Real-world evidence (RWE) studies often stall on the same friction points: defining the most appropriate cohort, identifying the relevant codes, and curating data to produce an analysis ready dataset. Often external partners and datasets don't offer transparency resulting in a lack of insights and the ability to reproduce findings.
For emerging and mid-size biopharma, especially teams without resources, including budget or a large bench of analysts, those steps can stretch from weeks to months and even years if they involve manual collection of patient data. To meet the market demands, HealthVerity eXOS applies an agentic AI approach to compress that research cycle.1 In practice this means autonomous but human-researcher supervised agents translate a plain-English question about real-world data into structured designs, execute data prep and analyses, and return interpretable outputs with human checkpoints.1
The most noticeable gains tend to be turnaround time on standard epidemiologic questions, generation of meaningful figures and graphics and a clear methodology including the full code used, that can be reviewed by other researchers. That combination is particularly powerful for smaller organizations that need credible RWE quickly without a heavy data analysis infrastructure.
Prompt example given to HealthVerity eXOs.
Think of HealthVerity eXOs as an evidence studio rather than a black box of AI. The platform carries out familiar epidemiologic designs that cover much of day-to-day RWE questions with applied enrollment periods. Some common examples (but not limited to) include:
By capturing definitions, parameters, and execution details, it makes the mechanical parts of RWE easier to repeat across therapeutic areas and study variants because the output and “step-by-step thought process” of the tool is fully visible to the user, and can be edited even before analysis begins.
Beyond retrospective epidemiology, HealthVerity eXOs can also accelerate stages of clinical development by bringing real-world evidence into trial design, feasibility, and post-market evaluation.
In early planning, agentic AI can use HealthVerity real-world healthcare data (RWD) to identify and characterize potential patient populations and estimate enrollment feasibility across therapeutic areas or geographies. During protocol design, the same workflow can uncover baseline event rates, treatment pathways, and comorbidity patterns. Once a study is underway, HealthVerity eXOs can analyze control arm comparators using real-world populations. After approval, the same framework scales into safety signal monitoring, label expansion analyses, and outcomes analysis, creating continuity between pre-market research and post-market evidence generation.
HealthVerity eXOs runs directly on HealthVerity RWD. That means your studies execute against fully privacy-compliant healthcare data that is routinely updated from sources with clear data rights and usage controls. For researchers, the practical upside is less time wrestling with data onboarding and more time specifying the question and reviewing results.
HealthVerity eXOS accelerates real-world evidence generation by turning traditional, linear study workflows into an automated, agentic pipeline. What once required long manual coordination across data, analytics and documentation now runs in a structured sequence of supervised AI-driven steps. The method is simple to describe and powerful in practice:
Ask → Design → Prepare → Analyze → Interpret
For emerging and mid-size biopharma teams, HealthVerity eXOS offers a practical way to speed up credible RWE by standardizing core methods and making each step reproducible and reviewable. You get consistent study designs, transparent lineage, and faster turnaround without a dedicated analytics organization. A recent webinar wrap-up covered the capabilities of HealthVerity eXOs in detail, read more here.
If you’d like to pressure-test your current business questions, consider sharing up to 3 questions and we'll run them through HealthVerity eXOs and share the method and results. Ready to see how your questions perform under an agentic workflow? Let’s set up a demo.