TY - JOUR
T1 - Artificial Intelligence and Novel Trial Designs for Acute Ischemic Stroke
T2 - Opportunities and Challenges
AU - Broderick, Joseph P.
AU - Mistry, Eva A.
AU - Wechsler, Paul M.
AU - Elkind, Mitchell S.V.
AU - Liebeskind, David S.
AU - Harston, George
AU - Wolenberg, Jake
AU - Frontera, Jennifer A.
AU - Kimberly, W. Taylor
AU - Favilla, Christopher G.
AU - Boltze, Johannes
AU - Ospel, Johanna
AU - Samaniego, Edgar A.
AU - Adeoye, Opeolu
AU - Kasner, Scott E.
AU - Schwamm, Lee H.
AU - Albers, Gregory W.
AU - Bolanos, Oscar
AU - Campbell, Bruce C.V.
AU - Carone, Davide
AU - Deljkich, Emir
AU - Rada Eltatawy, A.
AU - Fisher, Marc
AU - Heit, Jeremy
AU - Hill, Michael D.
AU - Houser, Gary
AU - Jauch, Edward C.
AU - Kamel, Hooman
AU - Kjos, Del
AU - Ortiz, Sara
AU - Savitz, Sean I.
AU - Sheth, Kevin N.
AU - Tymianski, Michael
AU - Wakhloo, Ajay K.
N1 - Publisher Copyright:
© 2025 American Heart Association, Inc.
PY - 2026/1
Y1 - 2026/1
N2 - The Stroke Treatment Academic Industry Roundtable convened a workshop regarding artificial intelligence (AI) and innovative clinical trial designs during the Stroke Treatment Academic Industry Roundtable XIII meeting on March 28, 2025. This forum brought together stroke physicians and researchers, and industry representatives to discuss the current use and future opportunities for AI and novel trial designs in acute stroke trials. AI already plays a substantial role in the treatment of acute stroke with regards to imaging but is poised to have a much larger impact in clinical care and research trials over the coming years. The quality and understanding of the data are used to train the AI, the human element needed to ensure training is successful, and the clinician and trialist at the bedside, the humans “in the loop, ” will be necessary to maximize AI’s effectiveness in clinical practice and trials. Platform trials address multiple scientific questions in an area of medicine simultaneously within the same trial structure by sharing controls across multiple interventions. While platform trials increase efficiency and potentially decrease the time needed to answer important clinical scientific questions, they also can introduce complexity to standard workflows. Future acute ischemic stroke clinical trials should incorporate elements of pragmatic and patient-centered trial design when possible. Pragmatic trials aim to assess the effectiveness of treatments when they are implemented into routine clinical care rather than under idealized conditions. AI models and platform, pragmatic, and patient-centered trial designs are new tools to answer important clinical questions, but understanding how they work, their best uses, and their limitations is critical for accelerating successful new treatments for stroke.
AB - The Stroke Treatment Academic Industry Roundtable convened a workshop regarding artificial intelligence (AI) and innovative clinical trial designs during the Stroke Treatment Academic Industry Roundtable XIII meeting on March 28, 2025. This forum brought together stroke physicians and researchers, and industry representatives to discuss the current use and future opportunities for AI and novel trial designs in acute stroke trials. AI already plays a substantial role in the treatment of acute stroke with regards to imaging but is poised to have a much larger impact in clinical care and research trials over the coming years. The quality and understanding of the data are used to train the AI, the human element needed to ensure training is successful, and the clinician and trialist at the bedside, the humans “in the loop, ” will be necessary to maximize AI’s effectiveness in clinical practice and trials. Platform trials address multiple scientific questions in an area of medicine simultaneously within the same trial structure by sharing controls across multiple interventions. While platform trials increase efficiency and potentially decrease the time needed to answer important clinical scientific questions, they also can introduce complexity to standard workflows. Future acute ischemic stroke clinical trials should incorporate elements of pragmatic and patient-centered trial design when possible. Pragmatic trials aim to assess the effectiveness of treatments when they are implemented into routine clinical care rather than under idealized conditions. AI models and platform, pragmatic, and patient-centered trial designs are new tools to answer important clinical questions, but understanding how they work, their best uses, and their limitations is critical for accelerating successful new treatments for stroke.
KW - artificial intelligence
KW - atrial fibrillation
KW - hemorrhage
KW - infarction
KW - ischemic stroke
UR - https://www.scopus.com/pages/publications/105025719482
U2 - 10.1161/STROKEAHA.125.052146
DO - 10.1161/STROKEAHA.125.052146
M3 - Artículo de revisión
C2 - 41025236
AN - SCOPUS:105025719482
SN - 0039-2499
VL - 57
SP - 265
EP - 274
JO - Stroke
JF - Stroke
IS - 1
ER -