Drug Digest: The Rush for Quality Data and the Means to Protect It

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This discussion explores how the management and analysis of vast data generated by advanced analytical technologies are revolutionizing the drug discovery and development process within the biopharma industry.


In this episode of Drug Digest, industry experts discuss why data is the biopharma industry’s most valuable asset today. The discussion also delves into the means by which the industry as a whole is learning to upgrade data integrity practices to better protect their data and the use of innovative technologies, such as advanced graph technologies, to better shape the drug discovery and development process.

Interview featuring

Nathalie Batoux, Product Manager, Research Innovation, IDBS

Nathalie Batoux left the lab and joined IDBS in 2005, driven by her passion to help scientists with workflows and informatics tools to expedite their research. At IDBS, Batoux is a product manager for Research and Innovation. In her role, she regularly interacts with customers and researchers to gain an understanding of their data management needs and drives the development of platform capabilities to provide a solution. Batoux is an organic chemist by training and started her career as a post-doctoral researcher in chemistry working in the domain of nucleoside and dinucleotide analogues.

Thierry Dorval, Head of Data Science & Data Management, Servier

Thierry Dorval received a PhD in image analysis and artificial intelligence (AI) from University Pierre & Marie Curie and then joined the institut Pasteur Korea in 2005 as a group leader specializing in high content screening applied to cellular differentiation and toxicity prediction. In 2012, he joined AstraZeneca, where he focused on developing and advising on quantitative image and data analysis solutions in support of high content phenotypic screening. In 2015 he joined Servier, France, to lead the Data Sciences & Data Management pole of activities where he is in charge of optimizing the early stages of the drug discovery process by taking advantage of cutting-edge computational approaches. This includes usage of AI, knowledge graph database, system modeling and sequences design applied to multiple modalities including small molecules, antibodies, and oligonucleotides.

Jeremy Grignard, Data & Research Scientist, Servier

Jeremy Grignard holds a PhD in computer science, data, and artificial intelligence (AI) from École Polytechnique. He also earned a master’s degree in applied mathematics in Data Science and an engineering degree in computer science and big data. In 2019, he joined the Servier Research & Development Institute to complete his thesis with Inria Saclay, during which he developed computational methods using knowledge graphs, data science, and mathematical modeling to improve early drug discovery. Since 2022, he has been designing and implementing AI projects related to gene inference, explainable machine learning, heteromodality algorithms, biologically constrained deep learning models, knowledge graphs, and large language models.


This episode of Drug Digest is sponsored by:

  • LabVantage Solutions

About Drug Digest

Drug Digest is a tech talk video series with the Pharmaceutical Technology® editors, who interview industry experts to discuss the emerging opportunities, obstacles, and advances in the pharmaceutical and biopharmaceutical industry for the research, development, formulation, analysis, upstream and downstream processing, manufacturing, supply chain, and packaging of drug products.

Upcoming episodes

  • March 2024: Hot Melt Extrusion
  • April 2024: Stability Testing
  • May 2024: Updates in Outsourcing