Placebo-controlled trials continue to face ethical scrutiny, recruitment delays, and rising operational demands. This guide explains how AI-powered SCAs built from real-world data can help address these challenges—supporting faster enrollment, cost reduction, and greater patient trust without compromising scientific rigor. It also outlines why SCAs are increasingly being considered a viable alternative in Phase II and III trials.
Key highlights of SCAs include:
- 85–90% concordance with traditional placebo arms
- 20–30% fewer patient recruits needed
- $35–50M in estimated cost savings per trial
- 30%+ improvement in participation and retention
- Supported by FDA, EMA, and PMDA guidance
Who Should Read This Guide—and Why
This guide is intended for:
- Clinical Operations Leaders seeking approaches that reduce recruitment burden, shorten timelines, and improve feasibility without compromising trial integrity.
- Regulatory and Compliance Teams evaluating SCA methodologies within the context of global regulatory expectations and evidence standards.
- R&D and Clinical Strategy Executives looking for scalable, patient-centric trial designs that balance scientific rigor, ethics, and operational efficiency.
- Biostatisticians and Data Science Teams exploring how real-world data and AI models can be integrated into trial design and evidence generation.
Readers in these roles will benefit from practical frameworks, real-world examples, and clear explanations of when and how SCAs can be responsibly adopted within existing clinical development processes.
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