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Developing AI capabilities to help find actionable biomarkers to identify potential therapeutic and clinical trial options for your patients.

Our digital pathology platform leverages data and AI to identify potential therapeutic options for patients earlier in their journey.

AI algorithms for molecular biomarker prediction

Our portfolio of digital pathology algorithms are in development to use single whole slide H&E images to predict biomarkers or guide pathologist review. These include:

  • DNA alterations, such as FGFR
  • RNA expressions, such as MET
  • Broad genomic signatures, such as HRD or MSI
  • Spatial analysis, such as TIL

AI algorithms for clinical trial enrichment

Our algorithms are being developed to use an H&E whole slide image to identify patients likely to contain characteristics relevant for clinical trial eligibility through our unique biomarker prediction technology.

Digitization as a Service

We can serve as a partner to your practice in digitizing your pathology workflow, from scanning to integrating AI algorithms into your existing workflow to uncover more potential options for patients.

Join our pathology network to learn more about these options.

Our impact in oncology

  • ~200

    petabytes of data, which represents ~50 times the size of the Cancer Genome Atlas

  • 6.5K+

    oncologists rely on Tempus as their precision medicine partner

  • 50%+

    of all Academic Medical Centers in the US are connected to Tempus

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Our Science


    Imaging-based histological features are predictive of MET alterations in Non-Small Cell Lung Cancer

    MET is a proto-oncogene whose somatic activation in non-small cell lung cancer leads to increased cell growth and tumor progression

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    2022 United States and Canadian Academy of Pathology (USCAP) Abstract

    Deep Learning Identifies Microsatellite Instability in H&E Whole Slide Images from Prostate, Esophageal, and Gastric Cancers and Generalizes across Cancer Types

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    2022 United States and Canadian Academy of Pathology (USCAP) Abstract

    Effects of Color Calibration via ICC Profile on Inter-scanner Generalization of AI Models

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    AI-augmented histopathologic review using image analysis to optimize DNA yield and tumor purity from FFPE slides

    AI-augmented histopathologic review using SmartPath could decrease tissue waste, sequencing time, and laboratory costs by optimizing DNA yields and tumor purity

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    Medical Image Computing and Computer Assisted Intervention – MICCAI 2021

    Deep Orthogonal Fusion: Multimodal Prognostic Biomarker Discovery Integrating Radiology, Pathology, Genomic, and Clinical Data

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Partnering with Tempus is investing in the future

We believe that AI solutions can open the door to more treatment options for patients by identifying actionable markers leading to potential novel therapies and clinical trials.