Virgine Dominguez, Exec VP Digital, Data & Info Systems at Servier on AI for Health | AdoptAI Summit

Summary

At the Adop Summit, Ser's representative shared the company's bold strategic move into oncology and rare diseases, focusing on AI adoption to drive innovation in pharmaceutical R&D. Ser uses AI in key stages of drug development, including target discovery, drug discovery, and dosage prediction, to accelerate the process and improve success rates. With a long-term commitment to therapeutic progress, Ser aims to reduce the time to market and enhance clinical trial efficiency. The company plans to scale its AI efforts, emphasizing collaboration between R&D scientists and data experts to deliver life-saving treatments faster.

Takeaways

• 😀 Ser is a global pharmaceutical company with 5.3 billion Euro in revenue and 22,000 employees, focused on treating rare diseases and oncology.
• 😀 Ser invests 20% of its revenue annually in R&D, with a long-term, foundation-governed vision dedicated to therapeutic progress for patients.
• 😀 AI is seen as a game-changer in the pharmaceutical industry, particularly in optimizing R&D, manufacturing, distribution, and marketing.
• 😀 The probability of success in R&D is extremely low, with a success rate below 5%, and even lower for rare diseases and oncology, which is about 2-3%.
• 😀 AI can help reduce the long time to market in drug development, which currently spans 10 to 15 years, by accelerating research and improving success rates.
• 😀 Ser has developed a knowledge graph to identify potential drug targets, linking proteins, genes, and diseases to aid in the discovery of new treatments.
• 😀 Machine learning algorithms are being used at Ser to predict molecular properties, helping scientists focus on promising drug candidates and streamline drug discovery.
• 😀 AI is used to predict the right human active dose, optimizing the balance between efficacy and side effects in drug development.
• 😀 In clinical trials, AI accelerates data collection and analysis, enhancing precision in evaluating drug effectiveness, such as through the analysis of brain MRI scans.
• 😀 Ser envisions scaling AI use in R&D and other functions by identifying and prioritizing high-value use cases, focusing on 18 R&D use cases and 20 cases across other functions in the next 2-3 years.

Q & A

What is the main focus of Serier as a company?

Serier is a global pharmaceutical company with a focus on chronic diseases such as cardiovascular and diabetes. Six years ago, they made a strategic shift to focus on oncology, particularly rare diseases, aiming to find innovative treatments for patients suffering from hard-to-treat diseases.

What are Serier’s key strategic objectives for the next decade?

Serier's key objectives are to improve operational efficiency in their core business, which involves optimizing costs to fuel growth and research, and to accelerate innovation, particularly in oncology and rare diseases, with a long-term goal of expanding into neurodegenerative diseases.

What are the main challenges Serier faces in R&D?

The primary challenges in R&D are the low probability of success in drug development (less than 5% success rate, and even lower for rare diseases and oncology) and the lengthy time to market, which can take 10 to 15 years.

How does AI fit into Serier’s R&D strategy?

AI plays a crucial role in Serier’s R&D strategy by helping to increase the probability of success and reduce the time to market. It aids in drug discovery, target identification, molecule screening, dosage prediction, and clinical trials, providing valuable insights and accelerating decision-making.

Can you explain the role of AI in the Target Discovery phase?

In the Target Discovery phase, AI is used to build knowledge graphs that map links between proteins, genes, and diseases. This helps Serier identify novel targets for rare diseases, providing a deeper understanding of disease mechanisms and guiding therapeutic interventions.

How does AI assist in identifying the right drug candidates?

Serier employs machine learning algorithms to predict the properties of molecules. These algorithms help narrow the field by identifying molecules with the best potential in terms of activity, selectivity, and safety profiles, which accelerates the drug discovery process.

How does AI contribute to determining the right dosage for drugs?

AI helps predict the appropriate human active dose for a drug by analyzing molecular properties and balancing efficacy with side effects. This prediction aids researchers in determining the optimal dosage to ensure the drug's effectiveness while minimizing adverse effects.

How can AI reduce the length of clinical trials?

AI accelerates clinical trials by improving data collection and analysis, such as using image platforms to analyze brain MRIs with precision. This helps accumulate more data more quickly, allowing for faster adjustments to treatment protocols and more effective trial outcomes.

What are some of the practical uses of AI in clinical trials at Serier?

At Serier, AI is used in clinical trials to automate medical writing, reducing the workload involved in creating thousands of pages of regulatory documents. AI models can help write protocols and explain trial objectives in multiple languages, improving efficiency and productivity.

How does Serier measure progress in AI adoption within R&D?

Serier measures its progress by tracking key use cases across R&D, selecting high-value areas where AI can bring significant improvements. They’ve identified 40 use cases in R&D, prioritized 18 for the next 2-3 years, and are systematically scaling AI initiatives across the company, including manufacturing, finance, and promotion.