Dassault Systèmes company Medidata has unveiled a new patient-centric native myMedidata app to accelerate the start up of clinical trials and enhance patient experience.
The app was created to offer trial subjects an option for a smooth platform experience and one login for all of their remote trial works.
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With a preliminary focus on electronic clinical outcome assessments (eCOA), the app will have all the myMedidata patient-centric solutions.
Available on iOS and Android, the app can be used on patients’ own devices (BYOD) or through an assigned device of the patients.
In addition, it is integrated with the Medidata Platform, including Rave electronic data capture (EDC).
This offers a self-sustaining ecosystem where input from the patients, site-based works, and data management carried out behind the scenes work together smoothly.
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By GlobalDataA new platform configuration tool named Medidata Designer is used for configuring the app, offering a patient-centric, mobile-first workflow builder for app.
Sponsors and CRO partners can leverage Designer to create a robust patient experience through drag and drop screen templates and visual workflow tools.
These templates and tools in the background establish a clinical database, without requiring any special code.
Designer also reduces the build times of the trial by utilising Medidata and client libraries, which include pre-built eCOA instruments, translations, and trial configurations.
Medidata Patient Cloud senior vice-president Matt Noble said: “Our latest addition to myMedidata brings an innovative app to patients designed in concert with our patient insights team, customer feedback, and the experiences derived from running the world’s biggest DCTs over the last twenty years.
“Medidata is leveraging its unique insights from sponsors, CROs, sites, and patients to make a meaningful difference in the clinical trial experience.”
In November this year, the company announced plans to launch the scalable technology, Rave Companion, which aids trial sites in saving time and reducing errors while automating electronic health record data to the Rave EDC system.
