AI medicine is now becoming a number-one game-changer in the healthcare sector. Artificial intelligence can help with diagnosing patients, detecting cancer cells, analyzing patient documentation, and even running clinical trials. Here, this technology speeds up the entire process and makes it cheaper and less prone to errors. Let’s find out more about AI in clinical trials.
Clinical trials constitute the most expensive and time-consuming stage of any drug development. There are many requirements to be met, and each participant is paid to participate in those trials. Given that sometimes thousands of patients participate in just one drug discovery process, we’re talking about millions of dollars.
At the same time, clinical trials are the most important part of the drug development process because they need to confirm that the medicine in development is both effective and safe for patients. This is why pharmaceutical companies pay a lot of attention to this phase.
Until recently, clinical trials were done mostly by humans; only small portions of this process were automated or supported by modern technologies. But with the rapid advancement in healthcare when it comes to technology and AI, clinical trials are now different.
AI in clinical trials – 5 aspects
PARTICIPANT SELECTION
The first element of clinical trials where AI medicine can help is finding the suitable candidates. In clinical trials, often two groups of participants are involved – healthy ones and with a given disease. Moreover, these participants should come from different races, ethnicities, ages and genders to ensure that the medicine in development is suitable for broad use.
AI in clinical trials can considerably speed up the process of looking for these candidates and rejecting unsuitable ones. For example, pharma companies can use this technology to analyze genetic information to identify optimal candidates for the trial. Here, machine learning also plays a vital role – this AI-related technology can significantly reduce data errors and speed up its processing.
Here, there is one more aspect that should be mentioned – patient safety. AI can also increase patient safety during medical trials by identifying adverse events and drug interactions. By analyzing patient data in real time, AI algorithms can alert researchers to potential safety concerns, thus enabling their quick reactions to ensure all patients are taken care of properly during the entire trial process.
DATA ENTRY AND MONITORING
AI in clinical trials can also provide support when it comes to the automation of repetitive tasks, such as participant data entry and monitoring. Clinical trials produce tons of data regarding every patient, as well as their symptoms and reactions to the tested medicine. All that data needs to be analyzed and stored to implement necessary corrections effectively. This is something AI can deal with, thus freeing up valuable time for researchers. This increased efficiency accelerates the research pace and allows for a more effective decision-making process throughout the trial.
MINIMIZING REQUIRED RESOURCES
AI in clinical trials operates as a super-effective assistant to human researchers. It can also help with a multitude of smaller tasks that need to be performed during the trials. By streamlining trial-related workflows, AI can help minimize the need for extensive teams and infrastructure, thereby reducing HR-related expenses. This directly translates to cheaper clinical trials, giving pharmaceutical companies more wiggle room when it comes to trial-related investments.
PREDICTIVE ANALYTICS
AI medicine has one more fascinating application: predictive analytics. This advanced AI-fueled technology uses deep learning to identify potential risks and challenges related to a given medicine trial as early in the trial process as possible. Thus, researchers can identify potential weak points and eliminate them to avoid costly delays.
ERROR AND ANOMALY DETECTION
For humans, finding anomalies in data using manual methods can take a lot of time. AI is much more efficient at that sort of work, and it’s true also concerning clinical trials. AI medicine algorithms can be set to detect errors, anomalies, and inconsistencies in the available trial and patient data. Those algorithms can monitor data quality and integrity in real-time, 24/7, all year round, with no loss in quality. As a result, artificial intelligence tools can help you identify and react to potential anomalies rapidly, thus minimizing the risk of compromising the validity of trial results.
Wrapping up
There is no doubt that AI in clinical trials is a brilliant invention that streamlines the whole process, cuts the costs related to new drug development, and makes drug discovery faster and safer. Many of the solutions we mentioned in this post can be implemented to any clinical trial with just minor adjustments, other need to be designed from scratch for a given trial or medicine.
If you operate in the healthcare sector and you want to benefit from medicine AI, the best thing you can do is consult a trusted AI consulting company that specializes in the healthcare sector. They will help you pick and implement AI-powered tools that will be effective in your situation.
Source: Explore
