Owlstone Awarded $49.1M to Develop At-home Multi-Cancer-Early Detection Tests

The project involves the inhalation of synthetic sensors from a single-use inhaler.

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Owlstone

Owlstone Medical today announced that it has won an award of up to $49.1 million from the Advanced Research Projects Agency for Health (ARPA-H) for the Platform Optimizing SynBio for Early Intervention and Detection in Oncology (POSEIDON) program. POSEIDON aims to develop synthetic-sensor based Multi-Cancer-Early Detection (MCED) tests for Stage I detection of 30+ solid tumors using only breath and urine samples that can be performed in the home and are available over the counter.

Owlstone’s project, in partnership with the Massachusetts Institute of Technology, Boston University, Georgia Tech Research Corporation, Qurin B.V., and Planned Systems International Inc, aims to overcome this challenge by delivering accurate, low-cost cancer screening for 30+ solid tumors to Americans aged 18 and older.

The project involves the inhalation of a mix of pan-cancer and tumor-specific synthetic sensors from a single-use inhaler, which then circulate throughout the body and accumulate on the surface of cancer cells. The reporters produced by the sensors are either DNA-based which act as a readable barcode, or a set of volatile organic compounds (VOCs), supporting the detection of 36 cancers in total. These will be collected at-home or in clinic in urine samples and from breath respectively using portable collection and analysis devices. Results will be uploadable real-time to electronic health records (EHR) for rapid review by healthcare professionals, integrating seamlessly into clinical practice and digitally enabled care.

This unique approach offers significant advantages over competing technologies. These include boosting the signal to enhance test performance such that cancer is reliably detectable from early stage, enabling simple and non-invasive sample collection at home, rapid result generation and EHR integration, and a low-cost manufacturing model such that economics are not a barrier to adoption of the technology as the new standard of care for early cancer detection.

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