health Insurance Portability and Accountability Act of 1996, as amended (HIPAA). Federal regulations related to HIPAA contain minimum standards for electronic transactions and code sets and for the privacy and security of protected health information. Patient health information is among the most sensitive of personal information, and it is critically important that information about an individual’s healthcare is properly protected from inappropriate access, use and disclosure. Real world evidence — information that allows us to examine actual practices and outcomes — is essential to increase access to care, improve outcomes, and lower costs.

OneMedNet uses a wide variety of privacy-enhancing technologies and safeguards to protect individual privacy while generating and analyzing information on a scale that helps healthcare stakeholders identify disease patterns and correlate with the precise treatment path and therapy needed for better outcomes. We employ a wide variety of methods to manage privacy requirements, including:

We have relied on expertise in the industry with de-identifying data. Our capabilities allow us to render data non-identified while still maintaining data utility, thus protecting privacy while still advancing innovation. Not only do we make use of de-identification techniques with respect to the data we hold, but we also share our expertise in this area with policymakers, regulators and others to help them understand de-identification methodologies and practical considerations to avoid re-identification risk. We operate in more than 100 countries around the world, many of which have data protection and privacy laws and regulations based on similar core principles (*e.g.,*openness, accountability, security safeguards, etc.). We apply those principles globally and augment our practices to address local laws, contractual obligations and other data privacy requirements.

Our Compliance team, led by our Chief Compliance Officer, is comprised of privacy professionals and privacy law experts who drive our strategy and develop and manage our policies and standards. The Compliance team provides subject matter expertise related to the proper management of all data types. In addition, our Compliance team liaises with our Legal, IT, Information Security and other teams so that privacy requirements are addressed in technology, contracting, offerings and other business activities.

The OneMedNet Privacy Policy (the “Privacy Policy”) is our foundational privacy policy. It explains how, when applicable, we collect, hold, use and disclose personal information, including that of our personnel, consumers, healthcare professionals, patients, medical research subjects, clinical investigators, customers, suppliers, vendors, business partners and investors.

Regulatory Quality Compliance (FDA 21 CFR Part 11)

OneMedNet provides high-quality, de-identified, regulatory-grade imaging and clinical data; as such OneMedNet adheres to all applicable local and Federal regulatory quality requirements, including but not limited to FDA 21 CFR Part 11. OneMedNet maintains a rigorous and ongoing internal quality management system to enable the organization to produce the highest quality regulatory compliant clinical data for our clients and consumers. This program includes:

Organizational Structure

The following is a current organizational chart of our Company:

Human Capital Resources

Our workforce is comprised of approximately 20 employees (as of December 31, 2023), including approximately 0 part-time employees (references herein to “employees” include to the employees of our subsidiaries). Our Board of Directors and its committees oversee human capital matters through regular reporting from management and advisors.

Diversity, Equity and Inclusion

We are committed to fostering a culture of inclusion that embraces and supports our patients, colleagues, partners, physicians and communities. Our policies prohibit discrimination on the basis of age, gender, disability, race, color, ancestry, citizenship, religion, pregnancy, sexual orientation, gender identity or expression, national origin, medical condition, marital status, veteran status, payment source or ability, or any other basis prohibited by federal, state or local law.

Compensation and Benefits

We provide competitive compensation and benefits programs to help meet the needs of our employees. In addition to salaries, these programs (which vary by location) include a 2024 Stock Option Plan, a 401(k) Plan, health care and insurance benefits, health savings and flexible spending accounts, paid time off, family leave, family care resources, flexible work schedules, employee assistance programs, tuition and student loan assistance and on-site services, such as cafeterias and fitness centers, among many others.

Facilities

Prior to the closing of the Business Combination, the Company’s executive offices were located at Unit G6, Frome Business Park, Manor Road, Frome, United Kingdom, BA11 4FN and its telephone number was +44 203 833 4000. The Company agreed to pay ARC Group Ltd., an affiliate of the Sponsor, up to an amount of $10,000 per month for office space, secretarial and administrative support. For the nine months ended September 30, 2023 and 2022, we had incurred $60,000 in fees under this agreement, respectively. Upon completion of our Business Combination, the Company ceased paying these monthly fees.

After the closing of the Business Combination, our headquarters is located at 6385 Old Shady Oak Road, Suite 250, Eden Prairie, MN 55344 and our telephone number is (800) 918-7189, where we lease and occupy our office space with an aggregate floor area of approximately 67 square feet from unrelated third parties under operating lease agreements. We believe the current office space is adequate for our current operations and are adequate for our anticipated future needs.

Implications of Being an Emerging Growth Company

As a company with less than $1.235 billion in revenues during our last fiscal year, we qualify as an emerging growth company as defined in the Jumpstart Our Business Startups Act (“JOBS Act”) enacted in 2012. As an emerging growth company, we expect to take advantage of reduced reporting requirements that are otherwise applicable to public companies. These provisions include, but are not limited to: