Previously Recorded Webinars

The clinical life science industry is constantly evolving. Having as much knowledge as possible is only going to help you grow and understand the transformation. Keeping up to date with all of the changes that occur within clinical research can be just as important as the actual study.

Medidata provides life sciences professionals with the tools, expertise, and knowledge to power smarter treatments and healthier people. We are committed to helping you answer the hopes of patients and healthcare professionals for a life-saving drug, device or treatment. You build hope. We accelerate it.

Browse through our past events to learn more about best practices to optimize your clinical research.

Single Source of Truth: The Future of TMF Automation

Hear from Frederico Braga, Medidata Principal of Platform Strategy and Adoption, on the value of eTMF integration and automation; Sholeh Ehdaivand from LMK will present on how Clinical Ops & Clinical IT processes can be improved as a result. Learn how Medidata eTMF manages all your data and content--from study planning to close--on one platform, accelerating study startup and ensuring compliance & inspection readiness.  

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The Future of Monitoring Compliance Implications and Technology

As the business of clinical trials evolves into a more complex, cloud-based realm, placing a high premium on an end-to-end monitoring strategy is most crucial. Risk assessment is a very important first step in an organization’s overall monitoring efforts and a major driver for sponsors’ monitoring efforts - as detailed in the amended ICH E6 GCP (good clinical practice) guidelines on risk assessment - yet many sponsors still view it as a routine trial exercise. The future of monitoring compliance: implications & technology”, will focus on understanding ICH E6 as the main driver of an end-to-end risk management approach, and how we can leverage it to more effectively implement a superior risk-based monitoring strategy that ultimately leads to increased compliance and better patient outcomes.

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Precision Medicine in Clinical Development: A Current State of Affairs

Precision Medicine in Clinical Development: A Current State of Affairs,” and hear from Ruthie Davi, PhD, Director of Data Science at Medidata and former FDA Deputy Director, and Jeff Wiser, Medidata’s Sr. Director of Genomics, as they explore and discuss precision medicine’s impact on clinical development. Whether you’re adopting a foundation for precision medicine that ingests, standardizes and analyzes a variety of data, facilitating complex trial design, striving to maintain regulatory compliance, or using advanced analytics, let us help you get closer to achieving your clinical trial goals.

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Bring Your Life Sciences Content Management Strategy into the Digital Age

The life sciences industry is undergoing a digital transformation, as legacy IT systems move into the cloud and cohesive transition strategies are required. Join Medidata, the leader in cloud-based clinical technology, and Box, the leader in cloud content management, for an interactive webinar, “Bring Your Life Sciences Content Management Strategy into the Digital Age." Whether you’re in Quality Control, Clinical Operations, IT, Regulatory Compliance, or manage another area of the trial, join us as we explore how to build a total regulated and non-regulated content management strategy to match today’s unique challenges, including implementing technology via a single, user-friendly platform.

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What Errors Are Lurking in Your Trial Data?

Ineffective and inefficient monitoring of data quality in traditional data management delays risk identification by months. Current methods are resource intensive, and manual processes only identify risks that clinical teams know to look for:

- Up to ~80% of edit checks never fire

- Many edit checks that DO fire are closed without the site fixing the problem

- Many errors are never detected and add risk to drug submissions 

With the advancement of machine learning, there is a more effective way. We’ll present a modern approach to data quality monitoring that uses machine learning to identify anomalies and help you comply with ICH E6 (R2).

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