Today, most people prefer to first search online, learn about, and assess their options before making a purchase decision, be it for a laptop, a mobile phone, a car, or even a house. In many ways, social media has come in to make this process even more democratized – allowing potential buyers to learn from existing customers who are more than willing to share their experiences as reviews and comments.
This trend is however not limited to consumer goods alone and cuts across industries. Social media has given customers a platform to voice their opinion on just about everything that is important to them, including health. To keep up with the times, companies will have to learn how to use this emerging channel to reach out to patients and discover ways through which they can overcome some of the more persistent challenges such as recruiting suitable candidates for clinical trials. According to a recent study, as much as 86% of clinical trials do not reach recruitment targets within their speciﬁed time periods. It highlighted recruitment strategies as one of the contributing factors for this gap.
Social media is a promising platform to connect with target audience across industry domains, and clinical trials are no exception. The first question that comes to mind, however, is: Are clinical trials compatible with social media? The answer is yes; despite the many regulatory constraints, data protection requirements, and participant limitations, social media can still be a valuable tool across a study’s lifecycle. Its benefits can primarily be realized within the context of patient recruitment and evangelizing the drug success.
Putting an ear to the ground
Social media listening can help enterprises learn more about the real life concerns of patients and caregivers, enabling clinical investigators to narrow down their focus on specific issues of interest. The technology itself can be used to scan through numerous conversations on a global scale, in multiple languages, and isolate the discussions around specific diseases or therapies. In addition, the same set of tools can be used to identify most influencer groups that can help companies get the word out about a new drug or a trial. This will help in directing efforts to address the most pressing problems within the patient community and engage suitable candidates for a study.
Robotics Process Automation (RPA) can propagate value by delivering transformation and optimization along infrastructure, efficiency, accuracy, and operations. RPA can sift through millions of patients’ online conversations in order to sort and categorize them. On top of it, machine learning algorithms extract features to identify suitable candidates for trial by parsing large texts, images, and audio-video inputs. Couple it with Artificial Intelligence (AI)- based system, and you can quickly match extracted features with the trial parameters, which will fully automate your patient recruitment process. Clinical researchers can identify and learn a lot about patients who are a potential fit and reach out to them. New segments of patient populations not considered previously may be identified as a result of such analysis, expanding the pool of target individuals as well as impacting channel selection. Recruiters can use health consumer destinations as well as analytics services to determine which destinations are the most heavily trafficked for the target population.
Amplifying human intelligence with AI
Today in the era of Business 4.0, the technological platforms are built to be intelligent, agile, cloud-based, and automated. Also, they are designed to provide scalable processes to manage business risks effectively. These technology driven platforms have resulted in increasing number of patients enrolling in clinical trials also leading to trials’ success through better patient engagement and management. AI is going to be the most promising technology in achieving the goal of faster patient recruitment. This goal can be achieved by better patient screening with the help of intelligent computing capabilities that analyze medical records as well as social conversations in minutes. The other benefit is that the researchers can get notification of event or activity of a particular user or user groups through an automated communication system.
Moreover, big data analytics can be used to dredge up information from historic data archives associated with previous clinical trials. This information is highly valuable for identifying biomarkers and genomic sequences associated with specific diseases. Data science provides statistical data that builds confidence in decision making by detecting variables that can influence the clinical outcomes. This in turn will help the investigator optimize the patient recruitment process. AI can add synergy in post market surveillance over social media along traditional channels of pharmacovigilance by understanding patterns observed across multiple trials, medical records, and adverse drug reactions.
Combining social media and AI is going to make clinical trials more efficient in terms of reducing time and cost, and improving overall outcome. Are you up for including these two elements in your clinical trial plan?