How AI is Transforming Clinical Trials: A Conversation with expert.ai – expert.ai

Clinical trials are the foundation of drug development, but they come with significant challenges that risk slow down drug discovery and development. At the heart of these challenges is data—massive volumes of clinical, scientific and regulatory information that companies must process, interpret and apply effectively.

At the upcoming Bio-IT World Conference & Expo, expert.ai is proud to be a sponsor, exhibitor and speaker, bringing our expertise in AI-driven innovation to the life sciences community. Christophe Aubry, Global Head of Life Sciences and Healthcare, will be presenting in the Generative AI track, where we’ll explore how AI is transforming clinical research, from trial design and patient recruitment to competitive intelligence and regulatory compliance. As a preview, we spoke with Christophe about the transformative power of AI in clinical research and how companies can leverage it to accelerate drug development and improve trial outcomes.

Q: Why are clinical trials so complex, and how can AI help?

Christophe: Clinical trials generate and rely on vast amounts of data, from many sources: clinical registries, real-world patient records and scientific literature. The traditional methods of analyzing this information are just not enough to keep up with the amount of data that exists and the vital need to make it actionable for different aspects of trial processes as quickly as possible. By automating data indexing, extracting meaningful insights and enabling real-time access to critical trial intelligence, AI accelerates a company’s ability to drive trial innovation. Because we’re able to take both structured and unstructured data into account, research teams can make data-driven decisions with greater accuracy and efficiency.

Q: Trial benchmarking is time consuming. How does AI make this process more efficient?

Christophe: Benchmarking requires analyzing thousands of existing trials to identify best practices and competitive insights. Again, doing this manually is impractical due to the sheer volume of available data. With AI, you’re able to analyze trial similarity, comparing protocols, endpoints and study designs across global databases, and in a repeatable way through automation. Because you’re able to surface the most relevant insights, research teams can optimize trial protocols, apply historical data to justify decisions and avoid costly design flaws—helping them move from concept to execution faster.

Q: Patient recruitment is a major hurdle in clinical trials. How does AI optimize this process?

Christophe: Many trials fail to meet recruitment targets because eligibility criteria are either too restrictive or misaligned with real-world patient populations. AI helps companies bridge this gap by analyzing real-world data from sources like scientific literature, health authority reports and electronic health records. This allows research teams to refine their inclusion/exclusion criteria, improve patient matching and enhance recruitment strategies based on comprehensive, data-driven insights. The result is faster enrollment, improved trial diversity and reduced delays.

Q: With so many clinical trials happening globally, how does AI help biotech companies stay ahead of competitors?

Christophe: The pharmaceutical landscape is highly competitive, with thousands of ongoing trials happening across the world at this very moment. To know what one of your competitors is doing, a company would have to continuously monitor many data-intensive sources, like clinical trial registries, scientific literature and regulatory filings. This is an area where AI can really help by providing real-time intelligence on emerging trends, trial designs and drug development strategies. By taking advantage of such AI-powered competitive intelligence, biotech companies can adjust their trial approaches, identify market gaps and maintain a strategic advantage proactively and using real-time information.

Q: What makes expert.ai a leader in AI-driven clinical trial innovation?

Christophe: At expert.ai, we specialize in transforming unstructured biomedical data into actionable insights. Our AI-powered platform integrates natural language processing (NLP), machine learning and generative AI to structure, classify and analyze scientific information at scale. Our technology mines data from more than 900,000 clinical trials worldwide. This includes multiple clinical trial registries, from clinicaltrials.gov, EUDRA and EUPAS, to Japanese registries, Australian registries, and many others. It provides the most up-to-date and comprehensive data landscape by disease, drug, mechanisms of action, organization or geography. Not only can researchers find related trials, but they can also access related publications, news, study results and principal investigators all in one place. We help accelerate drug development while reducing costs and risks by enabling biotech companies to efficiently navigate clinical data, optimize recruitment and refine their regulatory strategies.

The Future of AI in Clinical Trials

The pharmaceutical and biotechnology industries are entering a new era—one where AI is no longer an option but a necessity for improving clinical trial efficiency, accelerating drug development, and staying competitive. Generative AI, in particular, is poised to unlock new dimensions of research and innovation, but its successful implementation requires the right expertise and technology.

At expert.ai, we help biotech companies harness the power of AI to make smarter, data-driven decisions at every stage of clinical trials. Whether it’s optimizing study design, enhancing patient recruitment, or staying ahead of competitors, our hybrid AI approach ensures accuracy, reliability, and compliance in the fast-evolving life sciences landscape.

Join us at Bio-IT World, April 2-4 in Boston, to learn more about AI-powered clinical trials! Visit our booth, attend our speaker session in the Generative AI track, or contact us today to see AI in action.