decentralized clinical trials

Decentralized Clinical Trials; More than Industry Buzzword

In the last decade, there has been a gradual increase in the acceptance of decentralized clinical trials (DCTs), one trend that has accelerated dramatically due to the pandemic.

Now, there will be no going back, primarily due to the convenience and flexibility for patients. By minimizing the burden of participating in a clinical trial, sponsors simplify recruitment and increase retention and compliance. Study effectiveness is amplified, and drugs get to market faster, saving patient lives and sponsors’ money. 

Largely conducted remotely, these trials use technology and other novel solutions to minimize the patient’s need to travel. Site visits may be replaced by visits from a home nurse, or to the patient’s own primary care physician. At the same time, wearables, apps, and home-monitoring devices collect data on an ongoing basis. With all the complexities needing carefully tracked, analyzed, and managed data, it’s not surprising that while patients prefer this alternative to site-anchored studies, DCTs are not always simple for sponsors and contract research organizations (CROs).

This has led to sponsors being as wary of Decentralized Clinical Trials as patients are appreciative of them. Sponsors often feel that DCTs increase operational complexity, business risk, and regulatory hurdles. However, with the right technology, the seven mentioned below, those fears are unjustified;  

·       Collects all data in any form: A platform that is able to aggregate, analyze, and visualize all the data collected across trials, including data from wearables, apps, and more traditional forms of data collection is pertinent. 

·       Harmonizes that data: Collecting the data is not enough, but finding a system that can integrate data across 

·       Supports detailed examination: The same attention to detail that clinical research associates traditionally supply onsite—is needed remotely. Look for a system with dynamic drill-down capabilities for further interrogation of issues with source data. 

·       One able to process calculated metrics: Comprehensive risk management requires in-depth analysis. You want the flexibility to set user-defined metrics for more relevant analyses and greater actionability.  

·       Should have a built-in audit trail: Regulatory bodies require demonstrated proof of monitoring and risk-based data management; some systems provide that automatically. 

·       Offers machine learning capabilities: Machine learning enables systems to quickly analyze data and provide near-real-time insights, facilitating many aspects of risk-based monitoring. 

·       Supports independent system set-up and use: The ideal platform should self-sufficiently enable receiving support from the vendor when you want it, but not require perpetual services in order to operate effectively.  

Xcene Research believes that being armed with these seven features in a data-management platform, will strengthen sponsors’ and CROs’ belief that data management can be streamlined, risk-based monitoring will be readily accomplished, and that all regulatory requirements will be met automatically.

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  1. Pingback: Driving Equity in Clinical Trials with a Diversity First Mindset…….Meeting The Need. - Xcene Innovate

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