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Qualification program aims to help streamline clinical trial processes
November 14, 2014
By: Kristin Brooks
Managing Editor, Contract Pharma
SGS Life Science Services’ Biometrics group has become a Medidata Rave accredited partner. Medidata Rave, a system for capturing, managing and reporting clinical research data, is designed to help life science companies streamline the clinical trial process. Medidata’s accreditation program for Rave is a qualification program through both build and process enablement tracks, with the aim for partners to provide end-user training, user and site administration, study build, reporting, outputs and migration services. SGS has implemented Rave studies since 2010, and has been a Medidata CTMS partner for five years. “Medidata Rave provides unmatched capabilities for complex designs that we manage in today’s oncology and infectious disease programs, as well as when implementing targeted SDV,” said Luc Braeken, business unit manager Biometrics & Medical Affairs, SGS Life Science Services. “We find that our sponsors benefit greatly from data collection in Medidata Rave, with efficient data conversion to CDISC SDTM compliant datasets at the SGS Data Management center. Our goal is to empower our clients with full visibility on the study data at any moment via the eCRF, progress reports indicating the cleaning status and the CDISC SDTM datasets, which can be delivered soon after FPI.” “Medidata Rave is a well-known system by many sites, allowing immediate data entry from FPI onwards without the hurdles and learning curve that are typically experienced with less-known EDC systems,” said Joris De Bondt, head EDC and Data Standards, SGS Life Science Services. “As a Medidata Rave accredited partner, SGS Life Science Services can offer the best, most innovative technology for clinical trials with a superior site experience. Our eCRF designers now have access to configurable work flows, sophisticated eCRF design, simple and complex edit checking and straight-forward integrations for a wide variety of data sources.”
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