Inteliquet

Inteliquet

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Private Company

Total funding raised: $32M

Overview

Inteliquet operates at the intersection of oncology, digital health, and AI, providing a software-as-a-service (SaaS) platform to streamline the complex process of clinical trial matching. The company's core value proposition is using structured real-world data from electronic health records (EHRs) and other sources to intelligently identify and pre-screen eligible patients for oncology trials, thereby reducing enrollment times and costs for trial sponsors. As a private company founded in 2015, it targets a significant pain point in drug development, positioning itself as an enabler for more efficient and inclusive clinical research. Its success hinges on data partnerships, algorithm accuracy, and adoption by major biopharma and research institutions.

Oncology

Technology Platform

AI/ML-powered platform that uses structured real-world data (RWD) from electronic health records to match oncology patients with appropriate clinical trials, optimizing patient pre-screening and enrollment.

Funding History

2
Total raised:$32M
Series B$20M
Series A$12M

Opportunities

The strong push from regulators for the use of real-world evidence (RWE) and the chronic inefficiency in clinical trial patient recruitment create a large and growing addressable market.
The trend towards precision oncology and smaller, more specific patient populations increases the need for intelligent matching tools like Inteliquet's.

Risk Factors

Heavy reliance on securing data-sharing partnerships with healthcare systems, which can be difficult and slow.
Facing competition from both nimble startups and large, entrenched players like EHR vendors and CROs who are building similar capabilities.

Competitive Landscape

Inteliquet competes in the clinical trial matching and patient recruitment enablement space. Competitors include other digital health startups (e.g., Deep 6 AI, TriNetX), large contract research organizations (CROs) developing internal tech, and electronic health record (EHR) companies adding trial matching modules. Differentiation is based on data network size, algorithm accuracy, and oncology-specific focus.