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This perspective examines how artificial intelligence (ai), large language models (llms), adaptive trial designs, and digital twins (dts) can modernize trial design and execution. In intelligent clinical trials, ai is merely a technological upgrade, but a blueprint for optimizing study design, accelerating patient recruitment, and flagging risks before they derail timelines. In this q&a, rohit nambisan, ceo of lokavant, and jonathan crowther, head of predictive analytics, pfizer, explore how ai is transforming study feasibility, regulatory review, and trial execution.
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The answer, at least in part, lies in applying artificial intelligence and analytics to design clinical studies. Leveraging ai agents to eliminate ‘white space’ in clinical trials for decades, clinical trials have played an integral role in developing and determining the safety and efficacy of new and. Ai is redefining how clinical trials are designed, executed, and analyzed
By leveraging vast amounts of data, ai technologies can uncover insights that would have been nearly impossible to detect through conventional methods.
Below is a quick snapshot of how ai is reshaping study design from traditional challenges to measurable impact In this article, we break down the role of ai and ml in clinical trials with special attention to use cases Ai helps overcome the challenges of clinical trial design, streamlining complex tasks such as patient selection, trial monitoring, and data analysis.
