Clinical Trial Analytics & AI
Operate more efficiently today, discover what may be possible tomorrow.
Turn fragmented clinical trial data into an operational and strategic asset.
The Clinical Discovery Platform brings authorized data from across studies, systems, and sources into a private Clinical Data Lake powered by Microsoft Fabric. This allows you to improve operational efficiency with unified analytics and AI agents. Then use natural-language prompts to explore your governed clinical data and accelerate AI-assisted discovery.
MEET THE CLINICAL DATA LAKE
One trusted clinical data foundation—built around your organization.
CDP enables each client to establish its own Clinical Data Lake: a private, governed, and AI-ready foundation that brings together authorized clinical trial data across studies, systems, formats, and sources.
The Clinical Data Lake does not have to replace the systems that run your trials. Veeva, Medidata, CDP, or another application can remain an operational system of record. The Clinical Data Lake makes authorized data available beyond individual applications so it can be harmonized, analyzed, and used more broadly.
Bring together data from across the clinical ecosystem
- CDP Unified Electronic Data Capture, including traditional EDC and Zero Data Entry™
- Other EDC and CTMS platforms, including authorized data from Veeva and Medidata
- Central laboratories, LIMS, imaging, eCOA, ePRO, safety, and pharmacovigilance systems
- EHR/EMR, FHIR, HL7, APIs, real-world data, wearables, and IoMT sources
- Clinical documents, spreadsheets, CDISC datasets, SAS files, and historical trial archives
GOVERNED INTELLIGENCE BY DESIGN
Clinical intelligence must be trusted before it can be useful.
CDP is designed around controlled access, data governance, traceability, and clear separation among source data, transformed data, analytical outputs, and AI-generated assistance. The goal is not unrestricted access to every data point. It is the right data, available to the right user or agent, for the right purpose.
- Private, client-specific data environments and controlled study boundaries
- Role- and permission-aware access to governed information
- Lineage and traceability from insight back to supporting data
- Human oversight for consequential workflows and regulated decisions
- Security, privacy, validation, and retention controls appropriate to each use case
ANALYTICS WITHOUT STARTING OVER
Use Power BI—or the tools your teams already trust.
Power BI provides a deeply integrated Microsoft experience for dashboards, visual analytics, operational reporting, and executive insight. But your Clinical Data Lake is not limited to a single reporting tool.
Clinical operations teams can use Power BI. Executives can continue working in Excel. Biostatisticians can use SAS or R. Data scientists can work in Python. Established analytics teams can connect compatible tools such as Tableau, Qlik, or Spotfire—all drawing from the same governed clinical data foundation, subject to authorization and implementation requirements.
Use Power BI—or the tools your teams already trust.
- Track enrollment, site performance, data quality, monitoring activity, and operational risk.
- Compare performance and outcomes across programs, protocols, geographies, sites, and populations.
- Explore historical and current studies without rebuilding the same data preparation repeatedly.
- Create executive, operational, medical, and statistical views from a shared governed foundation.
- Make trusted data available for advanced analytics, machine learning, and AI-assisted exploration.
MOVE FROM DASHBOARDS TO ACTION
Operational AI agents can help teams identify, investigate, and respond.
Traditional reporting often focuses on what has already happened. Governed AI agents can help teams monitor what is happening now, investigate the context behind an issue, and support the next appropriate action.
Agents can be designed to watch defined conditions, surface exceptions, assemble supporting information, route work, and assist users with repetitive analytical tasks. Human review, permissions, traceability, and controlled operating boundaries remain essential—especially when an action could affect clinical data, trial conduct, or a regulated decision.
Operational use cases
- Identify enrollment, site-performance, or data-quality trends that require attention.
- Summarize aging queries, missing data, and reconciliation exceptions for review.
- Assemble relevant study, site, and patient context before a team investigates an issue.
- Prepare role-specific operational briefs and route approved follow-up work.
Specific agent capabilities depend on the approved workflow, available data, configured permissions, validation approach, and human oversight.
ASK MORE OF YOUR CLINCICAL DATA
AI-assisted discovery grounded in your private clinical data foundation.
The Clinical Data Lake provides authorized AI models and agents with governed clinical context for more relevant, data-grounded responses. Using models and tools available through Microsoft Foundry, medical teams can ask questions in natural language, retrieve supporting evidence, compare observations across studies, and explore possibilities that individual reports may not reveal.
AI-assisted discovery does not prove a new indication or replace scientific judgment. It helps sponsors recognize signals, relationships, and evidence-grounded hypotheses that deserve deeper analysis, scientific review, and—when warranted—further clinical investigation.
What could you discover from your clinical trial data—if it was truly unified, analysis-ready, and AI-enabled?
An overlooked responder population
Identify patient characteristics, phenotypes, biomarkers, or clinical factors associated with unexpectedly strong outcomes.
An unexpected therapeutic signal
Explore beneficial effects, outcome patterns, and relationships that extend beyond the questions the original protocol was designed to answer.
A potential new or expanded use for your product
Recognize converging signals across studies, endpoints, adverse events, documents, and patient populations that may support a new scientific hypothesis or development opportunity.
Example AI prompts
- Which patient subgroups experienced the strongest clinical benefit?
- Were beneficial effects observed outside the primary and secondary endpoints?
- Do adverse-event patterns suggest a potentially useful physiological or therapeutic effect?
- Are similar response patterns present across other studies, products, or historical datasets?
- What potential new uses are suggested by multiple independent signals in our data?
- Which findings appear sufficiently supported to warrant further scientific investigation?
These prompts support exploration and hypothesis generation—not autonomous clinical conclusions. Potential findings require expert assessment, appropriate statistical analysis, and validation for their intended use.
THE COMPLETE CDP DATA JOURNEY
From capture to discovery—on one clinical data foundation.
1
Unified Data Collection
Capture data through traditional EDC, Zero Data Entry™, connected systems, and real-world sources.
2
Clinical Trial Data Management
Validate, review, reconcile, automate, govern, and prepare clinical data for use.
3
Clinical Trial Analytics & AI
Improve operational efficiency and explore new possibilities through AI-assisted discovery.
Your next discovery may already be in your clinical data.
CDP helps you bring the evidence together, explore what it may reveal, and determine what deserves further investigation—all through a private Clinical Data Lake powered by Microsoft Fabric.
Closing brand line: Clinical Discovery Platform — Accelerate Your Discovery.