Knowledge Center

Artificial intelligence continues to move from experimentation to execution across the life sciences industry. On a recent episode of the AI in Business podcast, Matthew Peruhakal, Global Head of Data Architecture, Utilization, and AI Engineering at Sanofi, offered a deep look at how the pharmaceutical giant is integrating AI to transform clinical trials. From intelligent data workflows to proactive risk detection and regulatory alignment, Peruhakal described an organization reshaping its research and development operations around a new digital core. 

His message was clear: AI cannot remain a side project. To make a meaningful impact, it must be embedded as a strategic capability that connects people, systems, and data across the enterprise.

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Artificial intelligence is shifting from promise to practice in biopharma, and few domains feel the impact more than clinical development. In a recent conversation on the AI in Business podcast, Zhong Lu, director of data science and AI at Novartis, outlined how AI is evolving the clinical trials process end to end. His perspective centered on building internal platforms that unite structured and unstructured data, deploying document intelligence to remove process friction, and using responsible generative AI to support scientific decision making without compromising compliance. While the regulatory bar remains high and patient trust is paramount, Novartis’s approach shows how targeted applications of AI can streamline data operations, strengthen regulatory readiness, and make both traditional and decentralized trials faster and more resilient.

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Artificial intelligence continues to influence nearly every industry, and life sciences are no exception. In a recent conversation on the AI and Business podcast, Damien Nero, Head of Data Science in US Medical at Takeda Pharmaceuticals, shared his perspective on how AI is changing the clinical trial landscape. With over 15 years of experience applying machine learning and real-world data to drug development, Nero outlined both the progress already being made and the challenges that still stand in the way of broader transformation. His insights highlight how pharmaceutical leaders can think strategically about deploying AI to balance innovation with operational efficiency.

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Learn how Medable powered a decade-long, global long-term follow-up (LTFU) obesity study, achieving an impressive 97% patient retention rate without using a traditional EDC system all while delivering a compliant, scalable, and cost-efficient solution.

It has become clear that our industry has reachedthe limits of human-only clinical development. As clinical trials have become increasingly complex, the endeavors that people alone can perform are no longer sufficient to generate the momentum needed to address the growing burden of human disease. This has led to longer drug development timelines and significant delays for patients. One large are of lost time is “white space,” definied simply as unproductive time caused by manual, sequential processes and fragmented data systems. Thankfully, a solution lies in agentic AI and its abilities to perform series of tasks.

The successful integration of AI agents in enterprise operations requires a balanced, deliberate approach. Drawing from recent research in Strategic Integration (SI) and agentic AI adoption within large enterprises, the following best practices help maximize value, manage change effectively, and mitigate common pitfalls. Medable Agent Studio specifically streamlines this process by providing robust tools, no-code simplicity, and built-in compliance and security standards.

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Deployment of remote and virtual clinical trial methods and technologies, referred to collectively as decentralized clinical trials (DCTs), represents a profound shift in clinical trial practice. To our knowledge, a comprehensive assessment of the financial net benefits of DCTs has not been conducted

Research looking at mobile apps and how they may provide a meaningful access point for all stakeholders for symptom management.

Explore how artificial intelligence (AI) is fundamentally transforming every facet of clinical trials, from initial protocol design and patient recruitment to data management and regulatory approval. This comprehensive guide provides an authoritative, in-depth look at AI's role in accelerating drug development and improving patient outcomes, with special focus on emerging agentic AI technologies.

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Discover how Agentic AI is revolutionizing clinical trials by optimizing efficiency, accelerating drug development, and improving patient access to therapies.

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