As clinical trials evolve with technological advancements, wearable sensors and digital health technologies (DHTs) have significantly enhanced data collection by providing continuous, near real-time measurements. Traditional methods, constrained by infrequent site visits and subjective measures, often result in sparse, low-resolution data that limits understanding of patient outcomes. The adoption of wearables in drug development has led to the growth of novel digital endpoints across multiple therapeutic areas, such as stride velocity in Duchenne Muscular Dystrophy and physical activity in heart failure. Regulatory bodies have issued guidance supporting the integration of DHTs, emphasizing objective endpoints. The US Food and Drug Administration’s Digital Health Center of Excellence and guidelines on remote data acquisition exemplify this support. Additionally, frameworks such as the Digital Medicine Society’s “V3+” standardize the validation of fit-for-purpose digital endpoints. Emerging analytical approaches for wearable sensor data, including functional data analysis and handling missing data, further bolster the utility of digital endpoints in clinical trials. Collectively, these advancements allow for a more comprehensive and nuanced understanding of patient health, improving both the precision and applicability of clinical trial outcomes. Ultimately, the integration of digital endpoints revolutionizes patient monitoring, enhancing drug development and regulatory decision-making.