Tempus Presents Data Demonstrating AI-Enabled Pre-Screening Can Help Identify Patients for Biomarker Testing in NSCLC
Study to be presented at ESMO evaluated more than 60,000 advanced NSCLC cases and found greater than 80% sensitivity across all 12 biomarkers using routine H&E pathology images
CHICAGO, October 19, 2026--Tempus AI, Inc. (NASDAQ: TEM) today announced results from a study evaluating an AI-enabled pre-screening panel for patients with advanced non-small cell lung cancer (NSCLC). The panel achieved greater than 80% sensitivity across all 12 biomarkers assessed, with sensitivity exceeding 90% for several biomarkers, supporting its potential to identify patients who may need confirmatory biomarker testing. Results from the study will be presented at the European Society for Medical Oncology (ESMO) Congress 2026 in Madrid.
As the number of biomarker-driven therapies for advanced NSCLC continues to grow, identifying the right biomarkers can require multiple, time-consuming tests and sufficient tumor tissue. AI-enabled pre-screening is designed to help clinicians prioritize diagnostic testing, increase the number of patients who receive appropriate biomarker testing, accelerate access to clinically actionable results and preserve limited tissue samples.
"Precision medicine only works when clinicians have the right information at the right time," said Ezra Cohen, MD, Chief Medical Officer of Oncology at Tempus. "These findings demonstrate the potential for AI to extract meaningful information from a pathology image that is already part of routine care and help clinicians determine what testing may be most important next. This builds on our efforts to apply AI to routine diagnostic data to help more patients benefit from precision medicine."
Results are from a multi-center analysis of 60,459 advanced NSCLC cases across 56,969 patients. The AI-enabled panel analyzes routinely generated hematoxylin and eosin (H&E) pathology whole slide images (WSI) to predict potentially clinically relevant genomic and IHC biomarker status, supporting more timely access to personalized therapies. The study was conducted through an ongoing collaboration between Tempus and Pfizer focused on addressing diagnostic barriers and supporting biomarker testing across the broader treatment landscape, regardless of therapy.
The research also builds on Tempus' broader work in AI-enabled biomarker prediction, including Paige Predict and Tempus Preview. Paige Predict, used as part of clinical laboratory testing, analyzes H&E WSI to predict the likelihood of 123 biomarkers across multiple cancer types when tissue is insufficient for sequencing. Tempus Preview provides early predictions of clinically relevant biomarkers approximately 24 hours after sample receipt in the clinical laboratory.