NLP in Biology and Chemistry

Name: Prof. Dr. Philippe Schwaller

University: EPFL, Switzerland

Talk:

Learning the Language of Chemistry

Abstract:

AI-accelerated organic synthesis is an emerging field that uses machine learning algorithms to improve the efficiency and productivity of chemical synthesis. Modern machine learning models, such as (large) language models, can capture the knowledge hidden in large chemical databases to rapidly design and discover new compounds, predict the outcome of reactions, and help optimise chemical reactions. One of the key advantages of AI-accelerated organic synthesis is its ability to make vast chemical data accessible and predict promising candidate synthesis paths, potentially leading to breakthrough discoveries. Overall, AI is poised to revolutionise the field of organic synthesis, enabling faster and more efficient drug development, catalysis, and other applications.

Name: Dr. Marco Stenta

Company: Syngenta

Talk:

From Words to Molecules, and Back Again: The Role of NLP in the Design of Active Ingredients

Abstract:

In this presentation, we will explore the transformative role of Natural Language Processing (NLP) in the industrial landscape, with a special focus on the design and synthesis of active ingredients. We will how both scientific discovery approaches operational workflows are impacted by this innovative technology. The talk will also offer insights into how Large Language Models (LLMs) are enhancing coding and data science, thus reshaping workflows and methodologies - a testament to the powerful, practical impact of NLP on our ways of working.