Technology

As clinical trials become more complex and decentralized, the role of the CRA is evolving from site monitor to strategic, digitally fluent partner, requiring expertise in hybrid oversight, risk-based monitoring, and multi-system data management.

As AI adoption accelerates across clinical research, clear distinctions between AI agents, AI teammates, and integrated intelligence are essential for understanding how automation will reshape site operations, workforce roles, and end-to-end study processes.

AI-enabled automation is rapidly moving into routine pharmacovigilance operations, streamlining case intake and processing, reducing longstanding adoption barriers, and driving new efficiencies as sponsors and functional service provider partners scale safety workflows.

A new global Tufts CSDD survey of 387 investigative site professionals reveals broad experience with digital and decentralized trial tools, growing site-driven technology investments, and strong support for remote data collection—while highlighting persistent burdens tied to fragmented systems, training demands, and financial strain.

Emerging applications of AI/ML, automation, and digitization are helping sponsors cut clinical trial start-up times to as little as four weeks, reduce data errors, and enhance patient engagement—demonstrating how tech-enabled processes are reshaping trial efficiency and experience across the study lifecycle.

Leveraging real-world data and AI-driven insights in clinical trial planning can reduce enrollment failures, improve retention, and prevent costly rescue studies by providing a more accurate view of patient populations and site feasibility.

Melissa Hutchens, vice president of research & benchmarking at WCG, and Jimmy Garza, senior director of clinical operations at Bayer, discuss findings from the latest WCG CenterWatch Global Site Relationship Survey, revealing a decline in overall site satisfaction. They explore key drivers behind this trend, including technology usability, communication gaps, and limited site input in protocol design, and share actionable approaches to strengthen sponsor-site partnerships and improve study execution.

As biotechs expand their outsourced clinical operations, adopting a CTMS is becoming essential to ensure CRO oversight, regulatory compliance, and real-time visibility across trials and portfolios.

In 2025, both big pharma and biotech are redefining decision-making as AI, real-world evidence, and flexible deal structures accelerate drug development, flatten organizational silos, and close the innovation gap across the life sciences ecosystem.

In a decentralized, digitally enabled clinical trial environment, conventional approaches to data analysis are evolving as sponsors utilize technological tools in new ways to ensure compliance with global standards, mitigate risk, and bring life-changing therapies to patients faster.

Learn how increasing system complexity and patient-facing technologies are creating new burdens for clinical trial sites—and what vendors and sponsors can do to streamline operations and improve support.

Exploring how large-scale patient databases and AI analytics can accelerate site activation, strengthen recruitment, and improve trial design from the start.

Thermo Fisher will integrate OpenAI APIs into its Accelerator Drug Development platform and clinical research business, while Lundbeck deploys ChatGPT across its global workforce to drive R&D and commercial innovation.

Addressing the imbalance in clinical trial workloads by empowering mid-level investigators and using AI to expand access to high-quality, diverse research leadership.

Examining how artificial intelligence can help identify true key opinion leaders in emerging markets to improve site influence, patient engagement, and trial success.

As decentralized and hybrid trial models expand, eConsent is emerging as a critical tool for improving participant understanding, reducing site burden, and strengthening data integrity through digital automation, accessibility, and regulatory compliance.

How a unified approach to clinical data management, powered by artificial intelligence and advanced analytics, can elevate clinical trial monitoring and redefine how teams assess, act on and learn from data.

Learn how early regulatory engagement, validated digital systems, and robust protocol design enable biotechs to run parallel studies without compromising compliance or data integrity.

As pharma wrestles with whether to trust fully autonomous AI, semi-autonomous agents are emerging as a safer middle ground that reduces manual work, eliminates white space in clinical development, and accelerates trial timelines without compromising patient safety.

Uncover how improving data accuracy and leveraging synthetic control arms can optimize trial efficiency, reduce costs, and generate stronger real-world insights.

Sustainability should be central to clinical trial design and considerate of how digital tools such as electronic clinical outcomes assessments can help achieve this.

Examine strategies for validating, monitoring, and safely deploying configurable AI agents to ensure compliance and performance in clinical trials.

Capturing insights from clinical research professionals on the key trends and challenges shaping drug development today, from those in clinical trial operations and site relationships, to technology and AI, and the evolving regulatory and policy terrain.

Take a closer look at how agentic AI can automate repetitive monitoring tasks while keeping human oversight central to critical decision-making in clinical research.

Regulatory inspections of interactive response technology systems have surged 140% since 2022, signaling intensified global scrutiny of data integrity, randomization, and system validation in clinical trials.