SBIR Phase II:Development of AI Software to Capture and Identify Circulating Rare Cells in Lung Patients

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project is a new cancer treatment liquid biopsy product using Artificial Intelligence (AI) that can detect and classify cancer derived rare cell (CRC) from a blood draw.There are over 100 different types of cancers and over 1.9 million new cancer cases are expected to be diagnosed in the US in 2022 resulting in over 600,000 deaths (1,670 deaths per day). Cancer is the second most common cause of death in the US, exceeded only by heart disease. New treatment therapies are being developed for a substantial proportion of cancers with many clinical trials for new therapies on-going world-wide. The minimally invasive, high sensitivity blood test will monitor therapeutic response and progression at low-cost, supporting development of these new cancer treatments.Specifically, with a less invasive and more comprehensive diagnostic tool, the test results will give clinical researchers real-time insights into cancer tumor biology, providing better understanding of cancer heterogeneity._x000D_ _x000D_ This Small Business Innovation Research (SBIR) Phase II project combines Artificial Intelligence (AI), specifically deep learning neural networks used for computer vision, with CRC immunofluorescent reagents integrated into an immunofluorescent microscope.The main objective of this effort is to identify and classify CRCs with high accuracy. There is increasing evidence that CRCs are correlated with cancer type, staging, treatment response, minimal residual disease, and overall disease progression. However, in a typical blood sample, there are over 7 million blood artifacts with very few CRCs present.Current techniques to analyze CRCs are expensive, lengthy, and are limited in automation.To meet project sensitivity, specificity, and runtime requirements, the AI image analysis will be further optimized to:1) find CRCs, 2) discriminate against false positives, and 3) classify CRCs into clinically relevant types.The developed AI architectures will be selected through extensive training using thousands of clinical samples compared to expertly characterized cancer blood pathology images.After high sensitivity and specificity are demonstrated, development work will continue to mature the AI-revolutionized CRC liquid biopsy test to meet clinical research use only (RUO) requirements. For the cancer research community, the product offering will be used in the conduct of non-clinical laboratory research._x000D_ _x000D_ This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.