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Is AI truly transforming drug development, or are we still navigating through the hype?

Venu Mallarapu, Vice President of Global Strategy & Operations, eClinical Solutions

Companies across sectors are rethinking operations to adapt to an AI-driven landscape. However, biopharma’s AI adoption has been slow, with many still in exploratory stages. Skepticism persists following initial industry hype, and technology alone isn’t a fix – change management and transformed processes are essential for ROI. Organizations also face concerns like regulatory compliance and data privacy.

Despite these challenges, there is sustained interest in AI’s potential to automate and reduce cycle times within R&D. Generative AI presents quick wins for the industry. Tools like chatbot assistants have shown significant success in these areas, accelerating drug discovery, optimizing clinical trials, and enhancing data analysis.

However, many companies face barriers after the proof-of-concept (PoC) stage, due to lack of data, investment, and hard-to-prove outcomes. Mistrust of technology vendors, regulatory issues, and the need for robust infrastructure also remain hurdles.

Modern data infrastructure and analytics enable faster insights and better decision-making, and embedding AI streamlines these processes further. The FDA’s January 2025 draft guidance on AI use is a key milestone for responsible AI adoption. While balancing innovation with caution is crucial, there is a unique opportunity to embed AI across the life cycle, reducing cycle times and delivering therapies to patients faster.. 


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