Thursday, 21 October 2021
Symposium on Artificial Intelligence & Digitalization in Chemical Research

The development and integration of data-driven approaches to improve and facilitate decision making are key priorities in chemical and pharmaceutical research. 

In this symposium, we focus on the exploitation of synthesis data, as well as on the advances in the analysis and design of new materials and active ingredients. Both areas of research observed significant breakthroughs in the most recent years.

Achieving a wide adoption of novel data driven approaches is the ultimate goal in companies but not an easy transition. Successful examples of how to overcome this challenge will be presented and discussed.

Use the Vaucher Code for a free ticket: scs-ilmac21


Organizing Committee

Hans Peter Luethi, Swiss Chemical Society
Torsten Luksch, Syngenta Crop Protection 
Arndt Finkelmann, Syngenta Crop Protection

Program, 21 October 2021



Session 1




Synthesis Automation & Prediction
Chair: Arndt Finkelmann, Syngenta Crop Protection

Alessandra Toniato, IBM Research
«IBMRoboRXN: the autonomous chemical lab bringing together AI, Cloud and Automation»

Marco Stenta, Syngenta Crop Protection
«LinChemIn: The Network of Synthetic (Bio-)Chemistry»

Rolf Gueller, Chemspeed Technologies AG
«What is more important to enable efficient cyber-physical systems – Digital Twins or the degree of automation in RnD labs?»


Coffee Break

Session 2



Digital Change: New Ways of Working
Chair: Hans Peter Luethi, SCS

Nik Stiefl & Finton Sirockin, Novartis
«Citizen data science": from buzzword to MedChem reality»

Eric Alan Baur & Laurens Versluis, F. Hoffmann-La Roche
«Digital Transformation in Molecule Planning - Shift to Radical Collaborations»



Session 3


Active Ingredient & Materials Discovery
Chair: Torsten Luksch, Syngenta Crop Protection

Daniel Kuhn, Merck Healthcare KgaA
«What got you here won't get you there: How ML/AI change the way we work in early drug discovery»


Hergen Schultze, BASF
«BASLEARN – The Berlin Based Joint Lab for Machine Learning»


Coffee Break


Elisa Liberatore & Julien Hazemann, Idorsia
«Applications of Machine Learning Drug Design (MLDD)»



The symposium is supported by:

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