Medidata
Medidata, a Dassault Systèmes brand and provider of clinical trial solutions to the life sciences industry, has announced the launch of Medidata Clinical Data Studio, a unified experience that unlocks the true power of clinical research data. This groundbreaking technology gives stakeholders greater control over the quality of data and the ability to deliver safer trials to patients faster.
Built on the industry’s only unified platform, Clinical Data Studio integrates data from both Medidata and non-Medidata sources, accelerating decision-making across the full clinical trial process and delivering holistic data and risk strategies that connect patients, sites, and sponsors.
“Clinical Data Studio unlocks the broad ecosystem of clinical data. Powered by embedded AI, we are democratising access to data and revealing the signals, risks, and insights that matter most. Together this accelerates trial execution and creates rich data for new discoveries,” said Tom Doyle, chief technology officer, Medidata.
“As data volume and sources grow exponentially, managing this data and garnering real-time insights is becoming increasingly complex. Not only is this impacting time-to-market, but it is also delaying the timely delivery of therapies to patients, thus impacting patients' lives," said Dr. Nimita Limaye, research vice president, Life Sciences R&D Strategy and Technology, IDC. “By enabling users to manage all their data, both Medidata and non-Medidata data, in one place, Medidata Clinical Data Studio has the potential to disrupt the industry by accelerating clinical trials and getting therapies to patients faster.”
Through AI, study teams can more effectively identify potential data issues and safety signals, resulting in a more accurate understanding of the patient. This reduces the challenges posed by siloed data systems and enables action data review and reconciliation up to 80 percent faster. Clinical Data Studio offers a comprehensive workspace for data integration, transformation, and management. It includes AI-assisted data reconciliation and anomaly detection, self-serve data listings, robust risk-based quality management, and tools to implement a holistic data and risk strategy supported by workflows and visualisations.
