Are You Harnessing The Power Of Your Clinical Data?

In clinical development, we all strive to deliver therapies that improve patients’ lives. However, the clinical data we generate can profoundly impact our success in achieving this goal. A high-quality clinical data package is a fundamental requirement for a new therapy to obtain approval from regulators like the Food and Drug Administration (FDA) or the European Medicines Agency (EMA), as well as other stakeholders such as payers and health technology assessment (HTA) agencies. As such, ensuring data quality can increase your chances of successfully bringing your therapy to market or licensing it to another company.

However, generating high-quality clinical data is far from straightforward, especially if you don’t have the appropriate in-house expertise. For example, statistical validity, source type, and clinical relevance are just some of the many factors that can affect the quality of the data produced. What’s more, it can be challenging to manage increasingly vast and complex datasets while safeguarding data quality, such as when collecting real-world data using digital devices.

It can be extremely risky to deprioritize your clinical data strategy. You could lose considerable resource investment with no gains, and companies with a smaller portfolio may jeopardize their viability if their few assets fail to gain regulatory approval. Even more concerning is the risk of having to stop investigation into a promising therapy that could have been life-changing for many patients.

Considering all of this, Planning your data strategy, including your trial design, is crucial to ensure the quality of your evidence package so that you can manage risk and increase the chances of successful clinical development. Although most companies devise data strategies for their clinical programs, this often happens quite late in the development process, long after the time when a data strategy is most useful. In the best case scenario, your program will not reap the full benefits of a well-planned data strategy. In the worst case scenario, the evidence package will be of insufficient quality and you will fail to gain regulatory approval for a promising new therapy.

In this eBook, we discuss what is involved in planning a clinical data strategy for the entire duration of a development program, as well as for Phase 1 and Phase 2 trials specifically. We also outline some best practices for planning your data strategy, including tips from Cytel experts working in our Strategic Consulting, Clinical Research Services and Data Management teams. With even small, easy to implement changes to your data strategy, you could enhance your chances of success and ensure the therapies you develop ultimately reach patients.