Artificial Intelligence/Machine Learning

In this episode of the Applied Clinical Trials Brief, we recap our three most-viewed stories of the previous week with a look into the FDA’s heightened scrutiny of trial design, the wind-down of federal mRNA vaccine programs, and how digital innovation is reshaping the clinical research landscape.

A unified technology approach improves study efficiency and data collection.

Jon Walsh, founder, chief scientific officer, Unlearn, explains how AI-designed therapies and digital twin technology are accelerating clinical trials, improving data precision, and reshaping early-phase drug development.

Despite ambitions to streamline regulatory review, FDA’s Elsa platform has been prone to hallucinations, prompting internal scrutiny and questions about AI reliability and governance.

A new global report finds that clinical research teams are making progress but still lack the skills and tools needed to keep pace with growing trial complexity and emerging technologies.

Why a fundamental reimagining of how clinical studies operate is still necessary to achieve a true paradigm shift—and shed the cycle of reliance on incremental gains.

How the application of artificial intelligence, broader use of real-world evidence, decentralized clinical trials, master protocols, and risk-based quality monitoring, together with strong ethical oversight and increased collaboration, are contributing to better healthcare delivery and strengthening the role of clinical research in driving global health progress.

Why future-ready pharma companies must embrace AI-driven, real-time decision-making.

In this video interview, Kyle McAllister, co-founder, CEO, Trially, shares real-world examples of AI transforming clinical trial recruitment.

In this video interview, Kyle McAllister, co-founder, CEO, Trially, explains how AI is stepping in to fill staffing gaps in clinical research—streamlining patient identification, real-time feasibility assessments, and automated prescreening to help sites stay operational and efficient despite budget cuts.

How clinical operations teams can close the gap between controlled trial results and real-world adoption by generating evidence in broader, more representative patient populations.

At ASCO 2025, clinical operations leaders gained critical insights into how AI tools, bispecific antibodies, and evolving treatment paradigms are reshaping trial design, endpoint selection, and patient stratification.

AI as an accelerator for data-centric, process-centric, and human-centric clinical research.

Brian Ongioni, chief product officer, uMotif, discusses how AI and machine learning can enhance patient-reported outcomes by capturing meaningful feedback at scale and ensuring patient voices are reflected throughout the clinical trial lifecycle.

How human-centered AI that is focused on customer, user, and employee experience can drive real transformation in clinical trials and beyond by aligning intelligent technologies with the people who use them.

Peter Ronco, CEO, Emmes, shares his long-term vision for artificial intelligence in clinical research, from making automation routine to improving drug discovery, transforming regulatory oversight, reducing animal testing, and promoting ethical, equitable data use worldwide.

Peter Ronco, CEO, Emmes, explains how the company is investing in transparent goal setting, comprehensive education, and evolving talent strategies to embed AI-driven workflows across all teams—transforming the culture to embrace technology as a catalyst for innovation and efficiency in clinical development.

Brian Ongioni, chief product officer, uMotif, shares how early collaboration with patients and clinical sites helps shape intuitive, accessible digital health tools—and why co-design is key to building effective clinical research platforms.

Peter Ronco, CEO, Emmes, explains why AI in clinical development still needs human oversight despite widespread hype.

Peter Ronco, CEO, Emmes, explains how public sector leaders are driving innovation in clinical development through automation, long-term data utilization, and experimental trial design—despite the private sector dominating the conversation around artificial intelligence.

Using a recent survey on the adoption of AI/ML conducted by the Tufts CSDD as context, pharma leaders discussed how they are using these technologies to optimize trial execution.

Balancing the emerging benefits of AI in pharmacovigilance with new responsibilities and demands from regulators in enhancing efficiency and safety.

In this Q&A, Megan Bailey, EVP and president of central laboratories and international, Labcorp, discusses how central labs are evolving beyond testing to become strategic partners in clinical trial success.

Recent analysis explores AI's momentum in drug development, showcasing rapid adoption and significant time savings, despite challenges in trust and data governance.

In this video interview, Jim Kremidas, executive director, Association for MultiSite Research Corporations (AMRC), highlights opportunities to improve upon inefficiencies that currently exist in clinical workflows.