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AI systems can enhance patient trial process and improve drug success during clinical trials.
Fremont, CA: Clinical trials are a time-consuming and tiring process. Once the testing of a drug or medication begins, researchers can look into the positive and negative impacts of the drug or medication. However, there is a potential of long-term side effects in medical science that can develop into symptoms over time.
Artificial intelligence may be used at many stages in the medical industry, from identifying drug tests to repurposing obsolete drugs. AI assists in enhancing the use of data to discover potential patients and keeping track of the patients' journeys and drug success during clinical trials.
AI is being used for clinical trials in the following four ways:
Designing clinical trials
Traditional clinical trials were done with limited data but using AI, and data can be gathered from various available sources. Regardless of the success or failure rate of previous trials, AI-enabled technologies and systems can collect, organize, and evaluate the data created by them. Such algorithms are capable of determining the most appropriate scenarios and trial times. These intelligent systems can also assist in addressing the shortcomings of previous trials.
Selecting appropriate patient
AI uses the available database to improve patient selection and trial success. Artificial intelligence-based research systems use their algorithms to identify and select the appropriate individual for a trial—this aids in reducing population heterogeneity, which is necessary for a successful trial to begin with.AI algorithms can identify the most likely patients to respond to treatment, ensuring that only the most suitable patients participate in studies to meet the requirements.
Selecting trial site
AI systems can suggest acceptable sites and locations for testing based on that area's geographical and climatic parameters. Sites with proper equipment, trained professionals and emergency facilities are preferred.
Monitoring patient’s condition
AI algorithms utilize patient data to analyze the pre-trial and post-trial conditions of the patient. Wearing smart wearable devices while performing trials can help in monitoring the symptoms of the patient in real-time. AI-based systems record the data whenever they detect changes in patient symptoms after the drug is given to the patient. This data is transferred across various systems for further research and future reference.
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