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 companies. 

In this symposium, we focus on the exploitation of synthesis data, and on the advances in the analysis and design of new materials and active ingredients. Both areas achieved 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 task to achieve. Successful examples from industry will be presented to overcome this challenge.

Organizing Committee

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

Program, 21 October 2021

09.00

Welcome

Session 1

09.05

09.40

10.15

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»

Chemspeed
«Tbd.»

10.45

Coffee Break

Session 2

11.05

11.45

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»

12.15

Lunch

Session 3

13.30

14.05

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

Paul Czodrowski, TU Dortmund
«Tbd.»

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»

14.35

Coffee Break

15.00

15.35

Bruno Betoni Parodi, BASF
«BASLEARN – The Berlin Based Joint Lab for Machine Learning»

Elisa Liberatore & Julien Hazemann, Idorsia
«Machine Learning Drug Design (MLDD) and SARS-CoV-2 Mpro Inhibitor Discovery»

16.10 Apéro
Saved in your Bookmarks

We use cookies on our website. Some of them are essential, while others help us to improve this website. We are grateful if you accept them. More info