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Tempus AI Platform screenshot

What is Tempus AI Platform?

Tempus AI is a data platform designed to help clinicians and researchers in oncology and precision medicine make better treatment decisions. It combines AI analysis with large datasets of patient outcomes, genetic information, and treatment responses to identify which therapies are most likely to work for individual patients. The platform is primarily used by cancer centres, academic medical institutions, and oncologists looking to move beyond standard treatment protocols towards personalised approaches based on a patient's specific tumour characteristics and medical history. Access is free, making it available to healthcare providers without licensing fees.

Key Features

Patient outcome matching

compares individual patient profiles against thousands of similar cases to suggest relevant treatment options

Genomic analysis integration

incorporates tumour sequencing data and genetic markers to inform treatment selection

Clinical trial identification

helps match patients to relevant trials based on their specific cancer type and biomarkers

Survival prediction models

uses historical data to estimate likely outcomes for different treatment approaches

Real-time data access

provides access to large databases of treatment outcomes and patient responses

Pros & Cons

Advantages

  • Free to use for eligible healthcare providers, removing cost barriers to adoption
  • Focuses on practical advice rather than general information, giving clinicians specific treatment recommendations
  • Incorporates real-world patient outcome data, not just published clinical trial results
  • Helps identify clinical trials that match individual patient profiles

Limitations

  • Requires integration with existing clinical workflows and electronic health records, which can be time-consuming to set up
  • Primarily focused on oncology; limited application for other medical specialities
  • Effectiveness depends on data quality and completeness of patient information uploaded to the platform

Use Cases

Oncologists selecting second-line or third-line treatments when standard protocols have failed

Cancer centres developing personalised treatment plans based on tumour genetics

Researchers analysing patterns in treatment response across large patient populations

Clinical trial coordinators matching eligible patients to appropriate studies

Healthcare systems evaluating which therapies deliver the best outcomes for their patient populations