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Many biopharmaceutical companies have increased their emphasis on innovative technologies and data sciences to stimulate a digital transformation across R&D. Underlying successful digital transformations, is the critical need for R&D organizations to leverage information assets to enable enhanced insights, decision making, and process automation.

Address the technical, regulatory and social challenges of using mobile health devices and applications across study teams and utilize a working mHealth framework to support the use of mobile health technology at enterprise scale.

Examine the strategic evolution from manual data processing to approaches incorporating machine learning and predictive analytics for improved data quality and data management operations.

Many large BioPharmaceutical companies are anxiously expanding partnerships with a variety of contract research and specialty organizations in order to cut costs, share risk, and streamline the business. This is not really a new approach.

Externalization is rapidly evolving in Life Sciences well beyond the old outsourcing models. Although the need to innovate has never been greater in R&D, today’s environment is growing in emphasis on effectiveness at each step of the process.

Explore challenges and strategies to enable statistical computing environments based on generalized client projects and a benchmark that crystalizes some of the emerging industry trends.