Tempus AI, Inc. (Tempus) operates as a healthcare technology company. The company focuses on bringing artificial intelligence and machine learning to healthcare in order to improve the care of patients across multiple diseases.
The company combines the results of laboratory tests with other multimodal datasets to improve patient care by supporting all parties in the healthcare ecosystem, including physicians, researchers, payers, and pharmaceutical companies. The company primarily derives reven...
Tempus AI, Inc. (Tempus) operates as a healthcare technology company. The company focuses on bringing artificial intelligence and machine learning to healthcare in order to improve the care of patients across multiple diseases.
The company combines the results of laboratory tests with other multimodal datasets to improve patient care by supporting all parties in the healthcare ecosystem, including physicians, researchers, payers, and pharmaceutical companies. The company primarily derives revenue from selling comprehensive genetic testing to physicians and large academic research institutions, licensing data to third parties, matching patients to clinical trials, and related services.
The company makes tests intelligent by connecting laboratory results to a patient’s own clinical data, thereby personalizing the results. The company’s novel insight was realizing that all laboratory test results, genomic or otherwise, could be contextualized for a specific patient based upon that patient’s unique characteristics, and technology could therefore guide therapy selection and treatment decisions to allow each patient to progress on their its unique path. The company’s proprietary technology has allowed it to amass what it considers to be one of the largest libraries of clinical and molecular oncology data in the world. The company’s is to embed AI, including generative AI, throughout every aspect of diagnostics to enable physicians and researchers to make personalized, data-driven decisions that improve patient care.
The company established new data pipes, going to and from providers, to allow for the free exchange of data between physicians, who interpret data, and diagnostic and life science companies, who provide data, integrating relevant clinical data, such as outcomes, or adverse events, which are essential for many clinical decisions. Without this capability, that data would continue to accumulate without impacting patient care. To accomplish this, the company built both a technology platform to free healthcare data from silos and an operating system to make this data useful, the combination of which it refers to as the company’s Platform. The company’s Platform connects multiple stakeholders within the larger healthcare ecosystem, often in near real time, to assemble and integrate the data the company collects, thereby providing an opportunity for physicians to make data-driven decisions in the clinic and for researchers to discover and develop therapeutics.
Tempus is a technology company focused on healthcare that straddles two converging worlds. The company strives to combine deep healthcare expertise, providing next-generation diagnostics across multiple disease areas, with leading technology capabilities, harnessing the power of data and analytics to help personalize medicine. The company endeavors to unlock the true power of precision medicine by creating Intelligent Diagnostics through the practical application of artificial intelligence, or AI, in healthcare. Intelligent Diagnostics use AI, including generative AI, to make laboratory tests more accurate, tailored, and personal. Unlike traditional diagnostic labs, the company can incorporate unique patient information, such as clinical, molecular, and imaging data, with the goal of making its tests more intelligent and its results more insightful. Unlike other technology companies, the company is deeply rooted in clinical care delivery as one of the largest sequencers of cancer patients, and patients with other diseases, in the United States.
The company’s Platform includes proprietary software and dedicated data pipelines that create a network of healthcare institutions through approximately 700 unique data connections, many of which supply the company with complex multimodal data in near real time, across approximately 3,000 healthcare institutions that order its products and services. Healthcare institutions supply the company with this data in its capacity as a covered entity (for example, when the company provides Next Generation Sequencing, or NGS, services on behalf of a patient), or as a business associate (for example, when the company provides clinical trial matching services or data de-identification and structuring services). In addition to the data it receives in these capacities, the company currently has a limited number of paid license agreements through which it acquires de-identified data directly from healthcare associations or institutions, and in certain circumstances the company covers the actual direct costs associated with the technical integrations needed to create a data connection. The company then integrates this data into a unified multimodal database through which it offers numerous analytical and decision support capabilities to its customers. The company establishes dedicated and integrated data connections with healthcare institutions to enhance the information it provides in its clinical reports, to increase the effectiveness of its clinical trial matching services, and to enable the company’s AI Applications product line, which has the ability to transform healthcare.
The company has developed multiple products each based on its Platform that has allowed it to invest in structuring and harmonizing multimodal data, which is a necessary precursor for deploying AI at scale. The company’s products are organized under three product lines, Genomics, Data, and AI Applications or Algos. Each product line is designed to enable and enhance the others, thereby creating network effects in each of the markets in which the company operates. The company’s business model allows pharmaceutical and biotechnology companies to unlock value from the data it collects and allows it to monetize a de-identified copy of that data, in different ways across the company’s different product lines. The more data the company collects, the smarter its tests become, the more applications the company launch, the more physicians join its network, further growing its database, making its tests more precise for clinicians and its database more valuable for researchers.
The company’s Genomics product line leverages its laboratories to provide NGS diagnostics, PCR profiling, and other anatomic and molecular pathology testing to healthcare providers, life sciences companies, researchers, and other third parties. However, unlike other laboratory diagnostic testing providers, many of its tests are connected to clinical data in some manner, which allows its suite of tests to be self-learning and become more accurate with each new test that the company runs. The company’s Data and Services product line facilitates drug discovery and development for life sciences companies through two primary products, Insights and Trials. Through its Insights product, the company licenses de-identified libraries of linked clinical, molecular, and imaging data and provide a suite of analytic and cloud-and-compute tools to pharmaceutical and biotechnology companies. The company’s second product within its Data and Services product line, Trials, leverages the broad network of physicians the company works with in oncology to provide clinical trial support for pharmaceutical companies that are looking to reach hard-to-find and underserved patient populations. The company’s third product line, AI Applications, is focused on developing and providing diagnostics that are algorithmic in nature, implementing new software as a medical device, and building and deploying clinical decision support tools. The primary product of AI Applications is currently ‘Next,’ an AI platform that leverages machine learning to apply an ‘intelligent layer’ onto routinely generated data to proactively identify and minimize care gaps for oncology and cardiology patients. As this product gains adoption, the company intends to leverage large language models, generative AI algorithms, and its vast database of de-identified data to develop algorithmic diagnostics designed to identify these patients earlier in their disease progression, when treatments are most effective.
The Tempus Platform
Tempus set out to build proprietary technology to implement Intelligent Diagnostics and to facilitate access to, and use of, the resulting datasets. The Tempus Platform connects multiple stakeholders within the larger healthcare ecosystem and provides both the technical infrastructure for what the company consider to be one of the world’s largest libraries of matched clinical and molecular data, and an operating system to make that information useful. The company’s Platform is end-to-end and vertically integrated. It allows the company to ingest data from providers, perform diagnostic testing upon request, generate results leveraging its multimodal database, and provide clinical context for a specific patient. Below is a graphic illustrating its Platform’s core functionality.
The same is true in neuropsychiatry. A heterogeneous population suffers from numerous neurological disorder subtypes, such as depression, anxiety, bipolar disorder, and other psychiatric conditions. Like oncology, there is a diverse patient population and several prescribed antidepressants, often based on trial and error. Further, the complexity of oncology, neuropsychiatry, and many other major causes of morbidity necessitate a multimodal data approach, as any single modality (e.g., DNA-only) is unlikely to provide enough information to differentiate meaningful patient subgroups.
Facilitated by the company’s relationships with many leading hospitals across the healthcare system in the United States, the company is well positioned to introduce precision medicine at scale across multiple disease categories and drive adoption of its Platform and novel AI solutions. The company is leveraging its ability to collect, structure and harmonize data, and deploy AI on large datasets to facilitate precision medicine broadly. The company initially deployed its Platform in oncology, expanded substantially within oncology, and recently extended into neuropsychiatry, radiology, and cardiology.
Core Elements of its Platform
The Tempus Platform combines multiple elements into a vertically integrated infrastructure that enables the company to ingest data from providers, structure and harmonize the data into a common database, provide laboratory diagnostic testing, and deliver personalized results that provide clinical context by leveraging its data. The company offers closed-loop, full- stack, bi-directional integrations between a clinician’s desktop and its laboratory diagnostic capabilities, analytics platform, and repository of multimodal data. The company’s scaled, interconnected provider network covers more than 50% of U.S. oncologists and provides it with broad data rights, including the rights to longitudinally updated data from time to time. The combination of its Platform and vast provider network yields a powerful flywheel that continues to become more accurate and precise as more patients are added, thereby compounding the network effects of its offering.
Ingestion and Generation of Data
The company ingests healthcare data in near real time and at scale, including molecular, clinical, and imaging data. Between its sequencing and data collection efforts, the company is connected in some way to more than 50% of all oncologists practicing in the United States, along with a growing number of patients in neuropsychiatry, cardiology, and infectious disease. The company’s methods for collecting and creating data include the following:
Ingesting data through its relationships and partnerships with healthcare providers. The company has developed proprietary tools to establish approximately 700 direct data connections, across approximately 3,000 hospitals, many of which are bi-directional. The company has established relationships with hundreds of provider networks, including more than 65% of all academic medical centers in the United States. To obtain data from these sources, the company uses a variety of near real-time connections (e.g., HL7, FHIR) and batch data exchanges. Healthcare institutions supply the company with this data in its capacity as a covered entity (for example, when the company provides NGS services on behalf of a patient), or as a business associate (for example, when the company provides clinical trial matching services or data de-identification and structuring services). The company ingests and structures data using optical character recognition, or OCR, natural language processing, or NLP, and proprietary workflow tools along with manual data curation. The company’s proprietary tools connect to a provider’s EHR system, data warehouse, or third-party data provider to pull out relevant structured and unstructured data that the provider has agreed to provide to Tempus, including longitudinal follow-up data to the extent the provider has made such data available. To facilitate these data- sharing relationships, the company has developed software products and services that align to its customers’ interests by helping providers use its software tools to improve patient care. In certain circumstances, the company covers the actual direct costs associated with the technical integrations needed to create a data connection. The company covers these costs to help facilitate providers’ contribution of data and their corresponding use of its products, which then makes its tests more intelligent and helps them to facilitate the delivery of better care. The company generally retains the rights it acquires in de-identified data even if its contractual obligations expire or are terminated.
Relationships with industry associations. In addition to healthcare providers, the company works with numerous industry associations in the United States, such as ASCO. Under its collaboration with ASCO, the company structures and distributes the oncology data ASCO collects as part of CancerLinq, which is their oncology data effort. The company works with other large associations such as ONCare Alliance, LLC (surviving entity after merger of the National Cancer Care Alliance and the Quality Cancer Care Alliance), and has agreements in place with large integrated community practices. While the company’s relationships in oncology are widespread, it is making inroads in other disease areas. For example, the company is working with a large hospital network to train algorithmic models based on a de-identified subset of approximately 3.5 million electrocardiograms, or ECGs, across more than 800,000 patients, with decades of longitudinal clinical data, including outcome and response data. The company also has agreements with numerous other institutions through both its sequencing and data efforts to collect and structure multimodal infectious disease data and have entered into a variety of partnerships and collaborations across neuropsychiatry, diabetes, and cardiology giving the company access to additional clinical data.
Laboratory Diagnostics: In addition to its dedicated data pipelines, the company generates data for its Platform from its four high-throughput diagnostic testing labs in Chicago, Atlanta, Raleigh, and Aliso Viejo. The company’s labs offer a range of anatomical and molecular NGS tests, including a broad portfolio of solid tumor and liquid biopsy cancer tests. The company’s laboratory offerings enable it to populate its database with connected and comprehensive molecular, clinical, and morphologic data that has been de-identified. The company also makes available an unrestricted copy of the raw files containing the rich data the company generates in the laboratory, along with any clinical data it curate, to the providers who order its tests, to further enable their own research efforts. In February 2025, the company acquired Ambry Genetics Corporation, or Ambry, a leader in hereditary cancer screening and the supplier of its germline sequencing (Tempus|xG) for hereditary cancer risk. With the acquisition of Ambry, the company can leverage its vast amounts of data to augment its current data offerings. Further, Ambry’s offerings span multiple disease areas, enabling the company to expand beyond oncology into new categories, such as pediatrics, rare disease, cardiology, reproductive health and immunology. Additionally, Ambry’s significant laboratory capabilities on the west coast will help increase its overall footprint in the country.
The company ingests and generates a variety of different types of data from different sources. The following represents selected data modalities that it collects and aggregate into its database.
Proprietary Data Processing
Once data is ingested, the company deploys proprietary clinical data abstraction tools, including natural language processing, optical character recognition, and its abstraction software, to structure, harmonize, and de-identify the data it collects. The company has developed various software tools, including algorithmic agents that leverage large language models, to organize millions of records into a common format that spans a variety of data types. For example, the company organizes clinical data from unstructured documents and structured EHR fields, and typically digitize whole-slide pathology images as part of its clinical workflow. The company then combines this data with the molecular data that it generates in its labs or process from third parties, giving it a more comprehensive profile of patients. Unstructured data housed in physician notes and other documents is processed using OCR and NLP, mapped to Tempus’ Medical Ontology, and routed to data abstractors for further curation and quality control. Typically, the company receives identified data, either in its capacity as a covered entity under the Health Insurance Portability and Accountability Act, or HIPAA, or to the extent it has a business associate agreement with the provider. Following abstraction and structuring, it de-identifies data and only retain the resulting de-identified dataset, other than through its obligations to retain selected identified data as a covered entity providing laboratory tests to clinicians. Many clinicians who order Tempus tests clinically are also involved in research related activities. By making this organized and structured data available to the clinicians (along with raw files associated with the testing it performs) the company serves, those clinicians can use the data to further their own research efforts to help patients.
Proprietary Multimodal Database
Tempus is attempting to solve this problem by democratizing the use of near-real time molecular, clinical, and imaging data by embedding its solutions into the clinical care of patients. As the company’s testing volume has grown, and as its dedicated data pipelines have expanded, the size of the company’s database has increased exponentially. Since the company launched its Platform in 2016, Tempus has amassed over 900 million documents, across more than 7.3 million de-identified patient records, including over 1.1 billion pages of rich clinical text that the company uses to train its large language models. The database also includes over 1,400,000 records with imaging data, more than 1,300,000 with matched clinical records linked with genomic information, and more than 260,000 with full transcriptomic profiles. The breadth of its database, the quality and diversity of its data, as well as its regularly updating nature, allow the company to offer a variety of AI-enabled solutions to the market. The company also retains the rights to broadly commercialize de-identified data.
Proprietary Software Tools and Solutions
The company has developed numerous software tools and applications to help make its services accessible to multiple constituencies within the healthcare ecosystem and support its various product lines. The company is able to not only train and validate some of these AI models for research use, but it can also develop them into clinical-grade algorithmic tests, or Algos, and deploy them clinically as part of routine care.
The company leverages its varied expertise and extensive resources to continuously monitor and review the statistical performance of the models used across its Platform to ensure performance and prevent degradation.
External Facing Applications
The company has two primary software applications that serve as interfaces for different markets and allow its customers to interact with its Platform. Hub is the company’s clinical application for physicians and other healthcare providers and is used primarily in its Genomics product line as an end-to-end application for healthcare providers who use its NGS tests. Lens is the company’s application for life sciences customers and other healthcare researchers, launched in May 2021. Lens is aligned with Insights, one of its products within Data, and allows users to identify, license, and ultimately analyze cohorts of data for research purposes. The company typically enables its customers to access free or charge certain software applications (like Hub) and certain features of other applications (like Lens). However, in some cases the company may charge for access to Lens when a customer is interested in some form of customization or access to Lens’ full suite of capabilities.
Hub
Hub can be accessed on the web or through the company’s mobile applications. Hub enables physicians and other providers to interact with its Platform, place orders for its laboratory tests, track them through the sequencing process, view results, and develop treatment plans using the other information Tempus makes available. Hub streamlines and automates what previously required a significant investment of both time and resources for those ordering and delivering genomic reports.
A physician’s experience, through Hub, typically begins with its online ordering feature, which presents providers with Tempus’ various test options and guides users through the ordering process. Once Tempus has processed an order and sequenced a specimen, Hub synthesizes information across its various tests, orders, and patients, and presents the information in a consumer-friendly interface. For example, Order Summary synthesizes information from various clinical orders, test results, and other information relevant to a patient’s course of treatment. A typical patient might have multiple sequencing events over time. Hub visually presents all of a patient’s results side-by-side, so a treating physician can comprehensively view how a patient’s disease has changed over time, including in response to therapy. Hub also provides care teams a robust set of search and filtering tools so they can navigate its Platform. Physicians can use Hub to identify similarly situated patients or patient sub-groups, including by specific molecular alteration. Physicians can also export and download the resulting dataset for further analysis.
Hub offers additional functionality that goes beyond ordering and presenting clinical results. The company’s clinical trial system, for example, handles the complexities of matching patients to clinical trials, by synthesizing clinical and molecular data matched against inclusion and exclusion criteria for the trial. It even allows physicians to activate their point of care as a clinical trial site, if approved by the trial sponsor, in order to easily enroll patients who would otherwise not have access to experimental therapies. The proprietary features within Hub put powerful analytics in the hands of physicians, allowing them to pursue research opportunities using accessible molecular data, and explore immune insights, such as HLA type, immune infiltrates and neoantigens. Finally, Time on Therapy provides physicians a view into the Tempus Precision Medicine Library, which includes the treatment paths of patients within its de-identified database who display similar molecular or phenotypic profiles to their own patients. These tools enable new patients to potentially benefit from the experience of those that came before.
One example of an AI model whose results are available within Hub, and which illustrates a typical development and validation process for its AI models, is its Tumor Origin, or TO, algorithm. The company’s TO algorithm predicts the site of origin for cancer patients whose primary tumor site is unknown using machine learning models trained on tumor RNA expression results from its de-identified multimodal database. The company began developing its TO algorithm in 2019, and it was first deployed in a clinical setting in 2021. The company developed and trained the TO algorithm, like other machine learning models, by adopting best practices for AI model development. For example, in developing the TO algorithm, the company explored distinct model architectures (logistic regression, random forests and neural networks) and feature selection methods, and the company utilized multiple cross validation techniques using both its own and independent third-party datasets. After its launch, the company continues to monitor the performance of the TO algorithm by using advanced statistical methods to detect potential model drift or degradation over time. Each TO prediction is reviewed by its board-certified pathologists for consistency with underlying data, and the distribution of expected cases is reviewed and assessed against the expected distribution of diagnoses.
Lens
Lens is the company’s software application for life sciences and advanced precision research. The company designed Lens to expose its multimodal, de-identified dataset to two main constituencies: clinicians interested in exploring data related both to their own patients and to similarly situated patients from the broader Tempus dataset, and pharmaceutical and biotechnology clients that are focused on drug discovery and development and want to explore its dataset and/or supplement their own analytics with its tools and data.
For clinicians, Lens helps users filter its multimodal database to identify groups of patients that meet their research requirements. It allows browsing, segmenting, selecting, and analyzing cohorts of patients using a variety of clinical, molecular, and demographic characteristics. The company generally makes these aspects of Lens available to its customers without charge because such access helps its customers identify data cohorts of interest and facilitates data licensing opportunities.
In addition to this basic functionality, Lens allows advanced computational users to perform robust analytics using its cloud-and-compute infrastructure and modeling tool set. The company launched certain of these advanced features in May 2021, one of which is called Notebooks, a proprietary tool that allows users to run their own AI models within its cloud-and-compute environment, taking advantage of fast and streamlined access to its data and computational infrastructure, and saving researchers time and money. Over time, the company intends to enter into separate subscription agreements, and charge separately, for expanded access to Lens and the increased functionality the company intends to provide to its users.
Other Software Applications
The company’s software applications extend beyond the oncology space. In the neuropsychiatry space, for example, it has built a series of proprietary and customized applications that are oriented around depression and other related psychiatric conditions. In addition, the company licensed a customized software tool, which it calls TempusPRO, that helps track patient reported outcomes, which the company integrates into Hub. Patients use the mobile application to complete regular and systematic check-ins, while providers use the tool to view clinical reports and review the patient reported information. The company has developed this application to empower providers to make data-driven, personalized treatment decisions, as well as collect outcome measurements on a regular, longitudinal basis in an effort to build one of the largest real-world multimodal datasets in psychiatry.
Three Product Lines
The company’s products are organized under three product lines, with each product line designed to enable and enhance the others, thereby creating network effects in the markets in which it operates. The company’s Genomics product line provides a broad range of diagnostic testing services to healthcare providers. The company’s Data and Services product line monetizes de-identified data that it collects and facilitates enrollment in clinical trials, and which at scale has allowed it to provide a series of data related services to its life sciences customers, such as clinical trial matching. The company’s AI Applications product line leverages its database to provide diagnostics entirely driven by data, which helps route patients to the optimal therapy and advance research more broadly.
The company’s business model allows its clients to unlock value from its data and allows it to monetize that data (in de-identified format), in different ways across its different product lines. The more data the company collects, the smarter its tests become, the more applications it can launch, the more physicians join its network, further growing its database, making its tests smarter for clinicians and its database more valuable for researchers.
Genomics
The company launched its Genomics product line to provide a comprehensive suite of Intelligent Diagnostics to healthcare providers, and to generate a steady stream of molecular data to help fuel growth in its Data and AI Applications product lines. As the company run more tests through its laboratories, and as those tests are linked to patient records and clinical outcomes, the company grows its data assets and leverage them across its other product lines. The company operates three laboratories that provide NGS diagnostics, PCR profiling, and other anatomic and molecular pathology tests. The company has broad capabilities across genomic, transcriptomic, proteomic, microbiomic, epigenetic, and methylation-based assays, and its laboratory infrastructure allows it to operate as a high-quality, low-cost NGS provider broadly serving the market. However, unlike other laboratory diagnostic testing providers, many of its tests are connected to clinical data, in some manner, which allows its suite of tests to be self-learning, becoming more accurate and precise with each new test that the company run. Furthermore, rather than providing a result based on a single data modality, such as a DNA mutation, its Platform leverages data from other modalities and other patients in an effort to be more comprehensive.
The company is generally paid for its Genomics services by billing insurance companies, or patients directly, who reimburse it for the tests it runs, or by billing providers or pharmaceutical companies directly.
Oncology Tests
The company’s Platform’s first application was in oncology, where it has built a versatile portfolio of cancer tests spanning solid tumors and hematologic malignancies, germline and somatic variants, and tissue and liquid biopsies. Since its inception, its approach to precision oncology has been to provide comprehensive genomic profiling through NGS that enables the company to both generate clinically relevant insights that may not be possible with narrower testing approaches and contribute high-quality molecular information back to providers and to its database. The company offers large-panel solid tumor and hematologic testing through multiple assays, with its core clinical assay (xT and xR) offering large panel DNA, RNA full transcriptome, and incidental germline findings through normal blood or saliva analyses. The company’s offerings also include liquid biopsy (xF), whole exome (xE), and hereditary cancer risk (xG). The company is also validating a treatment response monitoring assay. The company’s oncology tests are differentiated not only because of their breadth, but also because in many cases they are connected to clinical data, which allows the company to account for the drugs the patient took historically, how they responded, and for which clinical trials they are actually eligible. The company endeavors to not recommend drugs for which a patient has been previously prescribed in a prior line of therapy and failed, and not recommend clinical trials they are not eligible to participate in, based on the inclusion or exclusion criteria of the trial.
The company launched xM, a high coverage methylation sequencing assay for monitoring for cancer recurrence and minimal residual disease on June 1, 2024, initially covering colorectal cancer with the potential to expand into additional indications. In November 2023, the company entered into a Commercialization and Reference Laboratory Agreement with Personalis, Inc., or Personalis, pursuant to which the company began marketing Personalis’ Personal Dx test in the United States initially in non-small cell lung cancer and breast cancer, as well as IO treatment response monitoring. Personalis will conduct additional development activities to further analytically validate the test in other indications. Personalis will perform tests ordered by patients through the company and will bill such patients or payers.
Neuropsychiatry Tests
The company offers its proprietary nP assay for pharmacogenomic testing for patients with psychiatric conditions, such as depression, general anxiety disorder, bipolar disorder, and other relevant diagnoses.
TempusPRO is its patient-facing mobile application that collects PRO measurements on a longitudinal basis. The company is also capturing passive lifestyle measurements through mobile sensory devices, such as daily steps and minutes spent exercising. These measurements serve as a quantitative, unbiased backbone to the more qualitative and subjective measures that are commonplace in psychiatry.
Data and Services
The company’s Data and Services product line facilitates drug discovery and development for life sciences companies through two primary products: Insights and Trials. The company also maintains a growing tumor-derived biological modeling (or organoid) laboratory, which allows it to provide modeling and screening services to its pharmaceutical and biotech clients.
One way the company measures its data business is based on the remaining total contract value (the Remaining TCV) that is contractually committed to be delivered in the future.
Insights
The company launched its Insights product to allow researchers to access large amounts of multimodal healthcare data that historically did not exist at scale in a single consolidated database. The company has amassed a large connected dataset, which it organizes in near-real time across multiple modalities and multiple disease areas, allowing it to work with pharmaceutical and biotechnology companies across the drug lifecycle—from discovery, research and development, and, ultimately, commercialization.
For its Insights offering, the company licenses libraries of linked, de-identified clinical, molecular, and imaging data, and provides a suite of analytic and cloud-and-compute tools for discovery, research, development, and other commercial purposes. The company’s primary customers are pharmaceutical and biotechnology companies. These customers either pay it on a per file basis or through multi-year data licensing agreements to use its de-identified patient database. The company works with 19 of the 20 largest public pharmaceutical companies based on 2023 revenue.
The company’s data is useful across the oncology drug development value chain, and its biotechnology and pharmaceutical customers are using the data to inform decisions in a variety of discovery and development applications.
Trials
Trials is its second offering within its Data and Services product line and leverages its broad network of physicians the company works with in oncology to provide clinical trial matching services for pharmaceutical companies trying to reach hard-to-find and underserved patient populations. The company’s clinical trial matching product is built on top of its near real-time data feeds and harnesses AI to accelerate the connection between patients, clinical trial sites (hospitals) and clinical trial sponsors (life sciences companies). The company empowers both oncologists to help their patients find clinical trials and pharmaceutical companies to enroll patients into their trials. The company generates revenue from both matching the patient to the trial (through notices it sends to physicians alerting them of potential trials that are a fit for their patients), and from the patient actually enrolling in the trial.
The company is endeavoring to create a just-in-time network across a wide variety of academic medical centers and community providers, that can support hundreds or even thousands of trials, in which the administrative and logistical foundation is uniform across the entire network. This network allows the company to identify a patient that is a match for a targeted trial and get that patient enrolled within days, even if the trial was not previously open at the hospital (assuming consent of the trial sponsor), anywhere in the United States.
The company’s clinical trial matching offering is called the TIME Trial program, which it launched in June of 2019. Since its introduction, this program has gained significant traction with more than 250 clinical trials signed into the network. More than 30,000 patients were identified for potential enrollment into clinical trials in the company’s network as of December 31, 2024.
One of the primary benefits of the company’s Trials product is its ability to facilitate the initiation of a clinical trial in a new location in a short amount of time. Third-party research suggests that it takes 6-12 months, on average, to initiate a new trial site for an ongoing clinical trial in the United States. The company has been able to substantially streamline this process by leveraging technology and introducing a standard methodology, with activation of new sites through its Trials product taking approximately two weeks on average in 2024.
In addition to TIME, the company provides other clinical trial services and conduct its own studies as part of its Trials program, all with a goal of identifying new therapies and bringing them to market more efficiently. In January 2022, the company acquired Highline Consulting, LLC, a contract research organization, or CRO, which the company subsequently renamed Tempus Compass, LLC, or Tempus Compass. Tempus Compass manages and executes early and late-stage clinical trials, primarily in oncology. The company also partners with life sciences companies to sponsor studies of drugs, devices, and diagnostics, integrating its life science solutions to help bring new drugs to market faster. Each of the products and services within its Trials program complement each other to create a suite of integrated solutions for life sciences companies from early discovery to commercialization.
Tumor Derived Biological Modeling—Organoids
In addition to its efforts to collect vast amounts of phenotypic, morphologic, and molecular data, the company has built a large, biological modeling lab that allows it to test various theories in vitro through its large repository of tumor-derived Organoids, and to perform drug screening for its various life sciences clients. Many of its Organoids are fully characterized and sequenced using its NGS panels, providing genomic and transcriptomic data for its models, allowing the company to explore various hypotheses that enhance its data. Examples of hypotheses the company is able to test in its Organoid lab include which therapeutics are most effective; differential levels of drug response by tumor type, genomic profile, or other targeted attributes; discovery of RNA signatures; attributes of responders and non-responders; and response rates in therapy-resistant models. The company works with numerous collaborators including biotechnology companies, pharmaceutical companies, academic institutions, and government labs. The company has scaled its sample collection efforts and has received approximately 4,000 tumor samples.
These samples cover a wide range of cancer subtypes, allowing the company to work on comprehensive drug screening applications across multiple epithelial based tumor types, such as breast, lung, colorectal, and pancreatic. One of the goals of this screening is to predict a series of therapeutic responses in the company’s Organoids and then test whether or not patients are experiencing similar responses in the clinical setting.
The company views biological models as another form of data. The company’s efforts to grow Organoids are part of its overall strategy to leverage the best of systems biology along with the best of AI to collect the requisite data needed to produce answers broadly throughout healthcare.
AI Applications
The vastness of its dataset, along with its connected platform, creates an opportunity to use data to algorithmically diagnose and treat patients. The company’s third product line, AI Applications, or Algos, is focused on developing and providing diagnostics that are algorithmic in nature, implementing new software as a medical device, and building and deploying clinical decision support tools. The primary product of AI Applications is Next, an AI platform that leverages machine learning to apply an intelligent layer onto routinely generated data to proactively identify and minimize care gaps for oncology and cardiology patients. As this product gains adoption, the company intends to leverage large language models, generative AI algorithms, and its vast database of de-identified data to develop algorithmic diagnostics designed to identify these patients earlier in their disease progression, when treatments are most effective. For example, algorithmic diagnostics that integrate multimodal data can be used to create a more accurate risk profile for patients, leading to improved outcomes and reduced cost. The company’s repository of multimodal data allows it to find associations and patterns that are largely invisible through a single data modality, but readily apparent when combined. In addition, the company finds the strength of its analytic models, and its ability to deploy them clinically, improves as it adds additional datasets. While the company plan to continue developing its own proprietary software and algorithms, from time to time, it also utilizes open-source technologies or in-license technologies from third parties.
Oncology Algos Portfolio
The company offers a suite of Algos in oncology and have more in various stages of development. As of December 31, 2024, more than 80,000 molecular oncology Algos have been ordered with its various genomic assays. Most of the Algos the company offers are part of its xR assay, and it do not bill separately for them.
Cardiology Algos
Heart disease is the leading cause of death in the United States. Tempus is working on solutions to find, diagnose, and help treat these patients earlier in order to improve patient outcomes, using routinely generated clinical data, such as data from a 12-lead ECG, a widely used and easily acquired medical test that measures the electrical activity of the heart, to screen patients who might be at high risk and help navigate them to the appropriate interventional therapy.
In cardiology, the company ingestsmultimodal data and use approximately 60 algorithms to identify potential care gaps and continuously monitor patient data to find at-risk patients who may be falling through a care gap unbeknownst to their physician, and automatically notify care teams of any needed follow-up or disease progression. More than 100 hospitals nationwide are powered by Tempus Next and more than 45,000 patients are screened per month.
The company is also developing algorithmic models that aid clinicians in identifying patients at increased risk of developing atrial fibrillation, or AFib, along with a variety of other cardiac conditions. These Algos are trained using a de-identified subset from approximately 3.5 million ECGs, across more than 800,000 patients, with decades of longitudinal clinical data, including outcome and response data. The FDA granted Tempus breakthrough status for its first ECG software device, which employs a diagnostic algorithm designed to identify patients at high risk of developing AFib in certain populations (patients 40 years of age and older, without pre-existing or concurrent AFib or atrial flutter, and who are at elevated risk of stroke based on a commonly used clinical stroke risk assessment tool (i.e., CHA2DS2-VASc score of =4)).
The company is also advancing Algos that are designed to predict aortic stenosis, and it is working on other disease areas within cardiology, such as low ejection fraction and familial hypercholesterolemia.
In addition to algorithms based on NGS testing or in the cardiology space, the company offers more than 50 algorithms and are continuing to develop additional algorithms derived from radiologic images and digital pathology slides. In October 2022, the company acquired Arterys, Inc., a company that provides a platform to derive insights from radiologic medical images to improve diagnostic decision-making, efficiency, and productivity across multiple disease areas. The company has also developed algorithms based on Immunohistochemistry, or IHC, and H&E staining, which can be used, among other things, to help identify patients who may be eligible for additional treatments or clinical trials.
Commercialization
The company’s commercial efforts are generally focused on driving increased adoption of its various products and services, both by increasing the utilization of existing customers and securing new customers. The company employs targeted sales and business development organizations, whose team members are engaged in direct sales and marketing efforts. The company’s commercial teams typically target healthcare providers and life sciences companies, which are the main purchasers of its products and services.
Genomics
The company’s Genomics product line, largely made up of molecular testing, has two primary customers: physicians and bio-pharma companies. When it sells its tests to physicians the company is typically providing them as part of routine clinical care and the company is often billing insurance and seeking reimbursement on behalf of the patients for whom the test was ordered. When the company sells its test to bio-pharma, it is typically being paid as a contract sequencing provider, either for the trials they are running or as a companion diagnostic to their drug. On the physician side, the company commercializes its Genomics products in the United States to clinicians and healthcare providers largely through its dedicated clinical sales organization, that calls on individual doctors or medical practices. As of December 31, 2024, the company’s clinical sales organization in the United States included approximately 210 sales representatives who are primarily contacting oncologists, psychiatrists, and other healthcare providers. The company’s sales representatives typically have backgrounds either in a particular disease area (such as oncology or neuropsychiatry) or in laboratory testing and therapeutics more generally. The company supplements its commercial team with clinical specialists with extensive medical affairs experience who provide molecular support in the field.
In oncology, which is its largest market, the company focuses on driving adoption by targeting individual treating physicians, academic medical centers, community oncology practices, leading physician networks, and industry associations. The company is exploring relationships with third-party payers and governmental institutions. The company has a land and expand strategy, by account, whereby it attempts to sign new accounts and increase adoption of its platform within these accounts over time. As such, the company often begin a relationship that is transactional in nature, but seek over time, to work on a more comprehensive basis with healthcare providers, serving an ever-increasing percentage of its molecular diagnostic needs over time. The company finds that once a physician starts using Tempus, if they order more than 5 oncology NGS tests from it, their 12-month retention rate is 87%.
The company has similar strategy in neuropsychiatry, in which it aims to increase the commercial adoption of the company’s nP test for depression as part of the rapidly growing market for pharmacogenomic testing, with a goal to better understand, diagnose and treat neuropsychiatric disorders.
The company’s commercial strategy for other disease areas is expected to follow its strategy in oncology, which is to focus on offering a broad range of molecular diagnostics to the market, that are connected to clinical data, so the company can track how molecular results correlate with outcomes and responses, thereby making its tests smarter and more personalized overtime.
Research Testing
A small component of the company’s genomic testing involves testing performed in a research capacity. This type of testing is typically done under an agreed upon contracted arrangement for specific tests at specific prices and volumes. Typical customers in these arrangements are pharmaceutical companies engaged in testing for clinical trials, researchers who need genomic testing to further research activities, or a company marketing products or services of their own who elects to use the company as a reference laboratory. In this type of research testing, the agreed upon rate for testing may vary significantly, and in some cases may even be offered as an in-kind service in exchange for other rights the company obtains in the contracted relationship.
As it relates to selling its Genomic Products to bio-pharma, the company has a dedicated team of sales executives focused on calling on biotech and pharmaceutical companies who use genomic sequencing services predominantly for the research they are conducting, the clinical trials they are running, or as a companion diagnostic to the extent their therapeutic relies on a bio-marker. To this group, the company typically selling retrospective and prospective sample testing services, as well as companion diagnostic development to support the approval and commercialization of therapeutics.
Data and Services
In addition to the company’s field sales force, its Data and Services products rely on a dedicated business development team focused on enterprise sales to pharmaceutical and biotechnology companies in the United States and abroad. The company’s strategy with each customer is to demonstrate the value proposition of its Platform and de-identified datasets, and to expand the utilization of its Data and Services products across the organization from early-stage research through clinical development to commercialization. The company can support its pharmaceutical and biopharmaceutical customers across many applications, including early-stage research and development; discovery of new targets and mechanisms of acquired resistance; clinical trial patient identification and enrollment; and analytic services, including cloud and compute.
As of December 31, 2024, the company had approximately 50 sales executives in its Data and Services product line development organization. The company divides these individuals by both geography and strategic account to ensure consistency and coordination across its sales efforts.
AI Applications
The company’s third product line, AI Applications, is focused on developing and providing diagnostics that are algorithmic in nature, implementing new software as a medical device, and building and deploying clinical decision support tools. The company’s primary AI Applications product is Next, an AI platform that leverages machine learning to apply an intelligent layer onto routinely generated data to proactively identify and minimize care gaps for oncology and cardiology patients. As this product gains adoption, the company intends to leverage large language models, generative AI algorithms, and its vast database of de-identified data to develop algorithmic diagnostics designed to identify these patients earlier in their disease progression, when treatments are most effective.
The company commercializes AI Applications in multiple ways. The commercialization of future Algos will depend on the nature of each and whether the company is able to bill insurance separately. When the company do so, it expects reimbursement will be limited for most Algos at launch and may grow over time as its build additional evidence to support the clinical utility and benefit of each Algo.
Competition
The company’s primary competitors for its marketed precision oncology tests include Foundation Medicine, Inc., which was acquired by Roche Holdings, Inc., Caris Life Sciences, Guardant Health, Inc., Natera, Neogenomics, ResolutionBio, which was acquired by Agilent, and others. Competitors for its pharmacogenetic test in neuropsychiatry include Myriad Genetics, Inc. and Genomind, Inc.
The company’s Data and Services products primarily face competition from companies that help pharmaceutical, and biotechnology companies acquire data to inform drug discovery and development. The company’s main competitors in this area are Flatiron Health, Inc., IQVIA Holdings Inc., ConcertAI, and others. The company’s Data and Services products also face competition from CROs, such as Fortrea, ICON, Syneos, PPD, and others, who provide data and clinical trial matching services to pharmaceutical and biotechnology companies.
The company’s TO test competes with liquid or tissue-based diagnostic tests from Roche Holdings, Inc., Caris Life Sciences, Guardant Health, Inc. Illumina, Inc, and others. The company’s HRD test competes with tests from Myriad Genetics, Inc., Caris Life Sciences, and others.
Operations
The company performs its laboratory tests, including its NGS and anatomic pathology tests in its clinical laboratories in Chicago, Atlanta, Raleigh and Aliso Viejo. The company’s Chicago, Atlanta, Raleigh, and Aliso Viejo laboratories are CAP-accredited and CLIA-certified, and licensed in other states including New York, California, Maryland, Pennsylvania, and Rhode Island.
Strategic Collaborations
AstraZeneca Master Services Agreement
In November 2021, the company entered into a Master Services Agreement, or, as amended in October 2022, February 2023 and December 2023, the MSA, with, and issued a warrant to, AstraZeneca. Under the MSA, the company agreed, on a non-exclusive basis, to provide AstraZeneca with certain of its products and services, including licensed data, sequencing, clinical trial matching, organoid modeling services, algorithm development, and others. The term of the master services agreement will continue through December 31, 2028, unless terminated sooner.
GSK Master Services Agreement
In August 2022, the company entered into a Strategic Collaboration Agreement, or, as amended in May 2024, the GSK Agreement, with GSK. Under the GSK Agreement, the company agreed, on a non-exclusive basis, to provide GSK with certain of its products and services, including licensed data, sequencing, clinical trial matching, organoid modeling services, algorithm development, and others. The term of the GSK Agreement will continue through December 31, 2027, unless terminated sooner.
Recursion Master Agreement
In November 2023, the company entered into a Master Agreement, or the Recursion Agreement, with Recursion Pharmaceuticals, Inc., or Recursion. Under the Recursion Agreement, the company agreed to provide certain of its services and to license certain data to Recursion, including a limited right to access its proprietary database of de-identified clinical and molecular data for certain therapeutic product development purposes. The term of the Recursion Agreement will continue through November 3, 2028, unless terminated sooner.
Supply Chain
The company has a highly automatic system in place to manage its workflow called LIMS, which also connects to its various supply chain systems through which the company ensures materials it ordered in a timely manner, and the logistics of each order are overseen to ensure the company is delivering orders, in the shortest time possible, with the highest quality possible.
The company relies on a limited number of suppliers, or, in some cases, sole suppliers to provide its products and services. Illumina, Inc., is its primary supplier of sequencers and laboratory reagents; however, the company purchases laboratory supplies from other companies as well, such as Roche Holdings, Inc., Integrated DNA Technologies, and PerkinsElmer. The company relies on standard commercial carriers for the delivery of samples to its laboratories.
In June 2021, the company entered into a supply agreement with Illumina to provide products and services that can be used for certain research and clinical activities, including certain sequencers, reagents, and other consumables for use with the Illumina sequencers, as well as service contracts for the maintenance and repair of the sequencers.
In addition to suppliers who provide products supporting its provision of laboratory tests, the company has cloud agreements with both AWS and Google. In June 2020, the company signed a multi-year strategic partnership with Google that included an agreement through which Tempus procures extensive cloud services from Google. The cloud agreement includes a convertible note that is reduced as it procures services from Google and also contemplates co-innovation projects that the company may work on with Google from time to time.
Laboratory Workflow Applications
With respect to the provision of laboratory services, in addition to Hub, its consumer- facing application, the company has developed multiple software tools that facilitate back-end processing, workflow, and report generation. The company’s back-office software stack was custom developed around its workflow, allowing the company to automate material components of its laboratory and order generation process. The following diagram represents the software applications supporting its laboratory workflow.
Data Structuring Applications
After the company generates a clinical report through the provision of laboratory services, or once the company obtains data through one of its dedicated connections to providers, it utilizes a different suite of proprietary software applications to abstract, structure, and de-identify the resulting data to help augment its existing multimodal dataset and provide additional healthcare services to its customers.
Intellectual Property
As of December 31, 2024, the company’s patent portfolio and patent applications included 96 issued U.S. patents and allowed applications, 130 pending U.S. non-provisional patent applications, 8 pending U.S. provisional patent applications, 9 pending Patent Cooperation Treaty (international) patent applications, 33 issued foreign patents, 189 pending foreign patent applications, 6 licensed issued U.S. patents, 4 licensed pending U.S. patent application, 10 licensed issued foreign patents and 2 licensed pending foreign patent applications. The company’s issued patents are expected to begin expiring in 2033, assuming payment of all appropriate maintenance, renewal, annuity or other governmental fees. These patents and applications generally fall into four broad categories:
applications and patents relating to its Platform, including claims directed to product ordering processes; data processing and multimodal data analytics;
applications and patents relating to its Genomics business, including claims directed to detecting and monitoring cancer and other diseases by determining genetic variations and other biomarkers in biological samples;
applications and patents relating to its Data business, including claims directed to analysis of healthcare records and patient outcomes; and
applications and patents related to its Algos business, including claims directed to machine learning diagnostics and predictions in cancer and cardiology.
Research and Development
The company’s research and development expenses were $149.3 million for the year ended December 31, 2024.
Government Regulation
The company’s diagnostic products and services are subject to extensive and ongoing regulation by the FDA under the Federal Food, Drug, and Cosmetic Act of 1938 and its implementing regulations, collectively referred to as the FDCA, as well as other federal and state regulatory bodies in the United States.
The company is also subject to the federal physician self-referral prohibition, commonly known as the Stark Law, and to comparable state laws. Together these restrictions generally prohibit the company from billing a patient or governmental or private payer for certain designated health services, including clinical laboratory services, when the physician ordering the service, or a member of such physician’s immediate family, has a financial relationship, such as an ownership or investment interest in or compensation arrangement, with it, unless the relationship meets an applicable exception to the prohibition.
History
The company was founded in 2015. The company was incorporated in 2015. The company was formerly known as Tempus Labs, Inc. and changed its name to Tempus AI, Inc in 2023.
