
In clinical research, the advent of artificial intelligence (AI) is transforming the way study teams approach their work. AI is no longer just a tool for data processing or analysis; it’s a true “digital colleague”—a virtual teammate with unmatched expertise and efficiency that can complement and inform human intuition and problem-solving. This blend of human…

Managing and analyzing massive amounts of data from multiple sources is one of the most pressing challenges faced by clinical researchers. As trials become more complex, with increasing use of decentralized (DCT) elements and wearable technologies, the data landscape becomes more fractured. Traditionally, this has resulted in silos that prevent organizations from fully understanding or…

Artificial intelligence (AI) is transforming the clinical research landscape. It is being used to optimize how data is collected, organized and moved through electronic data capture (EDC) platforms. Researchers are increasingly curious about its potential to streamline the entire clinical trial process. From study design to data submission, AI is helping clinical trials become more…

Clinical trial delays cost everyone. They cost sponsors in the traditional, dollars-and-cents way. However, they also cost patients and their loved ones when they are forced to wait for life-changing therapies. For many, the wait is just too long. In modern clinical trials, there is no longer any excuse for delays that occur between the…

The Challenge of Device Provisioning in Clinical Trials In clinical trials, gathering timely and accurate data from patients is essential for assessing the efficacy and safety of treatments. However, traditional methods of electronic data collection like electronic patient-reported outcomes (ePRO), can pose challenges when trying to ensure that patients are entering their data correctly. This…

Delays in study start-up and database go-live can create significant challenges in clinical trials. First off, delays cost money – as much as $500,000 per day according to a recent study from the Tufts Center for the Study of Drug Development (Tufts CSDD). Utilizing the right tools within an electronic data capture system like TrialKit…

In our last blog, we brought up the topic of vaporware in clinical research data management. Clinical trials require a lot of tech to collect, manage, and analyze data, and there are so many providers putting out claims about what their products can do. Certainly, we’ve all been in positions where a potential vendor seems…

It is not hyperbole to say that data is transforming clinical research at a breakneck pace. The critical need to integrate multiple data types efficiently and securely arises from this data explosion. eClinical platforms built upon robust RESTful web services infrastructures make these data integrations not only possible, but simple. By leveraging platforms like TrialKit,…

Clinical trial data is evolving – with broader and more diverse sources than ever. This requires new software applications to help collect and analyze mountains of information. Selecting the right eClinical platform is crucial for ensuring the efficiency, accuracy, and success of your trials. With numerous options available, it can be daunting to determine which…