Increasing acceptance of AI-generated digital twins through clinical trial applications.

Autor: Vidovszky AA; Unlearn.AI, San Francisco, California, USA., Fisher CK; Unlearn.AI, San Francisco, California, USA., Loukianov AD; Unlearn.AI, San Francisco, California, USA., Smith AM; Unlearn.AI, San Francisco, California, USA., Tramel EW; Unlearn.AI, San Francisco, California, USA., Walsh JR; Unlearn.AI, San Francisco, California, USA., Ross JL; Unlearn.AI, San Francisco, California, USA.
Jazyk: angličtina
Zdroj: Clinical and translational science [Clin Transl Sci] 2024 Jul; Vol. 17 (7), pp. e13897.
DOI: 10.1111/cts.13897
Abstrakt: Today's approach to medicine requires extensive trial and error to determine the proper treatment path for each patient. While many fields have benefited from technological breakthroughs in computer science, such as artificial intelligence (AI), the task of developing effective treatments is actually getting slower and more costly. With the increased availability of rich historical datasets from previous clinical trials and real-world data sources, one can leverage AI models to create holistic forecasts of future health outcomes for an individual patient in the form of an AI-generated digital twin. This could support the rapid evaluation of intervention strategies in silico and could eventually be implemented in clinical practice to make personalized medicine a reality. In this work, we focus on uses for AI-generated digital twins of clinical trial participants and contend that the regulatory outlook for this technology within drug development makes it an ideal setting for the safe application of AI-generated digital twins in healthcare. With continued research and growing regulatory acceptance, this path will serve to increase trust in this technology and provide momentum for the widespread adoption of AI-generated digital twins in clinical practice.
(© 2024 The Author(s). Clinical and Translational Science published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)
Databáze: MEDLINE
Externí odkaz:
Nepřihlášeným uživatelům se plný text nezobrazuje