공지 • May 07
Tempus AI, Inc. Increases Earnings Guidance for the Full Year 2026 Tempus AI, Inc. increased earnings guidance for the full year 2026. For the period, the company expects revenue in range of $1.59 billion to $1.60 billion, which represents ~25% annual growth. 공지 • Apr 21
Tempus AI, Inc. to Report Q1, 2026 Results on May 05, 2026 Tempus AI, Inc. announced that they will report Q1, 2026 results on May 05, 2026 공지 • Apr 14
Tempus AI, Inc. Launches Automated Active Follow-Up Service Tempus AI, Inc. announced the launch of an automated clinical update service designed to support guideline-concordant care by placing patients on an active follow-up track. This integrated workflow provides clinicians with ongoing therapy monitoring and context-aware notifications seamlessly delivered through Hub, Tempus’ secure, AI-enabled physician portal. Because NCCN guidelines, FDA approvals, and patient context can all evolve rapidly, an initial genomic report can quickly become outdated relative to a patient’s ongoing treatment journey. Tempus is addressing this challenge by automatically surfacing updated therapy recommendations when clinical guidelines change or new therapeutic options emerge—all without requiring a new patient sample. This ensures that patient insights remain as current as the science, supporting evidence-based decision-making throughout the patient’s treatment journey. 공지 • Apr 08
Tempus AI, Inc., Annual General Meeting, May 21, 2026 Tempus AI, Inc., Annual General Meeting, May 21, 2026. 공지 • Apr 01
Tempus AI, Inc. Announces Results from ALERT Trial Tempus AI, Inc. announced results from the ALERT (Addressing undertreatment and heaLth Equity in aortic stenosis and mitral regurgitation using an integrated ehR plaTform) trial, which were recently presented at the American College of Cardiology’s 75th Annual Scientific Session & Expo. The study, conducted in collaboration with Medtronic, found that automated electronic clinician notifications (ECNs) integrated into the electronic health record (EHR) significantly improve the timely evaluation and treatment of patients with significant aortic stenosis (AS) and mitral regurgitation (MR). Valvular heart disease is a leading cause of morbidity and mortality, yet it remains frequently undertreated. For patients with untreated symptomatic severe AS, mortality approaches 50% within just two years. Similarly, untreated severe MR carries a median survival of only five years. The ALERT trial was designed to determine if automated, AI-driven alerts could bridge this critical gap in care delivery. By leveraging the Tempus Next platform, which applies natural language processing to accurately extract findings from echocardiogram reports, the trial enabled real-time detection of significant disease and automatically delivered notifications with site-specific guideline-based care notifications directly to providers. The ALERT trial included 765 clinicians and 2,016 echocardiograms across five U.S. health systems and 35 hospitals. The study met its primary endpoint, demonstrating that automated ECN alerts were superior to usual care in a win ratio analysis (win ratio 1.27; P = .007), meaning patients in the alert group were 27% more likely to be evaluated by the multidisciplinary heart team or receive a valve intervention than those in the usual care group. By delivering actionable data directly to providers, the system facilitated a 40% relative increase in life-saving valve procedures (13.4% vs. 9.6%) and a 27% increase in multidisciplinary heart team evaluations (22.7% vs. 17.9%) within just 90 days. These alerts effectively reduced clinical inertia, prompting earlier specialist referrals and ensuring patients received interventions within established benchmarks for timely care. Beyond clinical efficiency, a central objective of the ALERT trial was to confront the persistent disparities that leave women, older adults, racial and ethnic minorities, and rural residents at higher risk of being undertreated. These findings suggest that EHR-integrated clinical decision support can serve as a powerful, scalable 'safety net,' standardizing care delivery to help ensure high-risk findings receive timely action regardless of a patient's demographics or care setting. While the ALERT trial was conducted in collaboration with Medtronic, the automated clinician notifications were designed to be device-agnostic to promote standardized care delivery, without requiring providers to use specific Medtronic devices for recommended evaluations or interventions. 공지 • Mar 11
Tempus Ai, Inc. Announces the Publication of A New Study in Jco Precision Oncology Tempus AI, Inc. announced the publication of a new study in JCO Precision Oncology highlighting how advanced features of comprehensive genomic profiling (CGP) expand treatment options for cancer patients in community oncology settings. The study, conducted in collaboration with The Oncology Institute (TOI), reveals that features such as tumor-normal matched sequencing, RNA sequencing, and liquid biopsy reflex identify actionable findings that are missed by more limited standard in-network testing. While organizations like ASCO and the NCCN strongly advocate for CGP to guide precision therapies, current guidelines often lack specificity regarding the exact composition or essential features required within these panels. This research demonstrates that CGP value extends far beyond simple panel size, highlighting the utility of advanced testing features to more fully capture clinically relevant findings. In the study, 12% (approximately 1 in 8) of patients across the pilot and expanded cohorts had potentially actionable findings associated with an approved therapy identified solely through advanced Tempus features—such as tumor-normal matching, RNA sequencing, and liquid biopsy reflex testing—that would otherwise have been missed by less comprehensive tests. 공지 • Feb 18
Tempus AI, Inc. Announces Novel Pan-Cancer HRD-RNA Algorithm Tempus AI, Inc. announced the launch of its new HRD-RNA algorithm. This next-generation model represents a significant improvement in identifying Homologous Recombination Deficiency (HRD), providing a more robust, functional assessment of tumor biology compared to traditional static DNA-based assays. Tempus HRD-RNA is an AI-driven, 1,660-gene logistic regression model designed to identify patients likely to respond to platinum-based chemotherapy or PARP inhibitors. Unlike traditional DNA tests that analyze static "genomic scars"--which may persist even after a patient develops drug resistance--this RNA-based approach provides a dynamic, real-time assessment of a tumor's functional status. By analyzing gene expression rather than structural DNA damage, the algorithm can detect HRD in patients and cancer types where genomic scarring is rare or difficult to identify. This advanced methodology allows the model to capture HRD status in patients who might be missed by DNA-based assays, significantly expanding the population that can be identified for potentially life-saving therapies. A real-world validation study demonstrates that HRD-RNA positive metastatic pancreatic patients treated with first line platinum-based regimens showed a significant reduction in mortality risk compared to those receiving non-platinum first line therapies. These findings, including the complete supporting data, will be published later this year. HRD-RNA is currently available for research use only in the detection of HRD status within solid tumor patient populations and for the identification of patients likely to respond to platinum regimens or PARP inhibitor therapy. Clinical availability is expected later this year. 공지 • Feb 10
Tempus AI, Inc. to Report Q4, 2025 Results on Feb 24, 2026 Tempus AI, Inc. announced that they will report Q4, 2025 results on Feb 24, 2026 공지 • Jan 27
Tempus Ai, Inc. Reveals Its AI-Driven IPS Test More Accurately Predicts Immunotherapy Benefit Compared to Conventional Biomarkers Tempus AI, Inc. announced results from a new study demonstrating that its algorithmic test, Immune Profile Score (IPS), more accurately predicts outcomes for patients receiving immune checkpoint inhibitors (ICIs) than conventional biomarkers, including tumor mutational burden (TMB) and microsatellite instability (MSI), and PD-L1. IPS is a multimodal biomarker that combines known and novel clinical and immune-related biomarkers from DNA and RNA analysis to predict a patient's response to ICI-based therapy. The new clinical validation results demonstrate that IPS consistently outperforms conventional biomarkers, highlighting its potential to change the way physicians can identify patients most likely to benefit from immunotherapy. In four independent validation cohorts of pan-cancer metastatic solid organ cancer patients, IPS was shown to be a more accurate predictor of ICI outcomes (HR=0.45) than TMB, MSS, and PD-L1, demonstrating prognostic utility that is independent of those conventional biomarkers. IPS identified 13% of patients with microsatellite stable colorectal cancer who demonstrated strong real-world overall survival with ICI treatment (HR=0.2), indicating that ICI immunotherapy may be a viable option for a key patient population that might have been overlooked with conventional biomarkers alone. Beyond colorectal cancer, the study's findings highlight how IPS could expand treatment options for patients with rare cancers. IPS classified 17% of patients with rare metastatic solid tumors as "IPS-High," despite these patients not falling within a cancer-specific FDA-approved ICI label. The significant difference in median real-world overall survival in "IPS High" versus "IPS-Low" patients (HR=0.26) shows that ICI could be a relevant and potentially life-saving option for patients that might otherwise be missed. The test is available as an add-on for clinicians ordering Tempus' xT (DNA) and xR (RNA) assays, helping to manage patients on immunotherapy by utilizing data already collected as part of a patient's standard sequencing. 공지 • Jan 21
Tempus AI, Inc. Announces the Launch of Paige Predict Tempus AI, Inc. announced the launch of Paige Predict, a suite of cutting-edge digital pathology applications that analyze hematoxylin and eosin (H&E) whole slide images to help inform testing decisions. The AI-powered solution is designed to predict the likely presence or absence of clinically actionable and relevant biomarkers directly from a single H&E slide, offering physicians insights even when tissue samples are insufficient for full molecular profiling. As the demand for next-generation sequencing (NGS) and immunohistochemistry (IHC) testing grows, so does the challenge of limited tissue availability. When a sample is "quantity not sufficient" (QNS), patients can face delays of days or weeks for testing results, waiting for repeat biopsies or alternative testing, ultimately prolonged uncertainty and potentially impacting treatment options. Paige Predict's ability to use an H&E image to identify biomarkers that are more or less likely to be present in the specimen can be used by clinicians to inform the sequence in which they will order confirmatory tissue-based tests, maximizing the likelihood of receiving an actionable result before exhausting tissue. Leveraging Tempus and Paige's intelligent digital pathology platform and proprietary AI products, Paige Predict identifies critical biomarker information from even scarce amounts of tissue and analyzes H&E images to predict the likelihood of 123 biomarkers and oncogenic molecular pathways in 16 cancer types, including NSCLC, prostate, breast, pancreatic, colorectal, and more. Results are automatically delivered with the clinical report to ordering physicians. Paige Predict was built using Paige's foundation model and a combined, multimodal cohort from Tempus and Paige, which contains de-identified data on over 200,000 patients. The model has been rigorously validated to demonstrate performance, generalizability and robustness across multiple, diverse datasets, including a large-scale cohort from Tempus. 공지 • Dec 09
Tempus AI, Inc. Announces Ten Abstracts Accepted for Presentation at the 2025 San Antonio Breast Cancer Symposium Tempus AI, Inc. announced that ten abstracts have been accepted for presentation at the 2025 San Antonio Breast Cancer Symposium (SABCS). The meeting takes place December 9-12 at the Henry B. Gonzalez Convention Center in San Antonio, Texas. Tempus will highlight its latest scientific and clinical research findings via ten poster presentations: Integrative Modeling of Multimodal Real-World Data for Improved Risk Stratification of First-Line CDK4/6 inhibitor plus endocrine treatment and identify predictors of response. This study demonstrated that multimodal real-world data collected during routine care can provide valuable insights into the biology of response to CDK4/6 inhibitors in patients with metastatic breast cancer and help improve patient stratification. Distinct Transcriptional and Immunosuppressive Microenvironment Signatures in PIK3CA-mutant Hormone Receptor Positive (HR+)/HER2- Metastatic Breast Cancer (MBC). Date/Time: December 10, 2025, 12:30 p.m. - 2:30 p.m. CDT. Presentation Number: PS1-11-08. Summary: This study compared transcriptomic and immune profiles in HR+/HER2- metastatic breast cancer across wild-type, PIK3CA-mutants, ESR1-mutant, and co-mutant groups. SFRP2 downregulation was specific to ESR1-mutant tumors, while SCGB2A2 was robustly upregulated in PIK3CA- mutant and co-mutant tumors, suggesting its potential as a diagnostic and therapeutic target. Immune analysis revealed increased M2 macrophages and regulatory T cells in PIK3CA- mutualant and co-mutant tumor, with the most pronounced immunosuppressive microenvironment in PIK3CA-Mutant cases. A notable percentage of patients with localized and de novo metastatic disease displayed TMB high status and/or PD-L1 positivity. Additionally, TMB-high and PD-L1 positive patients with de novo metastatic disease treated with first-line chemotherapy or anti-HER2 therapy had significantly worse real-world overall survival (rwOS), suggesting a potential therapeutic benefit of incorporating immunotherapy into the treatment paradigm, in both localized and metastatic disease settings. Furthermore, observed ethnic HLA polymorphisms in the cohort may contribute to differences in outcomes and could potentially guide the development of population-specific immunotherapeutic strategies. Real-World Data (RWD) Outcome Analysis of ESR1 Mutation Emergence in HR+/HER2 - Metastatic Breast Cancer through the Continuum of Standard of Care Hormonal Therapy. Date/Time: Friday, December 12, 2025, 12:30p.m. - 2:00 p.m. CDT, Presentation Number: PS5-05-02. Summary: This large multimodal RWD outcome analysis from longitudinal molecular surveillance testing (xF) in HR+/HER2. mBC patients treated with AI+CDK4/6 inhibitor (ER)-Positive/Human Epidermal Growth Factor Receptor 2 (HER2)-Negative Metastatic Breast Cancer. Date/Time: December 12, 2025, 12; 12:30 p.m., 2:00 p.m., CDT and Presentation Number: PS5.05-02; Summary: This large multimodAL RWD outcome analysis from longitudinal Molecular surveillance testing (xF)in HR+/HER2- mBC pts treated with AI+ CDK4/6 inhibitors treated with AI+CDK 4/6 inhibitor plus end endocrine treatment and resistance. These insights are essential for pinpointing patient populations who may benefit from novel therapies and for optimizing treatment strategies to ultimately improve outcomes for those with advanced disease. 공지 • Oct 21
Tempus AI, Inc. to Report Q3, 2025 Results on Nov 04, 2025 Tempus AI, Inc. announced that they will report Q3, 2025 results at 9:30 AM, US Eastern Standard Time on Nov 04, 2025 공지 • Sep 23
Tempus AI, Inc. Receives U.S. FDA 510(k) Clearance for Tempus xR IVD, its RNA NGS in Vitro Diagnostic Device Tempus AI, Inc. announced it has received 510(k) clearance from the U.S. Food and Drug Administration (FDA) for its RNA-based Tempus xR IVD device. xR IVD will be offered as a life science tool to support drug development programs. RNA sequencing captures a large array of biological information and offers deeper insights into the mechanisms of diseases, including enhanced fusion detection. RNA analysis is increasingly an important tool in research and development because it can identify molecular pathways and networks that are directly involved in disease progression. The Tempus xR IVD assay is a qualitative next generation sequencing-based in vitro diagnostic device that uses targeted high throughput hybridization-based capture technology for detection of rearrangements in two genes, using RNA isolated from formalin-fixed paraffin embedded (FFPE) tumor tissue specimens from patients with solid malignant neoplasms. Information provided by xR IVD is intended to be used by qualified health care professionals in accordance with professional guidelines in oncology for patients with previously diagnosed malignant neoplasms. Results from xR IVD are not intended to be prescriptive or conclusive for labeled use of any specific therapeutic product. The FDA authorization further solidifies Tempus as a one-stop-shop for precision medicine solutions. Collaborators can leverage Tempus' comprehensive collection of intelligent diagnostics and growing multimodal data that supports therapeutic innovation. xR IVD is one of the many solutions Tempus is applying to advance oncology therapeutic research and development. 공지 • Sep 11
Tempus AI, Inc. Receives U.S. FDA Special 510(k) Clearance for Updated Tempus Pixel Device Tempus AI, Inc. announced it has received 510(k) clearance from the U.S. Food and Drug Administration (FDA) for its updated Tempus Pixel, an AI-powered cardiac imaging platform. This update allows the generation of T1 and T2 inline maps, further enhancing the device's capabilities for cardiac MR image analysis. Tempus Pixel provides advanced viewing and automated reporting of cardiac MR images, improving efficiency and accuracy in flow visualization, functional analysis, and tissue characterization. AI-enabled radiology, like Tempus Pixel, enhances medical imaging by rapidly analyzing scans, highlighting subtle abnormalities, and generating consistent, actionable insights. By improving accuracy and efficiency, it empowers clinicians to make faster, more informed decisions and deliver personalized patient care. Unlike conventional MR images that show only brightness differences, T1 and T2 maps provide precise numerical values to cardiac tissue characteristics, helping clinicians detect conditions such as fibrosis, inflammation, or edema, that may otherwise go undetected. With its newly cleared functionality, Tempus Pixel can now generate T1 and T2 inline map directly from raw MRI data, even when the scanner itself does not produce them, calculating values at every pixel across the image to create detailed DICOM maps for comprehensive tissue assessment. Tempus has developed and deployed a suite of advanced algorithms across radiology and pathology, helping physicians deliver more precision, personalized care. Its strategic acquisitions have further strengthened its footprint in these fields. In 2022, Tempus acquired Arterys, incorporating its AI-powered tools for analyzing imaging data--ranging from lung CT scans and chest X-rays to cardiac MRIs-- into Tempus' platform. Most recently, Tempus acquired Paige, an AI company specializing in digital pathology, bringing a proprietary dataset of almost 7 million clinically annotated, de-identified pathology slides to accelerate Tempus' efforts. 공지 • Sep 09
Tempus AI, Inc. Announces New Study in JCO Precision Oncology Validating PurIST Algorithm for Enhanced Therapy Selection in Pancreatic Cancer Tempus AI, Inc. announced the publication of a study in JCO Precision Oncology validating the clinical utility of the company's PurIST®? algorithmic diagnostic. The study provides the largest real-world evidence to date supporting the integration of PurIST into routine clinical care for patients with advanced PDAC, with the aim of informing first-line chemotherapy selection and improving patient outcomes. Pancreatic cancer remains one of the most lethal malignancies, with limited therapeutic options and a five-year survival rate of just 12%. For patients with advanced, unresectable PDAC, the two most common first-line chemotherapy regimens, FOLFIRINOX (FFX) and gemcitabine plus nab-paclitaxel (GnP), have shown variable efficacy, and clinicians have lacked robust biomarkers to guide optimal therapy selection. To address this challenge, Tempus collaborated with GeneCentric to develop and deploy PurIST, a clinically validated, RNA-based algorithm test that classifies PDAC tumors as either "classical" or "basal" subtypes. The Tempus-led study analyzed a real-world cohort of 931 patients with advanced PDAC, using the Tempus xR RNA sequencing platform to assign PurIST subtypes. Patients were treated with either first-line FFX or GnP, and clinical outcomes were assessed according to PurIST classification. The study's findings establish PurIST as both a prognostic and predictive biomarker, enabling clinicians to personalize first-line therapy for advanced PDAC patients and maximize the likelihood of improved survival. Prognostic Value: Among patients treated with FFX (N=536), those with the classical subtype had a significantly longer median overall survival (OS) of 11.8 months, compared to 7.0 months for basal subtype patients (Hazard Ratio [HR]=1.86; p; Predictive Value: In patients with the classical subtype and good performance status (ECOG 0 or 1, N=311), treatment with FFX was associated with a 33% relative risk reduction in death compared to GnP (HR=0.67; p<0.009). No comparable benefit was observed in basal subtype patients. 공지 • Aug 23
Tempus AI, Inc. (NasdaqGS:TEM) acquired Paige.AI, Inc. in a transaction valued at $81.2 million. Tempus AI, Inc. (NasdaqGS:TEM) acquired Paige.AI, Inc. in a transaction valued at $81.2 million on August 22, 2025. The consideration consists of $81.25 million, which is being paid predominantly in Tempus common stock, as well as Tempus’ assumption of Paige’s remaining commitment under its existing Microsoft Azure cloud services agreement. Morgan Stanley (NYSE:MS) acted as financial advisor to Paige.AI, Inc.
Tempus AI, Inc. (NasdaqGS:TEM) completed the acquisition of Paige.AI, Inc. on August 22, 2025. 
