Medidata, a Dassault Systèmes brand, has launched Medidata Plus, an embedded artificial intelligence layer designed to bring AI capabilities across its entire clinical trial platform. Rather than relying on multiple standalone AI tools, the new offering provides a unified framework that supports study design, data management, analytics and operational workflows throughout the clinical development process. The company aims to help pharmaceutical companies and contract research organizations streamline research operations while reducing the complexity and cost associated with managing disconnected AI solutions.
Medidata Plus introduces automation across several key stages of clinical trial execution. The platform can automatically generate Electronic Data Capture (EDC) and Electronic Clinical Outcome Assessment (eCOA) workflows, create synthetic patient datasets for user acceptance testing and significantly shorten study setup timelines from weeks to hours. It also standardizes data from multiple sources—including clinical trial management systems, wearable devices and real-world data—without requiring custom coding, making it easier for organizations to work with large, diverse datasets.
The platform also incorporates predictive analytics and agentic AI tools to improve trial oversight and decision-making. Built-in analytics continuously monitor studies for potential enrollment challenges and emerging safety risks, allowing research teams to intervene earlier and reduce disruptions. In addition, users can query audit logs using natural language, enabling faster access to compliance information and simplifying regulatory review by transforming complex audit data into actionable insights.
The launch comes as life sciences organizations continue increasing investment in artificial intelligence while seeking greater returns from those technologies. Medidata argues that fragmented point solutions have created data silos, inconsistent governance and higher operational costs across the industry. By embedding a standardized AI layer directly into its platform, the company aims to provide biopharmaceutical sponsors and CROs with a more integrated approach to accelerating clinical trials, improving data quality and supporting more efficient drug development.
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