Artificial Intelligence in daily practice for chemists
Who is it for?
PhD’s, postdocs, information professionals and researchers in academia and industry who are interested in developments around artificial intelligence in chemical information that are immediately usable. The focus will be on practical knowledge and a better understanding of the underlying principles.
Purpose of the conference
Chemistry and pharmacology are extremely information intensive research areas. The first large scholarly indexes on chemistry already started in the 19th century (pharmacopeias, Beilstein and Gmelin). As time went by the amount and complexity of information increased even further: over 40.000 journals publish on chemistry, from which information on chemical structures, physical properties, reactions, biological activity, toxicology and spectra are extracted to progress the field of chemistry. This mountain of information has advantages: it is now possible to use artificial intelligence to predict properties of materials and medicine and to predict how to synthesize these compounds. However, there are also disadvantages: spitting through this much information, some of it published in deliberately hard to understand patents, means it is easy to miss important findings and difficult to test the inventiveness, making it almost compulsory to use artificial intelligence. Besides we also have to deal with the trustworthiness of the currently available information.During the symposium we will focus on the practical knowledge for using AI in our information need in one afternoon. You may think of topics such as:- How does retrosynthesis work in theory and practice (Reaxys / SciFinder)?- How is information from literature and patents indexed? Artificial intelligence for recognizing compounds, synthesis and context used in chemical indexes (CAS)- Optimizing synthesis/formulations for better yields (most likely someone from industry)- Experiences with tools for better literature research (think of Scite and other tools that are commonly used in systematic reviews)- What open data sources are there and which ones can be used for testing your own artificial intelligence?The definitive program Is still under development. Keep an eye on https://www.knvi.nl/interessegroep/chemische-informatie for updates.
About us
The conference is organized by the Special Interest Group Chemical Information (SIG-CI) from the Netherlands society for information professionals KNVI. The group exists of information specialists from industry, academia and research institutions that work within the chemistry or related areas such as pharmacology, toxicology, microbiology and material sciences. The group was setup to improve the accessibility of chemical information.
Schedule of Symposium AI in de Chemie
On donderdag 27 juni:
12:45 - 13:00 Introduction
13:00 - 13:30 Using AI to predict the feasibility of de novo drugs - Anthe Janssen (Leiden University) By Janssen (Anthe)
13:30 - 14:00 Leveraging AI technologies at CAS - Valentina Eigner-Pitto (CAS)
14:00 - 14:30 Formulation optimization Phil Clark - (CTO Nouryon) By Clark (Phil)
14:30 - 15:00 Break
15:00 - 15:45 Artificial Intelligence in Drug Discovery - Capturing Chemistry in Language - Gerard van Westen (Leiden University) By van Westen (Gerard)
16:15 - 16:45 Finetuning Gen AI for Chemistry - Jakub Zavrel (Zeta Alpha) By Zavrel (Jakub)
16:45 - 17:15 Open datasources and applications - Egon Willighagen (Maastricht University)
17:15 - 18:15 Drinks
