Jeran Stratford

Dr. Jeran Stratford is a pharmacologist and biostatistician at RTI. He is a key contributor to our work in genomics and applied public health, including biomarker discovery, subgroup analysis, and drug repurposing, and a leader in data management and sharing practices that enable cross-study analyses.

Dr. Stratford joined RTI in 2021. His current projects include Pharmacotherapies for Alcohol and Substance Abuse (PASA), the BioData Catalyst Data Management Core, and NCI Somatic Variant analysis. He also leads the development of the RTI Realomics and Resolving Unclassified variants to improve estimates of Disease Incidence (RUDI) service offerings,

Dr. Stratford has developed pipelines to integrate and analyze multi-omics dataset and translate disease-associated gene signals into clinical insight through drug repurposing workflows, into prioritized gene–compound pairs, to support follow-up evaluation, target validation, and dissemination. He has supported multi-omics analyses to identify and prioritize biomarkers of therapeutic response, connecting molecular signatures to clinically relevant outcomes. He has also conducted stratified analyses (e.g., by ancestry and genotype) to characterize heterogeneity in molecular signals and improve interpretability of results across cohorts and study populations.

In the area of data management and sharing, Dr. Stratford has contributed to data standards, harmonization, and centralized data management efforts. This enables the production of interoperable datasets and guidance aligned with FAIR principles and NIH expectations to enable secure, reusable data sharing and cross-study analyses.

In addition to his academic work in pharmacology and biostatistics, Dr. Stratford holds a certificate in Bioinformatics from the University of North Carolina at Chapel Hill. Some of his notable publications include Identifying compounds to treat opiate use disorder by leveraging multi-omic data integration and multiple drug repurposing databases; and Prognosis and oncogenomic profiling of patients with tropomyosin receptor kinase fusion cancer in the 100,000 genomes project.