Develop and validate a groundbreaking, reagent-less diagnostic device (cube scan) leveraging radio frequency (RF) and artificial intelligence (AI) technology for the rapid and accurate detection of…

The Department of Agriculture Animal and Plant Health Inspection Service awarded a Cooperative Agreement to Radiolife CO. on February 2, 2026, for $2,616,017 to develop and validate the CUBE SCAN, a reagent-less diagnostic device that leverages radio frequency and artificial intelligence technology to detect highly pathogenic avian influenza (HPAI) in poultry. The award funds work under the Plant and Animal Disease, Pest Control, and Animal Care program (CFDA 10.025).

Radiolife will train CUBE SCAN's AI to recognize RF signatures of HPAI, validate diagnostic accuracy, and assess performance in real-world settings. The project encompasses extensive sample collection, AI model refinement, device optimization, and multi-site field testing. The field-deployable solution aims to deliver rapid, accurate results without reagents, reducing costs for poultry producers, veterinary laboratories, and regulatory agencies while improving HPAI response strategies, enhancing biosecurity, and mitigating economic losses.

Work is performed in Penn Valley, California. The period of performance runs through September 30, 2028.

Develop and validate a groundbreaking, reagent-less diagnostic device (cube scan) leveraging radio frequency (RF) and artificial intelligence (AI) technology for the rapid and accurate detection of highly pathogenic avian influenza (hpai) in poultry. This initiative aims to transform hpai diagnostics by providing a cost-effective, field-deployable solution capable of delivering immediate, accurate results without the need for reagents. To achieve these objectives, the project will involve comprehensive activities, including extensive sample collection, AI model refinement, device optimization, and multi-site field testing. Radiolife will train cube scan's AI to recognize RF signatures of hpai, validate its diagnostic accuracy, and assess its performance in real-world settings. The goal is to improve response strategies, enhance biosecurity, and mitigate economic losses for poultry producers, veterinary laboratories, and regulatory agencies.