OneMedNet Corp

Company Overview

OneMedNet is a global provider of clinical imaging innovation and curator of regulatory-grade Imaging Real World Data (“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 (as defined below), an emerging market, and provides regulatory-grade image-centric iRWDTM that exactly matches OneMedNet’s life science partners case selection protocols and paves the way for Real World Evidence (as defined below).

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 Republic of Ireland.

OneMedNet continued to innovate by responding to the demand for and utilization of Real World Data (as defined below) (“RWD”) and Real World Evidence (“RWE”), 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 network of 1,400 healthcare sites, OneMedNet has the immediate ability to quickly search and extensively curate multi-layer data from a federated group of healthcare facilities. The term “healthcare sites” 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 has access to more than 1,400 sites who provide regulatory grade data to us.

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. The federated network allows OneMedNet to access the following data to provide to research as RWD.

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, life science companies contribute to patient care advancements in more meaningful ways. Moreover, life sciences improve life science companies’ 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 believe we unleash the power of research-grade image-centric iRWDTM that is curated to meet every cohort requirement and stand up to 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

We believe OneMedNet has been a leader in the business of extracting, securing, and transferring medical data for 10+ years. Doing so requires specialized expertise in:

Attaining in-house expertise in all essential elements is a challenge and we believe deters many organizations from 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 OneMedNet is a leader in the 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 over 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 are indexed at each network site using state-of-the-art AI/ML technology. This typically includes electronic health records (“EHR”), radiology, cardiology, lab, pathology and more. Our in-house clinical team performs intensive curation of the data so that results meet the specifications and requirements of life science Data Collection Protocol (“DCP”) - regardless of the complexity.

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

OneMedNet’s data is fully de-identified using a multi-step quality control process and goes beyond protected health information (“PHI”) to include personally identifiable information (“PII”), 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 a team of highly experienced and clinically trained data curators. This team appreciates the complexity and criticality of clinical data and can effectively communicate with both providers 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 for the Study of Drug Development 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 EHR, claims, and 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 EHR, 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 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 FDA. 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, EHR, 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 FDA or the European Medicines Agency (“EMA”), 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 relied on heavily relates to oncology approvals. The FDA’s Oncology Center of Excellence presented an analysis of this at the 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 FDA’s July 2021 approval of a new indication for Astella Pharma Inc.’s’ 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 FDA’s December 2021 approval of the supplemental BLA (Biological License Application) 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. 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, the largest multisite distributed database in the world dedicated to medical product safety, 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 EHR and case report forms or claims, and 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 fills 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 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, a traditional clinical trial 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 companies 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 EHR 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 (“EMR”) 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 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, in late 2022, 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 EHR 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 Real World Evidence. 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 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 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.

Real World Evidence solutions services allow pharmaceutical companies and healthcare providers as well as payers by providing efficient management of operations and accelerating 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 Real World Evidence 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 Real World Evidence 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 $7.51 billion in 2024 and is expected to exhibit a CAGR of 9.1% during the forecast period (2024-2031).

Our Long-Term Growth Strategies

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

Corporate Information

Data Knights was 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, a subsidiary of Data Knights merged with and into OneMedNet Solutions Corporation (formerly named OneMedNet Corporation) (“Legacy ONMD”), with Legacy ONMD surviving as a wholly-owned subsidiary of Data Knights (the “Business Combination”). In connection with the Business Combination, Data Knights changed its name to “OneMedNet Corporation.”

We are located at 6385 Old Shady Oak Road, Suite 250, Eden Prairie, MN 55344 and reachable by telephone on 800-918-7189.

Legacy ONMD was incorporated in the State of Delaware on November 20, 2015. Its wholly-owned subsidiary, OneMedNet Technologies (Canada) Inc. (“ONMD Canada”), was incorporated on October 16, 2015 under the provisions of the Business Corporations Act of British Columbia. ONMD Canada’s functional currency is the Canadian dollar.

Recent Developments

Closing of Business Combination

On November 7, 2023, following the approval of the Merger Agreement and the transactions contemplated thereby at the special meeting of the shareholders of Data Knights held on October 17, 2023 (the “Special Meeting”), Merger Sub merged with and into Legacy ONMD pursuant to the Merger Agreement (the “Merger”), with Legacy ONMD surviving the Merger as a wholly-owned subsidiary of Data Knights. Following Closing, Data Knights changed its name to “OneMedNet Corporation.”

The Business Combination was accounted for as a reverse recapitalization in accordance with U.S. generally accepted accounting principles (“GAAP”). Under this method of accounting, Data Knights was treated as the acquired company and Legacy ONMD was treated as the acquirer for financial statement reporting purposes.

Standby Equity Purchase Agreement

On June 17, 2024, we entered into a Standby Equity Purchase Agreement, or the SEPA, with Yorkville. Under the SEPA, we have the right to sell to Yorkville up to $25.0 million of our common stock, subject to certain limitations and conditions set forth in the SEPA, from time to time, over a 24-month period. Sales of our common stock to Yorkville under the SEPA, and the timing of any such sales, are at our option, and we are under no obligation to sell any shares of our common stock to Yorkville under the SEPA except in connection with notices that may be submitted by Yorkville, in certain circumstances as described below. Upon the satisfaction of the conditions precedent in the SEPA, which include having a resale shelf for shares of our common stock issued to Yorkville declared effective, we have the right to direct Yorkville to purchase a specified number of shares of our common stock by delivering written notice. Such purchase is referred to as an “Advance.” An Advance may not exceed 100% of the average of the daily trading volume of our Class A common stock on The Nasdaq Capital Market, or Nasdaq, during the five consecutive trading days immediately preceding the written notice. Yorkville will generally purchase shares of our common stock pursuant to an Advance at a price per share equal to 97% of the lowest daily volume weighted average price, or VWAP, on Nasdaq during the three consecutive trading days commencing on the date of the delivery of the written notice (unless we specify a minimum acceptable price or there is no VWAP on the subject trading day).

Upon entry into the SEPA, we issued Yorkville a $1.5 million convertible promissory note for $1.35 million in cash (after a 10% original issue discount), or the Initial Advance. The note bears interest at an annual rate equal to 0.0% (increased to 18.0% in the event of default as provided in the note) and matures June 17, 2025. The note is convertible by Yorkville into shares of common stock at an aggregate purchase price based on a price per share equal to the lower of (a) $1.3408 per share (subject to downward reset upon the filing of the resale registration statement described below) or (b) 90% of the lowest daily volume-weighted average price (“VWAP”) of the Common Stock on Nasdaq during the seven trading days immediately prior to each conversion (the “Variable Price”), but which Variable Price may not be lower than the Floor Price then in effect. The “Floor Price” is $0.28 per share, subject to the Company’s option to reduce the Floor Price to any amounts set forth in a written notice to Yorkville. Upon the occurrence and during the continuation of an event of default (as defined in the note), the note will become immediately due and payable. The issuance of our common stock upon conversion of the note and otherwise under the SEPA is capped at 19.9% of our outstanding common stock as of June 17, 2024 in order to comply with applicable Nasdaq rules. Further, the note and SEPA include a beneficial ownership blocker for Yorkville such that Yorkville may not be deemed the beneficial owner of more than 4.99% of our common stock.

The SEPA will automatically terminate on the earliest to occur of (i) the first day of the month next following the 24-month anniversary of the date of the SEPA or (ii) the date on which Yorkville shall have made payment of for shares of our common stock equal to $25.0 million. We have the right to terminate the SEPA at no cost or penalty upon five trading days’ prior written notice to Yorkville, provided that there are no outstanding advances for which shares of our common stock need to be issued and the convertible note (Initial Advance) has been paid in full. We and Yorkville may also agree to terminate the SEPA by mutual written consent. As consideration for Yorkville’s commitment to purchase the shares of our Class A common stock pursuant to the SEPA, we paid Yorkville a $25 thousand cash structuring fee and a commitment fee equal to 526,312 shares of our common stock.

In connection with the entry into the SEPA, on June 17, 2024, we entered into a registration rights agreement with Yorkville, pursuant to which we agreed to file with the SEC no later than August 30, 2024, a registration statement for the resale by Yorkville of the shares of our common stock issued under the SEPA (including the commitment fee shares). We agreed to use commercially reasonable efforts to have such registration statement declared effective within 30 days of such filing and to maintain the effectiveness of such registration statement during the 24-month commitment period. We will not have the ability to request any Advances under the SEPA (nor may Yorkville convert the Initial Advance into our common stock) until such resale registration statement is declared effective by the SEC. As of the filing date of this Annual Report, we have not filed a registration statement with the SEC.

Private Placements

July 2024 Financings

On July 23, 2024, we entered into a securities purchase agreement with Off the Chain Capital, LLC (“OTC”), pursuant to which weagreed to issue and sell to OTC 1,297,059 shares of our Common Stock at a price of $1.0278 per share and pre-funded warrants exercisable for 1,323,530 shares of our Common Stock at an exercise price of $1.0278 per share. OTC was required to prepay the exercise price for the pre-funded warrants, other than $0.0001 per share. The warrants and pre-funded warrants will be exercisable at any time after the date of issuance and will not expire. OTC is entitled to receive dividends on the pre-funded warrants, if declared, on an as-if-converted-to-common-stock basis, and in the same form as dividends actually paid on shares of our Common Stock.

On July 25, 2024, we entered into a securities purchase agreement with Discovery Capital Management, LLC (“Discovery”), pursuant to which weagreed to issue and sell 2,301,791 shares of our Common Stock at a price of $0.85 per share.

We received net proceeds of approximately $4.5 million from the July 2024 private placements, after deducting offering expenses of $0.1 million.

September 2024 Financing

On September 24, 2024, we entered into another securities purchase agreement with OTC, pursuant to which we agreed to issue and sell to OTC 1,918,591 shares of our Common Stock at a price of $0.65 per share, warrants exercisable for 133,095 shares of our Common Stock at an exercise price of $0.325 per share, and pre-funded warrants exercisable for 743,314 shares of our Common Stock at an exercise price of $0.65 per share. OTC was required to prepay the exercise price for the pre-funded warrants, other than $0.0001 per share. The warrants and pre-funded warrants will be exercisable at any time after the date of issuance and will not expire. OTC is entitled to receive dividends on the pre-funded warrants, if declared, on an as-if-converted-to-common-stock basis, and in the same form as dividends actually paid on shares of our Common Stock.

We received net proceeds of approximately $1.7 million, after deducting an immaterial amount of offering expenses. We have not yet issued the 1,918,591 shares of our Common Stock in order to keep OTC’s ownership percentage below a defined threshold.

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, Information Technology, 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 high quality regulatory compliant clinical data for our clients and consumers. This program includes:

Human Capital Resources

Our workforce is comprised of approximately 22 employees (as of December 31, 2024), including approximately 1 part-time employee (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.

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 of the employee) include a 2022 Stock Option Plan, health care and insurance benefits, health savings and flexible spending accounts, paid time off, family leave, family care resources, and employee assistance programs, among many others.

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:

Available Information

We file with, or furnish to, the SEC reports, including our annual report on Form 10-K, quarterly reports on Form 10-Q, current reports on Form 8-K and amendments to those reports pursuant to Section 13(a) or 15(d) of the Exchange Act. These reports are available free of charge via EDGAR through the SEC website (www.sec.gov) and are also available free of charge on our corporate website (https://www.onemednet.com) as soon as reasonably practicable after they are electronically filed with or furnished to the SEC. The foregoing website addresses are provided as inactive textual references only. The information provided on our website (or any other website referred to in this Annual Report) is not part of this report and is not incorporated by reference as part of this Annual Report.