Artificial Intelligence/Machine Learning

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

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.

A blend of FSO and FSP models in the landscape of artificial intelligence can ensure CROs stay up to date with the unique demands of industry.

How digital intake solutions driven by technological advancements can help overcome the challenges of operating across different regulatory markets.

In this video interview, Michel van Harten, MD, CEO, myTomorrows, discusses where the clinical research industry currently stands with AI adoption.

A pragmatic approach to streamlining technology and innovating processes will help advance clinical data management.

Companies share their experience in future-proofing clinical data technology.

In this video interview, Derek Ansel, vice president, therapeutic strategy lead, rare disease, Worldwide Clinical Trials, discusses how artificial intelligence can aid in bringing therapies to rare disease patients faster.

An increase in protocol complexity is paving the way for machine learning models to optimize trial design.

Andrew Mackinnon, Executive GM, Medable, discusses how AI-driven innovations are streamlining clinical trials through enabling scalable operations.

In this video interview, Rachael Higgins, chief commercial officer, PicnicHealth, discusses industry’s next steps in being able to maximize the benefits of virtual models.

Leveraging artificial intelligence-powered stochastic methods for clinical data review represents a significant leap beyond traditional approaches.

In this video interview, Rachael Higgins, chief commercial officer, PicnicHealth, highlights how addressing these challenges can aid industry in moving more towards the future.

In this video interview, Rachael Higgins, chief commercial officer, PicnicHealth, discusses findings from the report and the industry's willingness to adopt technology.

Understanding the benefits and concerns associated with implementing datasets into clinical trial workflows.

COVID-19 not only advanced scientific boundaries, but also transformed research methodologies and accelerated adaptive clinical trial design.

In this video interview, Cameron Breze, product manager, Inovalon, discusses the need for accurate information in creating useful clinical data.

Genomics has long been a primary focus in precision medicine, but other areas of research are increasingly being used to help attain a more complete picture of how an individual’s complex biology impacts their health profile.

Teams must work together with technology solutions and optimize integration to unlock their full potential.

Current industry trends align with the need for improved, fit for purpose technology.

A tool-based approach can significantly aid in the harmonization of regulatory requirements, mitigate inadvertent risks, and encourage collaboration by making data sharing more efficient and secure.

How targeted AI can improve the performance of clinical trials.

In an interview with Applied Clinical Trials Associate Editor Don Tracy, Shakthi Kumar, chief strategy & business officer, Edetek, provides examples of how Agentic AI can accelerate clinical development.

In this video interview, Dominique Demolle, CEO of Cognivia, talks artificial intelligence/machine learning and its potential in gathering patient data.

Machine learning can help investors dive deeper into trial data to evaluate the true potential of an asset and uncover new hidden opportunities.

In an interview with ACT senior editor Andy Studna at SCOPE Summit, Rajneesh Patil, vice president, digital innovation, IQVIA, highlights the impact of artificial intelligence/machine learning in improving outcomes and maintaining safety with its implementation.

In an interview with ACT senior editor Andy Studna at SCOPE Summit, Patil, vice president, digital innovation, IQVIA, discusses how artificial intelligence/machine learning can help in areas such as feasibility, site selection, and patient recruitment.