Prebic Working Group 2026

We identified this as a pivotal moment in preterm birth research, emphasizing that, despite significant scientific advances, the translational impact has been limited. Preterm birth is currently recognized as a heterogeneous “syndrome of syndromes” resulting from diverse and overlapping biological and pathophysiological mechanisms, such as inflammation, infection, vascular dysfunction, and endocrine signaling.

The field continues to encounter three primary challenges: insufficient alignment between clinical phenotypes and underlying mechanisms, dependence on associative rather than causal findings, and limited translation of research discoveries into effective interventions. Key structural barriers include fragmented data infrastructure, inconsistent biospecimen and clinical data standards, limited global representation, and unequal access to technologies that hinder education and translation in our field. Addressing these challenges will require harmonized international collaborations, standardized protocols, shared data platforms, and capacity-building in regions with the highest burden.

We determined that advancing the field further requires a transition toward precision-oriented research that integrates longitudinal cohort designs, multi-omics data, environmental exposures, and social-demographic determinants of health. Epidemiological approaches should move beyond static risk-factor analyses to adopt dynamic, trajectory-based models of pregnancy. Concurrently, basic science should prioritize mechanistic understanding within complex translational systems and establish more robust pathways for clinical and policy makers.

Importantly, the concept of translation is defined broadly to encompass both novel discoveries and the implementation of established evidence-based practices. There is a huge need to engage patients, clinicians, policymakers, funding agencies, and global partners to enhance translational impact across the field of preterm birth. Organizations such as PREBIC can serve as central facilitators of collaboration, education, and equitable dissemination, aiming to transform scientific complexity into actionable strategies that improve birth outcomes worldwide.

The PREBIC 2026 Committee on Preterm Birth Risk Prediction identified several critical gaps in knowledge, resources, and implementation that hinder progress in reducing preterm birth globally. A major limitation is the continued definition of preterm birth primarily by gestational age, without adequate recognition of distinct biological and clinical phenotypes. The group emphasized the need for phenotype-based classification systems to improve prediction, prevention, and personalized interventions.

Existing biomarkers show limited predictive accuracy, particularly in low-risk populations, and often fail to distinguish symptomatic from asymptomatic women. Most studies have been conducted in high-income settings, with insufficient validation across diverse populations and low- and middle-income countries (LMICs). Delayed antenatal care access, high costs, and limited laboratory infrastructure further restrict implementation in resource-limited regions.

The committee highlighted the need for dynamic longitudinal screening throughout pregnancy, especially during the first and second trimesters, recognizing that risk profiles evolve over time. Future predictive models should integrate clinical, biological, microbiome, environmental, and biomedical engineering data, while incorporating artificial intelligence and machine learning approaches where appropriate.

Priority areas for future work include development of standardized core datasets for preterm birth prediction, harmonized phenotyping strategies, inclusion of LMIC populations in multicenter studies, and validation of affordable home-based predictive tools.

Key concepts and literature areas include preterm birth phenotyping, precision medicine, longitudinal biomarker profiling, microbiome-associated risk prediction, and AI-driven predictive modeling in obstetrics.