NEW YORK -- Medidata, a Dassault Systèmes brand and the leading provider of clinical trial solutions to the life sciences industry, announced a partnership with neuroscience solutions leader Cogstate to reshape clinical trials and outcomes measurement for central nervous system (CNS) diseases across neurodegenerative, psychiatric, motor, and rare neurodevelopmental disorders, among others.

Together, the companies will deliver an improved experience, supported by Medidata eCOA (electronic clinical outcome assessment) that empowers customers through faster trial starts and optimal rater experiences. This includes a streamlined rater journey through a single mobile device app and a comprehensive suite of data quality assurance solutions for central nervous system (CNS) assessments.

The collaboration addresses the complexities of CNS clinical trials by delivering a fully unified platform for CNS assessment delivery and oversight. By combining Medidata’s industry-leading Medidata Platform with Cogstate’s validated digital cognitive assessments, expert rater training, and monitoring solutions, this relationship will deliver higher quality data collection with increased efficiency and accuracy.

By leveraging the Medidata App, a powerful mobile, site-based solution, with Medidata Rave EDC, and Medidata eCOA features designed for CNS trials, raters will gain greater precision in managing their studies, initiating patient site visits, and completing intricate CNS assessments on the site tablet. The app will also offer upgraded data capture, including enhanced controls and navigation, uniquely flexible annotation options (keyboard text, handwriting, and image capture of external notes), and embedded audio recording with smart transcription to allow for greater scoring accuracy and reducing rater burden.

Biopharmaceutical customers and raters will benefit from single device access to all the ClinRO, ePRO, and PerfO assessments—including Cogstate’s suite of validated digital assessments—offering a more holistic view of patient outcomes. Raters need only conduct a CNS assessment, with data submitted directly into Rave EDC, and connecting seamlessly to Cogstate’s rater monitoring platform for timely review and rater query management, faster trial starts, superior data quality monitoring, and a simplified rater journey.

“The subjective nature of evaluating patients and the potential for data variability pose significant challenges in CNS clinical trials,” said Anthony Costello, CEO, Medidata. “Through our joint efforts, and drawing on Medidata’s deep expertise in eCOA, AI, and sensors, we are enabling the highest endpoint data quality standard, simplifying CNS trial setup, and running automated checks on patient assessment transcripts to minimize study team burden and mitigate the potential for errors.”

In addition to Medidata eCOA, Medidata’s CNS Suite fuses advanced sensor technology and AI-driven analytics to address the unique issues of these trials by employing Medidata Sensor Cloud, AI, and myMedidata, enabling researchers to collect and analyze a vast array of biometric and behavioral data. As a result, they can provide deeper insights into patient outcomes while simultaneously supplying the most patient-centric clinical trial experience through their single portal for life.

“The ability to deliver precise and reliable data is critical for understanding and treating complex neurological conditions,” said Brad O’Connor, CEO, Cogstate. “The strategic combination of science and technology available in the Cogstate and Medidata partnership allows us to deliver unique data quality innovations for more informed clinical trial decision-making and better patient outcomes.”

Cogstate and Medidata are actively working together to create cutting-edge ways to use CNS technology, elevate data capture, and refine patient assessment tools.

Leaders from Medidata and Cogstate will present a keynote and panel session at Medidata NEXT New York, sharing additional details about the partnership as well as the latest advances in CNS clinical trial optimization.