Abstract
Preclinical stroke research faces a critical translational gap, with animal studies failing to reliably predict clinical efficacy. To address this, the field is moving toward rigorous, multicenter preclinical randomized controlled trials (mpRCTs) that mimic phase 3 clinical trials in several key components. This collective statement, derived from experts involved in mpRCTs, outlines considerations for designing and executing such trials. mpRCTs offer advantages such as increased sample sizes, robust statistical design, incorporation of heterogeneity, and standardized protocols, but they face challenges in finding the right balance between standardization and heterogeneity, appropriate stroke model selection, and outcome measures, as well as the implementation of complex network infrastructure. We discuss the importance of rigorous study design, including appropriate stroke models, representation of biological variables and comorbidities, functional outcome readouts, and handling of attrition and mortality. Statistical considerations such as adaptive sequential designs, covariate adjustments, and appropriate handling of missing data are also addressed. The integration of machine learning, the implementation of common data elements, and the selection of appropriate therapeutic candidates are crucial for maximizing the efficiency and utility of mpRCTs. Furthermore, the transition toward mpRCT platforms, akin to clinical trial platforms, holds promise for facilitating continuous evaluation of therapies. Finally, we discuss data-sharing practices and the collateral benefits of mpRCTs, emphasizing their potential to improve preclinical stroke research and bridge the translational gap. Altogether, we hope that this article will serve as a starting point for a lasting debate on the future of stroke mpRCTs and their evolution toward a universally accepted set of principles.