AI Agents – The Meaning of the Concepts

Posted: 19 Jun 2025

Olga Kubassova

Artificial Intelligence (AI) is revolutionizing industries and transforming the way machines interact with the world. One of its most intriguing components is the AI agent—an intelligent system capable of making decisions, learning from data, and autonomously performing tasks. Unlike traditional software, AI agents operate dynamically, adapting to new inputs and optimizing their performance over time.

So, what is an Clinical Trial Imaging?

Imaging in clinical trials is a cutting-edge approach that uses advanced technologies—such as MRI, PET, CT, and ultrasound—to gather objective visual evidence on drug safety and efficacy, disease progression, and the impact of therapeutic interventions

What Does Imaging Mean for Clinical Trials?

Imaging represents a non-invasive way to assess and quantify biological changes in participants during a trial. Where classic clinical endpoints (symptoms, lab results, or survival) might take months or years to appear, imaging can reveal changes in tissue structure, tumor size, or molecular activity much earlier. This allows researchers to detect efficacy signals or safety concerns with greater speed and precision.

Imaging Endpoints and Biomarkers:

Imaging Endpoints: These are specific measurements derived from imaging data used to evaluate treatment effects. For example, a decrease in tumor volume on MRI may serve as a primary endpoint indicating drug activity.
Imaging Biomarkers: Quantitative measures extracted from images (e.g., lesion size, vascularity, metabolic activity) act as surrogate markers for disease progression or therapeutic response. Regulators, including the FDA, recognize these biomarkers in expedited drug approval pathways—provided the data is rigorously standardized.

Why Is Imaging Indispensable in Modern Trials?

Imaging offers several strategic benefits:

Support for Regulatory Submissions: Imaging data, when standardized, supports regulatory filings, helping drugs and devices reach patients faster.ep learning, and reinforcement learning, to continuously improve their performance, as documented by the Berkeley Artificial Intelligence Research Lab.

Early Outcome Detection: Visual changes often precede clinical symptoms, enabling faster go/no-go decisions in drug development.

Reduced Trial Costs and Timelines: Reliable imaging endpoints can shorten the time needed to demonstrate efficacy or safety, meaning fewer participants and speedier approvals.

Objective, Quantitative Data: Imaging provides data that’s reproducible and less subjective than clinical assessments, strengthening the statistical power of trials.

Best Practices and Regulatory Considerations

Regulatory authorities emphasize the importance of standardized imaging protocols, blinded image reading, rigorous quality control, and centralized data analysis to ensure reliability and compliance. Choosing the right imaging endpoints for the study’s objectives and disease indication is crucial; referencing guidelines and past studies helps ensure alignment with regulatory expectations.

Conclusion

In summary, imaging in clinical trials transforms the way new therapeutics are developed, offering visual clarity, robust evidence, and accelerated decision-making. Understanding these concepts is essential for trial sponsors, sites, and all stakeholders aiming to advance meaningful innovations in medicine.