The COVID-19 global pandemic is something not seen in modern times. The clinical trial landscape is rapidly evolving. The FDA and EMA have released guidance on the impact of COVID-19 on clinical trials, recognizing the likely need for amendments, and identifying mitigation measures including centralized monitoring, secure drug supply delivery to home, and alternative methods of safety assessments.
Successfully adapting to the challenges created by the pandemic, including trial virtualization, the increased use of eCOA, ePRO, wearables/sensors, and centralized monitoring all require a critical approach to ensure continued trial momentum.
What if you could proactively detect issues and remediate efficiently? How valuable would it be to process real-time data from disparate sources? How would overall trial execution improve with resource efficiencies realized?
Learn how machine learning technology has the power to:
- Connect data from multiple sources to discover the known and unknown risks
- Maintain focus on data quality and patient safety amid centralized monitoring and reduced monitoring capacity
- Generate real-time data insights that help operational staff identify issues, mitigate risks and ensure focus on patient safety
Join us for a discussion and Live Q&A Chat on how to find errors, trends, and anomalies in data—through a number of statistical algorithms and tests that do not require programming—while integrating this process as part of your risk process improvement.