Big Data for Tiny Patients: A Precision Medicine Approach to Bronchopulmonary Dysplasia

Abstract

Bronchopulmonary dysplasia (BPD) is the most common chronic lung disease of extreme prematurity. Despite more than 50 years of research, current treatments are ineffective, and clinicians are largely unable to accurately predict which neonates the condition will develop in. A deeper understanding of the molecular mechanisms underlying the characteristic arrest in lung development are warranted. Integrating high-fidelity technology from precision medicine approaches may fill this gap and provide the tools necessary to identify biomarkers and targetable pathways. In this review, we describe insights garnered from current studies using omics for BPD prediction and stratification. We conclude by describing novel programs that will integrate multi-omics in efforts to better understand and treat the pathogenesis of BPD. [ Pediatr Ann . 2022;51(10):e396–e404.]

A clinical informatics approach to bronchopulmonary dysplasia: current barriers and future possibilities

“…By analyzing patient-specific data, including genetic markers, clinical history, and physiological parameters, informatics tools can help clinicians predict which neonates are at the highest risk of developing severe BPD and tailor interventions accordingly. This personalized approach aligns with the growing trend in medicine toward precision care and could lead to more effective treatments for BPD (46,47).…”