Project Summary Breast cancer is the second most commonly diagnosed malignancy and distant spread to other organs is a leading cause of cancer death. The treatment of metastatic breast cancer remains very challenging and requires serial radiological monitoring to ensure that the patient is on the right treatment at the right time. This process typically requires repeat CT or PET imaging scans which are expensive and subject patients to potential adverse reactions, including contrast-related allergies and organ damage. The cost of radiological monitoring has increased dramatically, at least as rapid as drug costs. Furthermore, because the radiological testing is relatively infrequent, many stay on ineffective treatments too long. During this period the disease may progress, leaving the patient under-treated with prolonged exposure to unnecessary toxicities and at significant cost burden, especially with newer targeted-therapy drug classes. At the other end of the spectrum, patients with durable response may be assigned to prolonged radiological imaging over the course of their management. Genomic characterization of cancer has revolutionized our ability to decipher the complexities of tumor biology and promote more precise cancer treatments. Advances in DNA sequencing have enabled the detection of mutations in the tumor and now in tumor DNA that circulate in the blood (ctDNA). Cell-free circulating tumor DNA has been proposed as a surrogate biological sample to define the genetic change(s) of a primary tumor and/or metastatic disease in a cancer patient, and to serve as a biomarker for diagnosis, prognostication, and monitoring of response to therapy. However, next generation sequencing (NGS) ctDNA panels are expensive and are typically not reimbursed when used for serial monitoring of disease. In this application we propose a low-cost strategy for dynamic molecular monitoring of metastatic breast cancer patients using bespoke digital droplet PCR (ddPCR) assays constructed from a baseline NGS ctDNA test. We hypothesize that this hybrid approach will offer a substantial lead-time over radiological detection of disease progression, allowing for adaptive treatment changes that will reduce the time patients are exposed to ineffective treatment and exposure to unnecessary toxicities. This cost-saving effort will substantially improve disease monitoring in metastatic breast cancer patients, reduce toxicity associated with ineffective treatment, improve clinical trial enrollment and serve as a viable approach to addressing cancer health inequities among underserved populations with limited access to imaging due to the cost of these procedures.