News By: Gary Cramer

The use of artificial intelligence (AI) has become pervasive throughout different fields from agriculture to finance, and healthcare is no exception. While AI has several usages in clinical settings and public health, such as diagnostics, robot-assisted surgery, patient medication reminders, and COVID-19 case surge prediction, here we focus on areas in which AI tools can be used to facilitate clinical research.

This article explores the evolution of ethical standards in clinical research, emphasizing historical violations and contemporary challenges. With a focus on maintaining participant safety, autonomy, and trust, the article provides clinical research professionals with insights into the foundational principles of ethical conduct, regulatory frameworks, and strategies for safeguarding human subjects in modern research environments.

As a follow-up to Clinical Trials Day 2025, held on May 20 with the theme of being “Powered by Purpose,” a collection of industry thought leaders shared their perspectives with ACRP on their clinical research powers, and on what they see as being the greatest current challenges and opportunities for the enterprise.

In today's increasingly competitive clinical research landscape, maximizing existing resources is not just a good practice; it's a necessity. A leaner, more efficient approach to what we do allows for greater productivity, faster timelines, and ultimately, more impactful discoveries.

Despite advancements in oncology, clinical trials for blood cancer face significant challenges in achieving subject diversity. Through a systematic review and meta-analysis, the authors estimate the extent of these challenges and their implications for clinical outcomes. Data from recent trials are analyzed to identify demographic, genetic, and clinical characteristics, highlighting gaps and proposing strategies for improvement.