AI APPLICATIONS

AI algorithms from NGS and digital pathology to increase clinical context on patients

Our algorithmic diagnostics sit on top of common diagnostic modalities of NGS, IHC, and H&E, powering researchers with new, AI-driven insights to support clinical care, whether in clinical decision making or trial eligibility.

Our Solutions

Get additional molecular context

Leverage Tempus AI-driven algorithms—such as HRD, TO, or DPYD—to gain molecular dimensionality to answer challenging scientific questions on patient outcomes.

Learn more about our algorithms

Partner in developing your own algorithm

Collaborate with Tempus’ data scientists and computational biologists to develop unique algorithmic biomarkers, whether based on DNA, RNA, or digital pathology, to support potential trial eligibility or clinicians' management of individual patients.

Validate your own algorithm

Partner with Tempus to leverage our capabilities to launch and operate studies and validate algorithms with prospective patients.

Identify patients earlier in their treatment journey

Deploy digital pathology algorithms in the Tempus NAPA network of pathology labs to identify patients who might qualify for your clinical trial—based upon an H&E image—potentially accelerating enrollment.

Our differentiators

70+

petabytes of data, which represents 25 times the size of the Cancer Genome Atlas
600K+

records with matched clinical data linked with genomic information
1M+

records with imaging data
300+

direct data connections across over 1,700 healthcare institutions that order our products and services
90%

of the top 20 pharma oncology companies partner with Tempus

Abstract in the Journal of Clinical Oncology
Learning relevant H&E slide morphologies for prediction of colorectal cancer tumor mutation burden using weakly supervised deep learning
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Abstract in the American Society for Clinical Oncology (ASCO) Meeting Library
H&E image-based consensus molecular subtype classification of colorectal cancer using weak labeling
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American Association for Cancer Research (AACR) Abstract
Abstract B57: Integrating RNA expression and visual features for immune infiltrate prediction
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Partnering with Tempus is investing in the future

We believe our AI solutions can guide researchers in understanding patients’ underlying biology, potentially leading to improved access to treatments, clinical trials, and care.