A data-driven approach to clinical trials is gaining attention as investigators look to reduce reliance on traditional placebo groups. Synthetic control arms use external datasets—such as real-world hospital data or historical trials—to generate comparator cohorts that can be used when randomized placebo control is impractical or ethically difficult. The spotlight notes practical reasons trials struggle with enrollment, timelines, and statistical power, and describes external control arm generation as a way to increase feasibility in complex and rare disease settings. It also outlines an implementation approach that repeatedly samples patients from an external dataset and uses that output as the synthetic comparator. For developers, the concept can reduce patient exposure to potentially ineffective controls and shorten recruitment needs—while raising new questions about data harmonization, bias control, and regulatory acceptability.