EFMC Medicinal Chemistry 2026
Date & Time - September 6th-10th, 2026
Location - Basel, Switzerland
Schrödinger is excited to be participating in the EFMC Medicinal Chemistry 2026 conference taking place on September 6th – 10th in Basel, Switzerland. Join us for a workshop by Schrödinger scientists David Rinaldo and Jonas Kaindl, titled “Accelerating Drug Discovery with Integrated AI/ML Modeling.” Stop by booth #22 to speak with Schrödinger scientists. Steven Jerome, Executive Director of Hit Discovery at Schrödinger will be a panelist on “Agentic AI Reimagining the Drug Discovery Pipeline” on September 9th at 15:30.
SEPT 7 | 12:25 Accelerating Drug Discovery with Integrated AI/ML Modeling
Speaker:
David Rinaldo, Senior Principal Scientist, Applications Science, Schrödinger
Jonas Kaindl, Principal Scientist, Applications Science, Schrödinger
Abstract:
AI/ML models are now indispensable in modern drug discovery, offering powerful
capabilities ranging from protein structures predictions to ligand property prediction and
including 3D protein-ligand binding pose prediction or de novo molecular design.
However, effectively deploying and managing these models requires a centralized,
collaborative platform.
LiveDesign-ML is the module within the LiveDesign platform that empowers scientists to
generate, validate, and deploy state-of-the-art AI/ML models with minimal manual
intervention. We will demonstrate its capability for molecular property predictions, which
are crucial for triaging newly designed ideas and enabling the screening of hundreds of
thousands of compound ideas in minutes. By treating datasets as dynamic information
feeds, LiveDesign ML ensures models are always optimized and reliable for your
evolving chemistry.
We will also introduce RetroSynth, Schrödinger’s AI-driven synthesis planning platform.
Engineered to accelerate and scale conventional retrosynthesis, RetroSynth uses
advanced deep learning and a cloud-native Monte Carlo tree search (MCTS)
architecture to predict and score optimal, accurate, and cost-efficient synthetic
pathways. Learn how the integration of real-time building block data with AI and
physics-based modeling in RetroSynth unlocks accurate retrosynthetic analysis, leading
to massive project acceleration and significant cost savings in hit identification and lead optimization.
Medicinal chemists, computational chemists, and R&D leaders are welcome to join this
workshop. We will showcase how Schrödinger’s LiveDesign-ML and RetroSynth are
integrated to tackle critical challenges in the design and synthesis workflow. It will also
be the opportunity to see the full potential of integrated AI/ML and physics-based
modeling to overcome bottlenecks and advance your drug discovery programs.
SEPT 9 | 15:30 Panel: Agentic AI Reimagining the Drug Discovery Pipeline
Panelist:
Steven Jerome, Executive Director, Hit Discovery, Schrödinger
Our Speakers
David Rinaldo
Senior Principal Scientist, Applications Science, Schrödinger
David is a Sr Principal Scientist at Schrödinger, in the Applications Science team. Before joining Schrodinger in 2007, David was initially trained as an organic chemist but since he was more interested in theory, he switched to computational chemistry for his Ph.D. During his Ph.D. in Martin Field’s group in Grenoble, David has been working on the coordination of metals by proteins and peptides using QM and MD approaches. He has also ported the local MD code to a special purpose electronic card developed by FujiXerox. He then did a post-doc at Columbia University in Rich Friesner’s lab where he worked on understanding the reactivity of metalloenzymes using QM/MM and on developing a DFT functional for metal. At Schrodinger, he has been supporting customers from the European French-speaking area (France, Belgium, Switzerland).
Jonas Kaindl
Principal Scientist, Applications Science, Schrödinger
Dr. Jonas Kaindl is a Principal Scientist in Schrödinger’s Applications Scientist team in Europe where he’s helping customers to use Schrödinger’s solutions to their full potential. He is a trained pharmacist and obtained his Ph.D. from the University of Erlangen-Nuremberg for his research studying GPCRs, where he was introduced to computational modeling. In 2021, he joined Schrödinger.
Steven Jerome
Executive Director, Hit Discovery, Schrödinger
Dr. Steven Jerome completed his PhD at Columbia University in the Chemistry Department under the supervision of Richard Friesner. While at Columbia, he contributed to tools for molecular docking and protein structure refinement. After Columbia, he joined Schrödinger as a scientific developer working on the Glide team, before transitioning to product management. He has since advanced through several roles at Schrödinger to his current dual role as Executive Director of Hit Discovery, directing the development of a broad portfolio of state-of-the-art computational tools for small molecule hit identification and head of EU+ Application Science, supporting greater adoption of the Schrödinger platform within Europe.