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Revolutionizing Clinical Trials: A Manifesto for AI-Driven Transformation

2025-06-10 · Mihaela van der Schaar, 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

This manifesto represents a collaborative vision forged by leaders in pharmaceuticals, consulting firms, clinical research, and AI. It outlines a roadmap for two AI technologies - causal inference and digital twins - to transform clinical trials, delivering faster, safer, and more personalized outcomes for patients. By focusing on actionable integration within existing regulatory frameworks, we propose a way forward to revolutionize clinical research and redefine the gold standard for clinical trials using AI.

📄 PDF Abstract BibTeX arXiv:2506.09102

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Tasks

Causal Inference

Methods 이 논문이 사용한 방법론

Causal inference Causal inference is the process of drawing a conclusion about a causal connection based on the conditions of the occurrence of an effect. The main difference between causal…

ITTC @ TREC 2021 Clinical Trials Track

2022-02-16 · Thinh Hung Truong, Yulia Otmakhova, Rahmad Mahendra, Timothy Baldwin 외

This paper describes the submissions of the Natural Language Processing (NLP) team from the Australian Research Council Industrial Transformation Training Centre (ITTC) for Cognitive Computing in Medical Technologies to …

Retrieval

CTG-DB: An Ontology-Based Transformation of ClinicalTrials.gov to Enable Cross-Trial Drug Safety Analyses

2026-03-16 · Jeffery L. Painter, François Haguinet, Andrew Bate arxiv

ClinicalTrials .gov (CT .gov) is the largest publicly accessible registry of clinical studies, yet its registry-oriented architecture and heterogeneous adverse event (AE) terminology limit systematic pharmacovigilance (P…

Revolutionizing Pharma: Unveiling the AI and LLM Trends in the Pharmaceutical Industry

2024-01-05 · Yu Han, Jingwen Tao

This document offers a critical overview of the emerging trends and significant advancements in artificial intelligence (AI) within the pharmaceutical industry. Detailing its application across key operational areas, inc…

Large Language Models in Drug Discovery and Development: From Disease Mechanisms to Clinical Trials

2024-09-06 · Yizhen Zheng, Huan Yee Koh, Maddie Yang, Li Li 외

The integration of Large Language Models (LLMs) into the drug discovery and development field marks a significant paradigm shift, offering novel methodologies for understanding disease mechanisms, facilitating drug disco…

Drug Discovery

AD-CDO: A Lightweight Ontology for Representing Eligibility Criteria in Alzheimer's Disease Clinical Trials

2025-11-20 · Zenan Sun, Rashmie Abeysinghe, Xiaojin Li, Xinyue Hu 외 arxiv

Objective This study introduces the Alzheimer's Disease Common Data Element Ontology for Clinical Trials (AD-CDO), a lightweight, semantically enriched ontology designed to represent and standardize key eligibility crite…