The Rush for Quality Data and the Means to Protect It

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Webinar Date/Time: Fri, Feb 23, 2024 11:00 AM EST

The biopharma industry is experiencing a “gold rush” of data generated by advanced analytical technologies. Tune into this discussion on how the management of these data and their analyses are driving the drug discovery and development process forward.

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Event Overview:

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.
Interviews featuring:

  • Nathalie Batoux, Product Manager, Research Innovation, IDBS
  • Thierry Dorval, Head of Data Science & Data Management, Servier
  • Jeremy Grignard, Data & Research Scientist, Servier

This episode of Drug Digest is sponsored by:

  • LabVantage Solutions

Key Learning Objectives:

  • A look at why data is the biopharma industry’s most valuable asset
  • Pros and cons: where are data integrity practices strongest? Where they are weakest?
  • Good data vs. bad data—how can you tell?
  • Introduce “graph technologies” and discuss their use
  • The role advanced technologies (such as AI) play in ensuring data integrity
  • Thoughts on how the biopharma industry is handling the rush of data

Who Should Attend:

  • Laboratory personnel
  • Data scientists
  • Process engineers/process development
  • CROs


Nathalie Batoux
Product Manager, Research Innovation

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

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

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.

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