Looking Ahead: How Technology will Shape Clinical Research in 2021 and Beyond

By Lei Guan

Certainly, none of us will ever forget the year we just survived. 2020 brought challenges most of us never would have expected. But challenging times demand sharp focus and open minds, which leads to innovation and advancement.

In the clinical trials space, we saw this firsthand as sponsors looked to technology more than ever to keep their businesses moving despite the obstacles imposed by the COVID-19 pandemic. We saw a tremendous increase in the use of remote technologies ranging from virtual patient visits to patient engagement and monitoring. While our industry can sometimes be slow to adopt new approaches, the necessity to do business during the pandemic opened minds, and the technologies themselves opened eyes, proving their worth in enabling study execution and delivering quality research data. With many technologies and tech-driven approaches now proven, the industry is hungry to see what’s next.

Following are some of the areas where, in 2021 and the years to follow, I think will produce new and game-changing innovations, helping to optimize what can be accomplished through clinical research

Artificial Intelligence

AI, and the solutions it enables will continue to impact how we execute clinical studies. As we get more comfortable with AI and machine learning, we’ll find new way to implement it in every phase of clinical research. Already it’s in play helping to optimize patient cohorts through predictive analytics related to things like dosing behaviors. We’ve begun using it to help detect improvements in patient symptomatology that are almost impossible to identify accurately and reliably with the human eye. In this way, it’s also working to reduce observer bias. Just recently, it was reported that Google’s DeepMind project is now able to determine the shape of a protein in three dimensions by analyzing its amino-acid sequence. This is a significant leap for artificial intelligence with near-limitless promise for fighting disease and drug discovery.

The use of AI to enable increasingly sophisticated data mining programs will grow in importance. Data mining works to find patterns and relationships in data by combing through vast amounts of information. In clinical research, this often means utilizing AI algorithms to dive into years’ worth of literature and patient outcome data to identify therapeutic needs, but also potential solutions to problems that were previously thought unsolvable. Finding patterns in the data can allow researchers to make accurate predictions for how a new drug might work and on which kinds of patients. The industry has been using data mining tools for many years, but evolving approaches and AI-driven solutions will result in faster and more comprehensive discoveries.

Growth in Cloud Computing

While the transition to cloud computing in the industry has been going on for some time, COVID-19 has accelerated things due to the need for multiple stakeholders to access data securely from any location. This necessity has had the added benefit of convincing the majority of the industry that serverless computing is a secure option that can help save a great deal of cost and that allowing users to access data in near real-time from the device of their choosing can speed up clinical research. This, I believe, will drive tremendous growth in cloud computing in the next few years.

Aside from direct benefits to current clinical studies, serverless computing enables companies to build more agile applications so they can innovate and respond to change faster. The technologies scale automatically from zero-to-peak demands and eliminate operational overhead such as server provisioning and management. While the pay-for-use billing model is still being perfected, as it is optimized, it will help companies manage costs better. All these benefits combine to help companies focus on building better applications and tools and growing new and innovative competencies.


This year promises to be the year when the world truly begins to take advantage of 5G technology. The speed at which we’ll be able to communicate will enable data of all kinds to be shared more quickly and the technology itself is becoming more affordable. In clinical research, the power to monitor and communicate with patients in real-time, enabled by lightning-fast data transfer, will help sponsors make better, faster decisions on things like patient selection, adverse event identification, medication adherence issues and more. In addition to higher speeds, 5G enables low latency, massive scaling in machine-to-machine connections and network slicing  capabilities that will allow the full potential of the internet of things (IoT) to be realized. Edge computing devices and sensors deployed at a massive scale will enable study teams to collect patient data in ways never possible before.  5G promises a path for study teams to engage with patients immediately when needed, helping to solve problems before they can result in data loss.

Remote Technologies Will Power an Increasing Number of Studies

Over the course of 2020, more and more sponsors and study teams saw the power of remote patient engagement and monitoring technologies. Not only were these technologies working to keep studies going and get new studies off the ground during a pandemic that was keeping many patients away from clinics, but they were also helping to produce better, more accurate data. No longer did study teams have to rely exclusively on data gathered during in-person visits; they now could have a continuous stream of patient data coming in via remote solutions. 

Now that sponsors have seen the data possibilities made available through remote solutions, and site teams have seen that technology can keep them better informed while easing their patient-visit burden, there’s no going back to the old way of doing things. I expect 2021 to show how remote technologies can be a permanent feature of any study, complementing and streamlining the important work being done at trial sites and, in general, enabling smaller, faster trials while producing high-quality data.

For more information about AiCure and our AI-powered remote patient monitoring and engagement solutions, visit aicure.com