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While artificial intelligence (AI) in clinical trials isn’t new, we’re witnessing an unprecedented acceleration in both its sophistication and practical implementation. The convergence of advanced algorithms, increased computing power and vast data sets is transforming how we design, conduct and analyse clinical studies.

Traditional clinical trial challenges – patient recruitment, retention and data quality – are being transformed through AI-powered solutions. One approach is to use ‘digital twin’ technology – effectively creating an AI replica of a trial participant with companies like Unlearn, showing how it can reduce control group sizes by up to 33% in Alzheimer’s trials while maintaining statistical validity.

Real-world evidence analysis, powered by machine learning, is enabling more precise protocol design and patient stratification. AI algorithms can now analyse millions of health records to identify optimal trial sites and predict enrolment patterns, significantly reducing the 80% of trials that historically miss their recruitment timelines.

However, it’s crucial to maintain perspective. AI should be viewed as an enhancer of human expertise rather than a replacement. The technology excels at pattern recognition and data analysis but requires human oversight to ensure ethical considerations and patient safety remain paramount. The challenge lies not in the technology itself, but in its thoughtful integration into existing clinical processes.

Looking ahead, the most promising applications combine AI with human insight. For instance, AI-powered monitoring systems can flag potential adverse events earlier, allowing medical professionals to intervene more quickly. Natural language processing improves protocol design through analysis of historical trial data and enables the creation of highly personalised patient materials. Meanwhile, predictive analytics help identify which patients are most likely to respond to specific treatments.

The key to success lies in striking the right balance: leveraging AI’s capabilities while maintaining the human elements that are essential to clinical research. As we move forward, the focus should be on developing frameworks that ensure AI enhances rather than compromises the quality and integrity of clinical trials.

The question isn’t whether AI will transform clinical trials, but how we can best harness its potential while maintaining the highest standards of patient care and scientific rigour.

David Kane is Global Managing Partner at Arc Bio Communications