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Discover the Value of an Optimized Clinical Data Strategy


To continue our Summer Weekend Reads series, Cytel presents “Discover the Value of an Optimized Clinical Data Strategy” by Natasa Rajicic, Executive Advisor, Strategic Consulting; Pauline Surrel, Senior Director, Global Head, Clinical Data Management; and Virginie Cessinas, Vice President, Business Development. Please click below to access the full publication.

High-quality clinical data is the cornerstone of any clinical trial, driving the decision-making process of drug development. And it is a fundamental requirement for regulator approval of new therapies. But generating high-quality data is far from straightforward, the lack of which impacts clinical development timelines and adds additional costs for sponsors. This is compounded by the increased complexity, volume, and proliferation of data sources, adding to the challenges faced by data managers to streamline and standardize this growing body of information.

To avoid these pitfalls, it is essential to prioritize planning clinical data strategy early in the development process for the entire program or portfolio. The earlier the planning, the more likely the processes and procedures implemented will yield high-quality data.

A strategic data plan crafted early on – rather than late in the development process or only on a trial-by-trial basis – can help define the approach to data collection, storage, and analysis; can ensure the design, build, and delivery is fit for purpose; can address data issues proactively and in real time, minimizing delays and improving data quality; and can help ensure decision-makers will approve the new therapy.

Our eBook, linked below, on the value of an optimized clinical data strategy discusses key elements of clinical data strategy planning for the duration of the development program, specifically for Phase 1 and Phase 2 trials. It outlines best practices and shares insights from industry experts. Topics include:

  1. Key Considerations in Planning Your Clinical Data Strategy

  2. The Value of Planning a Program-Wide Data Strategy, Earlier

  3. Planning Phase 1 – Mitigating Unknown Risks Before They Arise

  4. Planning Phase 2 – Ensuring a High-Quality Evidence Package

  5. Top Tips on Optimizing Your Data Strategy Planning

To learn more, click to download the full publication:


Download Publication



Read more from the Summer Weekend Read series:

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