Leaders’ POV: Accelerating drug innovation through AI at SERVIER – AI for Health Summit

Servier, a global pharmaceutical company, aims to place patients at the heart of its innovation efforts. Historically recognized for leadership in cardiovascular and metabolic diseases, Servier is now a leader in oncology, focusing on developing transformative treatments for hard-to-treat and rare cancers. Building on its oncology model, the company plans to establish a neurology franchise, setting ambitious goals to double the probability of success and reduce time-to-market by up to four years in the next decade.

Drug discovery is a lengthy and difficult process, with a success rate below 5%. Servier sees AI as a key enabler to accelerate innovation and improve efficiency. Essential elements for success include robust computational capabilities, high-quality data, and attracting top talent. However, data scarcity, especially for rare diseases, remains a challenge. Partnerships are also critical, as innovation cannot be achieved in isolation.

Servier has approached AI adoption in two phases. Initially, an opportunistic approach focused on proving AI’s potential through specific use cases, especially in collaboration with R&D teams. This phase helped bridge the cultural gap between scientists and data specialists. Now in a systemic phase, Servier integrates AI across all R&D processes, identifying 16 critical pain points and prioritizing 20 initiatives to maximize impact and feasibility.

Early research phases have seen significant advancements, particularly in target discovery and validation. AI has helped identify higher-quality drug targets and streamlined drug design processes, including small molecules and nucleotide-based therapies. Clinical development has benefited from faster patient recruitment and trial center identification. In later stages, AI supports medical writing, significantly reducing time spent on documentation.

Servier developed in-house tools leveraging generative AI for target assessment. These tools process vast scientific data to evaluate target safety, reducing scientists’ workload by 9%. Such solutions exemplify how AI augments, rather than replaces, scientific expertise, enabling faster and more informed decisions in drug development.

Collaboration is central to Servier’s strategy, both internally and externally. Pre-competitive networks like the Feder association aim to address shared challenges in AI and drug development. Servier also selectively partners with cutting-edge firms for digital twins and French company Owkin for imaging and machine learning. Public-private collaborations further accelerate progress, leveraging significant recent investments in French research and innovation.

Servier’s integration of AI into drug discovery and development demonstrates its commitment to innovation and patient-centered care. While challenges remain, particularly around data and resource allocation, the company’s strategic focus on AI, partnerships, and systemic integration positions it to lead in transforming healthcare outcomes.