Principal Scientist, Digital Drug Product Engineering

Job title: Principal scientist

• Location: Montpellier, France
• Grade: L3
• Hiring Manager: Sophie MARTIN

About the job:
Are you ready to shape the future of medicine? The race is on to speed up drug discovery and development to find answers for patients and their families. Your skills could be critical in helping our teams accelerate progress. Join our Pharmaceutical Engineering team, in the CMC Synthetics Platform, as a Principal Scientist and you will drive modeling implementation and technological solutions identification for the development of drug product processes for our new synthetic molecular entities.

You will be based at our primary drug product development site in Montpellier France. You will be at the forefront of Sanofi’s transformation from a traditional experiment heavy development approach to a digital approach that uses in-silico experimentation and high throughput data generation to accelerate knowledge generation and increase efficiency. You will work closely with the Drug Product Development and Crystallization and Particle Engineering groups on Process Selection, Process Design, Process Optimization, Tech Transfer and new technology implementation.

As a member of the Pharmaceutical Engineering group you will contribute to the leadership of Process Characterization (Control Strategy Definition) and Tech Transfer. Another key objective for the group will be to support the implementation of automation and robotics in Drug Product development. Overall, you will work in partnership with other functional groups in R&D and manufacturing to design robust and efficient pharmaceutical processes that meet quality, environmental and cost targets (e.g. Process capability, PMI, COGs).

As a Principal Scientist you will also be a key member of the Pharmaceutical Engineering team and you will support directly the Pharmaceutical Engineering Head for functional team coordination and collaboration with other departments.

• Help the section head establish operational frameworks to coordinate pharmaceutical engineering activities on projects (planning, priorities, challenges, resource allocation)
• Help the section head establish collaborative ways of working with other departments
• Elaborate and champion a roadmap for the use of digital development workflows and software tools (e.g., APPs), automation, and robotics to enable transition from traditional experimentally heavy protocols to Digital Twins for continuous improvement of Drug Product Process risk assessment throughout development
• Lead the transfer and handover of digital tools to Industrial Manufacturing to ensure robust process transfer, scale-up, and monitoring for PPQ and commercial launch
• Stay up to date with regulatory approaches and requirements in Drug Product sections regulatory filings and promote the description of mechanistic understanding, modeling, and digital twin in P2.3
• Stay up to date with new manufacturing and physical powder characterization technologies proposed on the market and identify interesting improvements to propose to Drug Product Development and Clinical Manufacturing
• Comply with all internal and applicable government Quality and HSE (Health, Safety and Environmental) requirements

• Demonstrated ability to identify and develop impactful modeling applications and technological engineering solutions for Drug Product development
• Ability to design experimental plans and propose representative use-tests to collect data required up to the translation of conceptual mathematical models to computer models
• Experience operating in a fast-paced environment leading modeling work package development and managing their integration in Drug Product development projects
• Developed an important expert network through conferences and collaborative multi‑big pharma consortiums or working groups

• Strong understanding of process engineering and solid‑state physical characterizations
• Demonstrated skills with computer programming using software such as Matlab and Python
• Basic understanding of statistical concepts and data engineering to effectively work with biostatisticians and IT partners…