Norman M. Goldfarb

AI agents operate only within workflows, but most organizations lack unified workflow management systems, making it difficult to identify where agents should be deployed or ensure they integrate effectively across connected business processes in clinical research.

Study coordinators identify only about 45% of critical and major problems during document reviews, with substantial performance variability across experience levels, but focused training can improve detection rates from 45% to approximately 68%.

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.

Survey from the Site Council gathered insights from its members on the quality of site coordinator work.

Moving towards the development of mature quality management systems.

While measuring and managing site costs can be challenging, these codes can aid in accounting for labor expenses, budgeting for sponsors, and more.

Giving sites and sponsors an effective tool for principled negotiations.

Although there are much larger problems in clinical research, storing obsolete study records is a totally unnecessary cost.

With variation in costs between different stakeholders in clinical trials, there is often disagreement on fair market value.

Minimizing the cost of financing receivables could be the difference between growth and decline.

If a future Supreme Court ruling on diversity were to be applicable to clinical research, the FDA’s positions on diversity will take on even more importance.

Developing consensus answers to these questions can aid industry in avoiding duplicative efforts and implementing new ideas more efficiently.

Measuring different dimensions of diversity beforehand can lead to more thoughtful planning and execution.