Immune IQ


Develops an AI-driven platform to decode the human immune system for multi-disease detection at the point of care. The company is building a compact analyzer and low-cost disposable test cartridges combined with a centralized immune-dataset and automated machine-learning pipeline to enable early disease screening, clinical decision support, and expansion of diagnostic menus via partner apps and database-driven model training.

Industries

biotechnology
health-care
health-diagnostics

Nr. of Employees

small (1-50)

Immune IQ

Saint Paul, Minnesota, United States, North America


Products

Point-of-care immune-decoding diagnostic system

A compact analyzer paired with low-cost disposable cartridges and AI-driven analytics designed to scan immune-system signals for multiple diseases rapidly at the point of care.


Services

Design and conduct of clinical studies (hands-off and retrospective) to generate performance datasets for regulatory submissions and clinical evaluation.

Provision of aggregated immune-dataset and analytic tools to support partner model training, drug development, and companion diagnostic discovery.

Platform capability enabling in-house and third-party app development to expand the diagnostic test menu for the point-of-care platform.

Expertise Areas

  • AI-driven immune profiling
  • Point-of-care diagnostic device development
  • Disposable cartridge design and manufacturing
  • Clinical performance evaluation and trial execution
  • Show More (4)

Key Technologies

  • Machine learning for immune-system signal decoding
  • Microfluidics
  • Tape-based disposable cartridge assembly
  • Point-of-care analyzer hardware
  • Show More (4)

News & Updates

Company states it holds approximately 100 patents related to its immune-decoding platform and technologies.

A month-long, hands-off clinical study at Massachusetts General Hospital demonstrated the system's ability to reliably generate its advanced dataset.

A preliminary clinical study reported superior results for COVID identification compared to PCR in the company’s dataset.

Company-reported dataset showed higher initial recognition of high-risk sepsis (94% vs. 30% cited) compared to the current process.

A retrospective study indicated the second-generation dataset had performance comparable to CT scan and cell-free DNA for lung cancer detection.


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