Journal Press India^®

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The most trustworthy way to demonstrate the efficacy and security of a treatment or clinical strategy is through clinical trials, which also offer crucial data that informs health policy and medical practice. Clinical research conducted today require a lot of labour, costly, complicated, and subject to biases such as socioeconomic, racial, and gender bias. Poor patient cohort selection and recruitment strategies, along with ineffective patient monitoring in the course of experiments, two of the primary reasons due to significant trial failure rates. Companies or appropriate healthcare facilities are currently using patient-centric strategies to find and interact with trial subjects. Digital resources (such as social media and mobile apps) and cooperation can be used to build a feasible pattern of patient-centric trials that will increase participant diversity, lessen patient burden enhance the availability of clinical trials, and hasten the approval of ground-breaking treatments. The application of artificial intelligence (Artificial intelligence)-enabled technology and real-world data (RWD), or data scientifically from several sources, in the healthcare industry has begun to change clinical trial methodology in recent years. This has allowed for the redesign of important phases in the clinical trial design process. Here, we talk about how Artificial intelligence might change how clinical trials are conducted in the future.

Keywords

Artificial intelligence; Clinical trials; Digital resources; Health care

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