Precision Medicine & Diagnostics
Tempus AI
by Tempus AI, Inc.
AI-powered precision medicine platform connecting clinical and molecular data at scale
Category
Precision Medicine & Diagnostics
Founded
2015
Headquarters
Chicago, IL, USA
Overview
Tempus AI operates one of the world's largest libraries of clinical and molecular data, combining genomic sequencing, clinical records, imaging, and real-world outcomes data to power precision medicine. The platform offers next-generation sequencing panels (xT, xF, xR), AI-powered clinical decision support, and real-world evidence analytics for oncology, cardiology, neuropsychiatry, and infectious disease. Oncologists and clinical care teams use Tempus to match patients with targeted therapies and clinical trials based on their tumor's molecular profile. Pharma companies leverage Tempus's de-identified dataset of over 7 million clinical records linked to multi-omic data for drug development, biomarker discovery, and clinical trial optimization. Tempus went public in 2024 at a valuation of over $6 billion. Tempus differentiates through the breadth and depth of its clinico-genomic dataset and the tight integration between diagnostic testing and AI analytics. The Tempus One platform uses large language models to synthesize patient records, clinical literature, and molecular data into actionable insights at the point of care.
Key Features
Pharmacogenomics Engine
Predict individual drug responses based on genetic variants affecting drug metabolism pathways.
Real-World Evidence Platform
Aggregation of de-identified patient data from healthcare systems for outcomes-based analysis.
Companion Diagnostic Development
AI-driven biomarker discovery and validation for companion diagnostic test development.
Clinical Trial Matching
Automated matching of patients to clinical trials based on genomic profiles and eligibility criteria.
Multi-Modal Patient Profiling
Integration of genomic, clinical, imaging, and real-world data for comprehensive patient profiles.
Pros & Cons
Pros
- +Longitudinal patient tracking enables outcomes-based analysis of treatment effectiveness
- +Partnerships with 50%+ of US academic medical centers provide diverse patient population coverage
- +FDA-cleared diagnostic tests validate AI-driven biomarker discoveries for clinical use
- +Companion diagnostic development accelerates clinical trial matching and treatment selection
- +Real-world evidence platform aggregates de-identified patient data from major healthcare systems
- +Multi-modal data integration combines genomic, clinical, and imaging data for comprehensive patient profiling
- +AI-powered genomic analysis identifies actionable biomarkers from clinical sequencing data in hours
Cons
- −Reimbursement pathways for AI-driven diagnostics remain uncertain in many healthcare markets
- −Requires high-quality, diverse patient datasets that may not be available for rare diseases
- −Clinical validation and regulatory approval processes are lengthy and resource-intensive
- −Clinical adoption depends on physician trust in AI-generated recommendations
Use Cases
Genomic-Guided Treatment Selection
AI-powered analysis of patient genomic data to identify actionable biomarkers and match patients to optimal therapies.
Clinical Trial Matching
Automated matching of patients to clinical trials based on genomic profile, medical history, and trial eligibility criteria.
Real-World Evidence Generation
Aggregation and analysis of de-identified patient data from healthcare systems to generate real-world evidence.