There is a growing and continuous need for new drugs and medical treatments. However, the development of a single drug can take several years to complete.
Drug development is also costly and complex – a new medication will only be approved after it goes through rigorous testing and meticulous evaluation in clinical trials. Even going through a trial phase doesn’t guarantee approval. According to an article published in the Congressional Budget Office, only about 12 percent of new medication gets approved by the U.S. Food and Drug Administration.
Additionally, Amber Kingston of Florida explains that a clinical trial isn’t a simple endeavor, either; it involves a lengthy process from screening participants to assessing and monitoring their responses. In recent years, Artificial Intelligence (AI), Machine Learning (ML), and predictive analytics have been utilized in these trials to help streamline the process.
Learn more about how AI is revolutionizing different aspects of clinical trials, from design to patient selection, and data analysis below.
The Top Benefits of Leveraging AI in Clinical Trials
Streamlines Clinical Trial Processes
The integration of AI in clinical trials can significantly shorten the duration of the whole process. With the help of AI, labor-intensive tasks and time-consuming processes can be automated for accuracy, efficiency, and faster turnaround.
One example would be using AI to assist with patient selection. The algorithm is able to analyze substantial amounts of data to determine high-potential candidates suited for the clinical trial, an otherwise lengthy and difficult process for humans.
AI can make patient recruitment easier through a simple rules-based AI approach. AI can examine a hospital database and create a list of high-potential participants. Doctors can use this list to contact the patients and inquire if they are interested to participate in the clinical trial.
Reduces Costs
Because the clinical trial process is streamlined, the costs associated with the process are significantly reduced.
The ability of AI to automate workflows can help R&D teams save time and money, while predictive analytics tools can provide guidance on resource allocation so that companies can make informed decisions with their budget.
Improves Patient Screening
One of the biggest challenges that healthcare professionals face in a clinical trial is responding to the different needs and preferences of each patient, which makes testing treatment more difficult.
AI has the ability to scan a vast amount of patient data and detect patient subgroups that might benefit more from a particular drug, making personalized medicine a reality.
AI can further personalize treatment by determining the right frequency and dosage fit for patients, based on their characteristics and family medical history.
Enhances Patient Experience
Not only does AI make it easier for facilitators of the clinical trial, but they also help improve patient experience.
With the help of the technology, decentralized clinical trials are made possible, enabling remote data collection and patient monitoring. Mobile apps and wearable devices powered by AI can also collect real-time data like vital signs and adherence to medication, which can easily accessed by researchers.
This means that patients can participate in the trial without having to leave the comfort of their homes.
AI is beneficial to the entire clinical trial process – from start to finish; proving the significance of the technology in the future of cynical research.