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Recent industry advancements such as DCTs, AI, and machine learning are shaping the future of clinical trials.
Clinical trials will continue to play a crucial role in the future of medicine. With the rise of the Millennial and Gen Z generations, it is important to consider how these demographic shifts will impact the design and execution of clinical trials. As technology advances and our understanding of medicine evolves, the way clinical trials are conducted is also changing. In particular, the future of clinical trials will likely significantly impact Gen Z and Millennials, who have grown up in a digital age and have different expectations of healthcare and research.
One key factor to consider is that Millennials and Gen Z are more tech-savvy and connected than previous generations. This means that they are more likely to be open to using digital tools and platforms for clinical trial participation, such as electronic consent forms and remote monitoring devices. Additionally, these generations are often more accustomed to engaging with health information online and may be more likely to seek out and participate in clinical trials advertised through social media or other digital channels (i.e., Google Ads). I’ve personally found that online advertising works very effectively at recruiting patients within that age group.
Another important consideration is that Millennials and Gen Z are more likely to value personalization and transparency in their healthcare. This means they may be more interested in participating in trials that offer personalized treatment options or provide detailed information about the trial process and potential risks and benefits in an easy-to-understand way. Additionally, these generations have a great interest in expressing their personal values, such as social impact, which may increase the likelihood of clinical trial familiarity and willingness to participate.
One of the biggest changes in the future of clinical trials is the shift towards decentralized trials (DCTs). While the concept is relatively new in the industry, it has gained ground, and regulators have written a recommendation paper. Data collection methods typically used in DCTs can include using smartphones and wearables to collect data and telemedicine to monitor patients remotely.
The benefits of decentralized trials for Gen Z and Millennials are numerous. For one, they allow for greater flexibility and convenience for participants, who can participate in the trial from the comfort of their own homes. This can make it easier for people to participate in trials, particularly those who may have mobility issues or live in remote areas. Additionally, decentralized trials can also help to increase diversity among participants, as people from different backgrounds and locations can participate. All of these factors speed up the drug development process.
Another important aspect of the future of clinical trials and DCTs is the increasing ability to use artificial intelligence and machine learning due to data digitization. For one, they can help increase the speed and accuracy of data analysis, leading to better treatments and faster drug development. Additionally, AI and machine learning can identify new potential drug targets and predict which patients are most likely to respond to a particular treatment. Say goodbye to the tasks of conducting interim data analyses if you can visualize your study’s endpoints and predict them in real time on a dashboard.
However, there are also risks associated with decentralized trials, particularly regarding data security and privacy. As more and more personal information is collected and stored digitally, DCT companies may become the target of hackers and data breaches. Additionally, there may be concerns about the accuracy and reliability of data collected through remote monitoring devices and apps, which could lead to inaccurate results and false conclusions. Furthermore, decentralized trials can make it easier for professional trial participants to participate in multiple trials simultaneously, especially if there is no database to track multiple trial participation.
There are also risks associated with using AI and machine learning in clinical trials. One of the biggest concerns is that these technologies may perpetuate existing biases and disparities in healthcare, as they are only as unbiased as the data they are trained on. Additionally, there may be concerns about the transparency and interpretability of the results these technologies generate, as it can be difficult to understand how they make decisions and predictions, especially for people who need to be trained in data sciences.
In summary, the future of clinical trials will likely significantly impact Gen Z and Millennials and will look very different. Decentralized trials and the use of artificial intelligence and machine learning are likely to become more prevalent, bringing many benefits such as convenience, flexibility, and increased diversity among participants. However, there are also risks associated with these changes, particularly regarding data security and privacy, as well as the potential for existing biases and disparities in healthcare.
Moe Alsumidaie, MBA, MSF, is a thought leader and expert in the application of business analytics toward clinical trials, and Editorial Advisory Board member for and regular contributor to Applied Clinical Trials.