AWS re:Invent 2025 - Can Your AI Show Its Work? Healthcare's Critical Imperative for Explainable AI

Leveraging AI to Accelerate Drug Discovery and Commercialization in Pharma

Sanofi's AI-Powered Approach to Shortening the Drug Development Lifecycle

• Sanofi, a leading biopharmaceutical company, is leveraging AI at scale to shorten the timeline between drug discovery and commercialization, which typically takes around 15 years.
• The company's goal is to use AI and other technologies to optimize their R&D, manufacturing, supply chain, and commercial processes to drive faster time-to-market for new therapies.

Applying a Balanced Approach to AI Adoption

• Sanofi takes a pragmatic approach to AI, using a mix of classical ML, time series analysis, and generative AI (GenAI) technologies.
• The selection of AI techniques is driven by the specific use case and desired business outcomes, rather than chasing the latest AI hype.
• For example, classical ML is well-suited for yield optimization in manufacturing, while GenAI shows promise for accelerating regulatory submissions and document processing.

Ensuring Explainability and Responsible AI Practices

• Explainability is a critical requirement for Sanofi, especially in the highly regulated pharmaceutical industry where transparency and trust are paramount.
• The company has developed a "RAISE" framework for Responsible AI, which encompasses key pillars such as Readiness, Accountability, Integrity, Sustainability, and Explainability.
• To operationalize this framework, Sanofi has built an "AI Foundry" ecosystem that leverages AWS, Snowflake, and DataIQ to ensure data quality, model explainability, and ongoing monitoring and governance.

Driving Value Across the Pharmaceutical Value Chain

• Sanofi is applying AI across the entire pharmaceutical value chain, from R&D and manufacturing to commercial operations and employee experience.
• In R&D, AI is used to accelerate the discovery and development of new drug molecules, with 70% of Sanofi's small molecule pipeline currently leveraging AI.
• In manufacturing and supply chain, AI is used for yield optimization, connecting scientists to the shop floor, and enabling faster decision-making by sales teams.

Establishing Robust Governance and Accountability

• Sanofi has implemented a centralized AI governance model, with a cross-functional XCOM board that reviews and approves all AI and GenAI initiatives.
• This governance process ensures alignment with the company's overarching objectives, feasibility assessments, and short-term value demonstration before deployment.
• The company also has a separate data and AI governance team that focuses on data quality, security, and the responsible development and deployment of AI models.

Key Takeaways

1. Sanofi is leveraging a balanced portfolio of AI technologies, including classical ML and GenAI, to drive tangible business outcomes across the pharmaceutical value chain.
2. Explainability and responsible AI practices are critical in the highly regulated pharmaceutical industry, where transparency and trust are essential.
3. Robust governance and accountability mechanisms, with cross-functional oversight and clear business objectives, are crucial for successful AI adoption and scaling.
4. Integrating AI into existing processes and systems, rather than pursuing AI for its own sake, is key to realizing the full potential of these technologies in the pharmaceutical industry.