Sanofi

Canvas Category OEM : Pharmaceutical

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Primary Location Paris, France

Financial Status NASDAQ: SNY

We are an innovative global healthcare company, driven by one purpose: we chase the miracles of science to improve people’s lives. Our teams across the world strive to transform the practice of medicine, turning the impossible into the possible for patients. We provide potentially life-changing treatments and the protection of life-saving vaccines to millions of people, and affordable access to our medicines in some of the world’s poorest countries.

Assembly Line

Sanofi uses the industrial metaverse to revolutionize training and operational efficiency

📅 Date:

🔖 Topics: Metaverse, Worker Training

🏢 Organizations: Sanofi, Microsoft


Sanofi is a leader in the development and manufacturing of both prescription and over-the-counter medications. To meet an increased demand for Sanofi pharmaceuticals, the Paris-based organization needed to find a way to make its production lines more streamlined while training and onboarding more operators. Sanofi launched a pilot project in it packaging workshop in Lisieux, France to work in the metaverse using Microsoft HoloLens 2 with Microsoft Dynamics 365 Guides and Microsoft Dynamics 365 Remote Assist. The aim was to streamline employee training procedures, enhance operator efficiency, and integrate a digital approach within the manufacturing environment. Using HoloLens 2, Sanofi has reduced training time for new operators from eight weeks to six weeks. The organization is also using HoloLens 2 for remote maintenance and troubleshooting, enabling quicker resolution of equipment issues. With the success of the pilot, Sanofi is looking to expand the solution across its value chain, with a specific emphasis on data analysis.

Read more at Microsoft Stories

Dassault Systèmes Partners with Sanofi to Optimize Tech Transfer and Industrialization at Its Future EVolutive Facilities

📅 Date:

🏢 Organizations: Dassault Systemes, Sanofi


Dassault Systèmes and Sanofi today announced their partnership to optimize “EVolutive Facility” production at Sanofi’s future state-of-the-art modular manufacturing facilities in France and Singapore. The partnership, which expands their long-standing collaboration in life sciences and healthcare, will leverage virtual twin experiences to enable agile and flexible operations that advance Sanofi’s ambition to secure its product portfolio.

Sanofi will use Dassault Systèmes’ “Made to Cure for BioPharma” industry solution experience based on the 3DEXPERIENCE platform to design, implement, qualify and operate modular production lines at the two “EVolutive Facilities.” These will rely on single-use technology and mobile equipment to manufacture up to four products simultaneously and sustainably by selecting the most advanced technologies to reduce their energy consumption. The platform provides a virtual environment for collaborative innovation and end-to-end data management across the life cycle. Sanofi can experience the manufacturing systems under development and their operation virtually and optimize scale up and industrialization processes before deploying them.

Read more at GlobeNewswire

Digital Twins and AI Reshape Biopharmaceutical Manufacturing

📅 Date:

✍️ Author: Gareth John Macdonald

🔖 Topics: Digital Twin

🏭 Vertical: Pharmaceutical

🏢 Organizations: Sanofi


The foundation of any control strategy is process understanding. And, according to the ICH’s Q8 guidance,1 modeling is the best way to generate process understanding and meet regulators’ quality-by-design expectations. The models should describe the relationship between process parameters and drug quality and performance attributes.

Statistical models—predictions based on available data—have proven to be the most popular approach so far. Many manufacturers have used data-based models to guide development, scale-up, and process control. But their predictive power is limited to the range of data available, and they require significant experimental effort.

For this reason, mechanistic models—assumptions based on known principles rather than just data—are gaining in popularity. Mechanistic models “can provide a full description of the system, higher prediction power, as well as the potential to extrapolate well outside of calibration space,” Li explains. “They are valuable tools for predicting scale-up process performance, thereby de-risking large-scale manufacturing runs.”

Read more at GenEng News