A patent-pending PETRI dish approach and a computer model of roughly 150 heart signaling nodes with thousands of variables enable virtual testing of drugs and combinations, aiming to predict fibrosis progression and treatment responses.

The model is designed to identify biomarkers for fibrosis, predict patient responses to therapies, and narrow down drug candidates for testing by simulating heart biology and testing multiple treatment scenarios.

The project is funded by the NIH’s National Heart, Lung, and Blood Institute, supporting efforts to uncover drug targets and new therapies by mapping signaling pathways and tissue responses in systolic heart failure.

A key objective is to validate findings by comparing patient-derived samples with experimental results, accelerating translation from model to clinical testing.

The work aims to map how individual patients’ heart cells respond to mechanical stimulation and to identify biomarkers that indicate treatment efficacy and disease progression.

Researchers will use tissue and blood samples from patients with left ventricular assist devices to grow cells in the Fayetteville lab and study how collagen fibers accumulate, fibrosis develops, and electrical signaling is affected.

Collaborations with Dr. Michael Zile and Dr. Amy Bradshaw at MUSC will provide damaged-heart tissue to support the study of fibrosis and tissue responses.

The effort emphasizes personalized medicine, tailoring potential therapies to patient-derived cells and samples to guide pharmaceutical development.

The computational model will identify biomarkers predictive of fibrosis, forecast treatment responses, and potentially reveal drug targets to slow heart damage while guiding virtual drug testing and combination screening.

By enabling virtual testing and target discovery, the model aims to spur pharmaceutical interest in new therapies for systolic heart failure and fibrosis.

University of Arkansas associate professor Will Richardson will lead a four-year, $2.16 million NIH-funded study to investigate systolic heart failure and its underlying fibrosis, with goals of developing personalized treatments.

The grant supports exploring causes of systolic heart failure, identifying potential medications, and leveraging patient-derived data to tailor therapies.