Unleashing the Power of Artificial Intelligence in Clinical Trials
Artefact's team of experts share their field experience and precise observations through this well-documented report, rich in lessons learned and concrete use cases.
Table of contents:
- [Foreword] AI in Clinical Trials: An ongoing revolution
- Real-world impact: Transformative AI Use Cases across the Clinical Trial value chain.
- Use case 1: Clinical trial design
- Use case 2: Patient recruitment and enrollment
- Use case 3: Execution and management
- Fueling innovation: The expanding ecosystem of AI-driven Trials.
- Challenges ahead: Overcoming barriers and limitations
Get a closer look at transformative AI use cases across the clinical trial value chain:
1) Clinical Trial Design AI streamlines trial design by predicting outcomes and optimizing patient eligibility criteria. Tools like AI-powered clinical trial optimization, algorithm-based trial success prediction, and TrialGPT improve decision-making by analyzing historical data.
2) Patient Recruitment and Enrollment AI addresses inefficiencies in recruitment, with platforms like inato expanding trial access and enhancing diversity and patient commitment. Predictive algorithms identify ideal sites for underrepresented demographics.
3) Execution and Management AI-driven analytics automate data processing, reveal hidden patterns, and generate initial summaries that streamline the conclusion writing process. Advanced tools manage data from decentralized trials, integrating insights to accelerate conclusions. Natural Language Processing (NLP) automates reporting, reducing timelines by over 50%.
Discover thought-provoking insights from healthcare researchers, startups, pharmaceutical companies, and investors, including Servier, Pfizer, Johnson & Johnson, Google, Elaia, Inato, Klineo, Deemea, and Naaia.
Download the report now!