Clinical Researcher

As clinical trials become increasingly complex and decentralized, the role of clinical research coordinators (CRCs) has evolved beyond traditional operational responsibilities. This article explores how CRCs are driving digital transformation in clinical trials, the operational challenges they face, and the essential strategies needed to build a resilient, research-ready workforce for the future.

Artificial intelligence (AI) is rapidly reshaping clinical research, with some of its most impactful applications emerging in patient pre-screening and recruitment. By analyzing electronic health records at scale, AI can match potential trial participants to complex eligibility criteria in a fraction of the time required for manual review.

Clinical research professionals working for study sites, clinical research organizations, and sponsors share a commitment to developing medications, medical devices, and other treatments designed to improve and extend quality of life. It’s a higher calling, and we as a clinical trial industry should be proud of these and other accomplishments. But at the same time, as an industry we aren’t living up to our highest potential—and it is the patients who endure the consequences of delayed new treatments and inefficient clinical trials that don’t always represent the full population.

For many study sponsors, particularly small to mid-sized biotechnology and pharmaceutical companies, oversight of the contract research organizations (CROs) with which they partner on projects is one of the most challenging aspects of running clinical trials. Too often, oversight becomes either hands-off neglect, where sponsors assume the CRO will “just handle it,” or suffocating micromanagement, where every report and decision is second-guessed. Neither approach works.

The people collecting and handling clinical data report that the tools and processes currently used in clinical trials are slowing them down. In fact, new industry research shows it might be interfering with the quality of data. Two-thirds of data managers and clinical research associates think data quality in clinical trials is at risk if the inefficiencies in execution persist. This highlights a known challenge in the industry—there are too many manual steps and disconnected technologies that don’t work together to conduct tasks.