Downloads: 3 | Views: 194 | Weekly Hits: ⮙2 | Monthly Hits: ⮙2

Informative Article | Health and Medical Sciences | India | Volume 9 Issue 1, January 2020 | Popularity: 5.6 / 10

Rate This Article!      

The Role of Artificial Intelligence (AI) and Real World Evidence (RWE) in Shaping Personalized Medicine

Aditya Gadiko

Abstract: The advent of Artificial Intelligence (AI) heralds a transformative shift in personalized medicine, bringing to the fore an unprecedented opportunity to refine clinical trial design through Real-World Evidence (RWE). This paper explores the confluence of AI and RWE in sculpting a more precise and patient-tailored approach to medicine. By leveraging vast datasets from diverse sources?from electronic health records and genomic profiles to patient-generated data?AI algorithms offer sophisticated analytics that transcends traditional statistical methods. These methods are instrumental in identifying nuanced patient subpopulations and predicting individual responses to therapeutic interventions. Our examination delineates how AI, particularly deep learning and neural networks, sifts through and learns from real-world data, fostering the discovery of intricate biological patterns and treatment correlations. We illustrate how these insights enable the development of predictive models crucial in customizing patient care, thereby maximizing therapeutic efficacy and minimizing adverse outcomes. Furthermore, the paper addresses the regulatory and ethical considerations of integrating RWE in clinical research, underscoring the balance between innovation and patient safety. In doing so, we present a vision of a healthcare ecosystem that is reactive and proactive, characterized by prevention and early intervention tailored to the individual. The synthesis of AI and RWE thus emerges as a pivotal strategy in pursuing personalized healthcare, signaling a shift from a historically homogeneous approach to a more discerning and individualized paradigm in medicine. This leap promises to refine drug development processes, streamline clinical trials, and forge a path toward more personalized, precise, and participatory medicine.

Keywords: Artificial Intelligence, Real World Evidence, Personalized Medicine, Precision Medicine, Clinical Trials, FDA, Machine Learning, Real World Data

Edition: Volume 9 Issue 1, January 2020

Pages: 1919 - 1923

DOI: https://www.doi.org/10.21275/SR24418112417

Make Sure to Disable the Pop-Up Blocker of Web Browser

Click to Cite this Article

Similar Articles