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Causal inference and digital twins: a roadmap for the future of clinical trials.

Created on 24 Jun 2026

Authors

Silas Ruhrberg Estévez, Richard Peck, Eoin McKinney, Jim Weatherall, Stuart Bailey, Justine Rochon, Chris Anagnostopoulos, Pierre Marquet, Anthony Wood, Nicky Best, Harry Amad, Julianna Piskorz, Krzysztof Kacprzyk, Rafik Salama, Christina Gunther, Francesca Frau, Antoine Pugeat, Ramon Hernandez, Mihaela van der Schaar

Published in

NPJ digital medicine. Jun 23, 2026. Epub Jun 23, 2026.

Abstract

Clinical trials generate essential evidence on treatment safety and efficacy, but slow timelines, high costs, and limited inclusivity constrain efficiency, generalisability, and clinical impact. Causal inference and digital twins offer complementary tools to define estimands, characterise treatment-effect heterogeneity, assess transportability, and simulate patient trajectories under alternative interventions. Integrated responsibly into trial design, recruitment, monitoring, and post-trial translation, they could support faster, fairer, and more informative clinical trials.

PMID:
42337047
Bibliographic data and abstract were imported from PubMed on 24 Jun 2026.

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