How to Increase Agility in Clinical Trials with RPA

As the world of pharmaceuticals develops at a rapid speed, companies are looking for methods to make menial tasks more efficient, in order to focus on the most important elements of pharmaceutical development. Of course, the new criterion for clinical testing as seen in the Randomized Clinical Trial (RCT) calls for significant organizational and technological development in raising success rates, which often linger around 40-80% due to difficulties in patient recruitment, study design, and other factors.

However, by using RPA, tasks within clinical trials such as patient matching can be automated through the use of RPA bots. Recruitment can be executed through initial virtual interactions that can quickly gather potential subject information and designate qualified subjects. After these automated interactions, clinical employees can continue the follow-up process. 

Focusing on safety, regulatory factors, and trial master processes can help to make drug costs more efficient and help your company to introduce safer, innovative drugs to the pharmaceutical market. Major developments within the pharmaceutical industry can be spurred on by quickly integrating data into complex environments and integrating RPA to improve and simplify administrative tasks.

This can help to quickly approve and bring drugs to the market to consumers that are often impacted by the cost and availability of medications. 

Are companies adopting RPA in clinical studies?

Studies indicate that the use of RPA is associated with significant success in patient matching, in that the automated technologies greatly reduce the need for manual intervention in patient screening.

The optimization of these clinical study processes is known to speed up the time it takes for vital drugs to make their way from the laboratory to the pharmacy shelves. 

How should biopharma companies adopt RPA?

While not every pharmaceutical or Life Sciences company has implemented RPA, it’s certain that most to all companies will implement the technology over the next decade. It’s important to not simply dive in and adopt technologies from all the areas that RPA has to offer. Companies should seriously consider which menial tasks can be best transitioned to an RPA and expect to experiment and potentially even fail. If the wrong system is chosen, the benefits of the technology won’t be as apparent.

Still, with potential failure can come clarity: as RPA develops, even more, innovative ways of utilizing the technology should give way to a more robust clinical trial environment that can effectively bring important pharmaceuticals from the lab to market. Read more about the role of robotics in the life sciences here.


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