Abstract B030: From genomic discovery to clinical utility: A framework for evaluating the translational impact of the Gabriella Miller Kids First Program

Abstract

The National Institutes of Health (NIH) Common Fund’s Gabriella Miller Kids First Pediatric Research Program (Kids First) was established by Congress in 2015 to identify shared genetic pathways between childhood cancer and congenital anomalies. After a decade, NIH leadership sought to understand how Kids First-supported research has contributed to clinical utility and translational impact. An evaluation framework was developed to characterize the clinical relevance of publications generated by and influenced by the Kids First ecosystem. Using a publication retrieval R script, 4,933 publications were identified across Kids First awardees, Kids First data users, and publications that cited the Kids First program. Publications were categorized into eight clinical utility domains: diagnostics and biomarkers, therapeutics, treatment decision, decision support tools, clinical trials and study design, patient stratification, prognosis and outcomes, and variant interpretation. Disease representation was assessed using MONDO Disease Ontology terms. Classification rules and keyword dictionaries were developed using a generative AI-assisted approach and implemented in R. Variant interpretation emerged as the most prevalent clinical utility category among awardee (46%), user (27%), and broader influence publications (30%). Diagnostics and biomarkers represented 12%, 12%, and 17% of publications, respectively, while patient stratification accounted for 14% of awardee and 15% of user publications. Prognosis and outcomes represented 10% of broader influence publications. Across 4,933 publications in the Kids First ecosystem, these findings demonstrate the program’s impact in generating clinically relevant knowledge, including expanded interpretation of genomic variants, discovery and validation of biomarkers, and refinement of patient risk stratification approaches. Pediatric cancer-related conditions, including leukemia, lymphoma, neuroblastoma, glioma, and acute lymphoblastic leukemia, were among the most frequently represented disease areas. Across the publication ecosystem, 270 distinct diseases and conditions were identified, underscoring the breadth of the Kids First program and its contribution to advancing research in pediatric cancer and congenital anomalies. This framework provides a scalable approach for evaluating the clinical utility of pediatric genomic research programs. By moving beyond traditional bibliometric measures, it enables systematic assessment of how research investments contribute to clinically actionable knowledge and translational impact, providing a model for evaluating future precision medicine and pediatric oncology research initiatives. Generative AI was used to refine abstract text.