Half of clinical trial experts asked in a recent survey cited trust and regulatory uncertainty as the major barriers to artificial intelligence (AI) adoption.
The poll, conducted by The Pistoia Alliance at the Clinical Trials Technology Congress (CTTC) in London, showed that AI is beginning to deliver value in clinical development, with 42% of respondents seeing early signs of return on investment (ROI) and a further 23% expecting ROI but not yet realising it. Respondents said that over the next three to five years, AI will have the most impact on cleaning data, data analysis and insight generation (48%) and sourcing and engaging patients (22%).
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The poll also examined the value of real-world data, including social media listening, in shaping clinical development operations. It found that 60% of respondents are already using, piloting or exploring patient-generated data to inform clinical development decisions beyond marketing. More than half (58%) say the primary benefit of social media listening is understanding patient needs, monitoring sentiment and experience.
Dr Becky Upton, President of the Pistoia Alliance, said: “A recurring message at the Congress was that regulators are ready to embrace AI, and are keen for pharma companies to engage early to ensure adoption is safe and compliant. The panel rightly emphasised that speed without control is not enough when patient safety is at stake. For AI to support clinical development at scale, the industry needs validated, auditable and explainable approaches, not black-box models that create uncertainty for sponsors and regulators alike. Regulators are not the enemy. They can be partners to pharma, working together to formalise AI guidance that supports both sides. This is exactly where the Pistoia Alliance helps, by convening pre-competitive working groups that bring pharma, technology providers and regulators together around common frameworks.”
In January 2025, the FDA released a guidance titled ‘Considerations for the Use of AI to Support Regulatory Decision-Making for Drug and Biological Products’, which provides recommendations on the use of AI to produce information or data intended to support regulatory decision-making regarding safety, effectiveness, or quality for drugs.
Meanwhile, the EMA has released a reflection paper on the same topic, entitled ‘The Use of AI in the Medicinal Product Lifecycle’, which discusses how AI and machine learning (ML) systems used in clinical trials should meet Good Clinical Practice or GCP guidance from the International Council for Harmonisation (ICH).
According to the GlobalData report ‘The State of the Biopharmaceutical Industry – 2025’, AI has the potential to significantly reduce pharmaceutical R&D costs by streamlining drug discovery, optimising clinical trials, and minimising costly failures through data-driven predictions and effectiveness assessments.
While the report highlights AI is more adopted in the preclinical setting, 10% of industry experts in a GlobalData survey believe AI will become a key driver in developing new treatments in both preclinical and clinical trials this year.
GlobalData is the parent company of Clinical Trials Arena.
