Virgine Dominguez, Exec VP Digital, Data & Info Systems at SERVIER at the Adopt AI Summit – How AI is reshaping pharmaceutical companies

The pharmaceutical industry faces significant challenges in R&D, such as low success rates (below 5%) and long development timelines (10-15 years). AI is seen as a potential game-changer, particularly in speeding up the R&D process and improving success rates.

Servier leverages AI primarily in R&D, focusing on disease understanding and target discovery. They have developed a knowledge graph that helps identify novel targets for diseases by linking proteins, genes, and diseases, significantly enhancing their ability to understand and combat rare diseases.

“Innovation is a race, so we need to go faster. We have a lot of opportunities with AI in terms of manufacturing, supply, distribution, promotion, and marketing. But where we want to develop a game changer is within R&D. and we really want to help scientists win the race.”

Virgine Dominguez, Executive Vice President Digital, Data & Information Systems at Servier

AI helps Servier narrow down the vast chemical space to find potential drug molecules. They use machine learning algorithms to predict molecular properties, focusing research efforts on the most promising candidates, thus accelerating the drug discovery process.

Determining the right dosage is crucial to balance efficacy and side effects. Servier uses AI to predict the optimal human active dose, enhancing the accuracy and speed of transitioning from lab research to human trials.

AI accelerates data collection and analysis during clinical trials. For example, Servier uses an image platform to analyze brain MRIs with precision, speeding up the assessment of drug efficacy. They also employ AI for medical writing, improving productivity and consistency across various languages and regulatory requirements.

AI adds value at every step of the R&D process by increasing the probability of success and reducing time to market. Servier uses diverse AI technologies to meet the specific needs of their R&D teams.

Servier emphasizes the importance of integrating AI talent with traditional R&D scientists. They have addressed cultural differences and now operate collaboratively, aiming to scale AI applications systematically across the company.

Servier has identified 40 high-value use cases for AI in R&D and prioritized 18 for the next few years. They are also exploring AI applications in other business functions, identifying 96 use cases and prioritizing 20 for implementation. They plan to significantly increase resources dedicated to these initiatives.

Governed by a foundation, Servier is committed to finding new treatments for hard-to-treat diseases. They strive to equip their employees with the best tools and technologies to achieve this mission, likening their journey to climbing the challenging North Face of Everest.

Servier’s strategic focus on AI in R&D and other business areas demonstrates their commitment to accelerating innovation and improving patient outcomes. Their comprehensive approach aims to harness AI’s potential to overcome industry challenges and achieve their ambitious goals.

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