Real-world data products and evidence studies for clinical research
Target RWE builds real-world data products and runs observational and prospective studies, with current focus on hepatology, gastroenterology and dermatology. Its stack pairs EHR interoperability (Epic, Cerner, FHIR, HL7) with Spark, Dask and LangChain/LangGraph, pointing to a push to turn LLM research into production ML systems. Research-heavy, accelerating hiring centers on data reliability, validation and reproducibility for regulatory-grade evidence.
Target RWE is a Durham, North Carolina company founded in 2015 that generates clinical evidence from real-world, longitudinal patient data. It works with US health systems and key opinion leaders to build data products and apply epidemiological methods to questions of medical need, disease progression, and treatment efficacy and safety. Beyond retrospective data, it launches prospective studies for harder use cases. Therapeutic coverage spans liver disease, inflammatory bowel disease, skin conditions, chronic hepatitis B and asthma. The privately held company has 51–200 employees and was acquired by Highlander Health in January 2025.
Target RWE uses Python, PostgreSQL, Apache Spark and Dask on AWS, GCP and Azure, with Epic, Cerner, FHIR and HL7 for health data, LangChain and LangGraph for LLM work, and Terraform, Docker and GitLab for infrastructure.
Yes. Hiring is accelerating and concentrated in research, with some engineering, across mid, senior and principal levels, all in the United States.
Current work includes hepatology real-world evidence studies, prospective studies, scalable ML systems for healthcare analytics, moving LLM research into production, and drift detection and observability tooling.
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Target RWE's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.