Amplifying medicinal chemist impact with large-scale ideation, FEP+, machine learning, and retrosynthesis through LiveDesign
Date & Time - April 1st, 2026
- 8:00 AM PDT | 11:00 AM EDT | 4:00 PM BST | 5:00 PM CEST
Location - Virtual
Medicinal chemistry is an increasingly complex orchestration of high-stakes tasks – interpreting project SAR, ideating compounds that satisfy both affinity and ADMET profiles, and managing the logistics of synthesis and assay reporting. When computational tools are siloed from the medicinal chemist’s primary workspace, the impact of advanced modeling is diluted, and the path to a development candidate (DC) becomes uncertain.
Join us to see how Schrödinger’s Enterprise Informatics Platform, LiveDesign, serves as the single terminal to bridge this gap. By integrating the complete computational pipeline, LiveDesign enables medicinal chemists to adopt a fully “predict-first” paradigm. This approach amplifies the impact of the entire project team, from modelers to leadership, by centralizing decision making and collaboration. By equipping your team with predictive insights throughout the discovery process, you can make MPO optimization more efficient, reduce the total number of synthesized compounds, and significantly shorten DMTA cycles and the journey to a DC.
Key Highlights:
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Strategic DMTA Acceleration: How to utilize AutoDesigner and Active Learning FEP+ to vet thousands of ideas before committing to synthesis
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Seamless MPO Workflows: Balancing potency and ADMET profiles simultaneously within the LiveDesign interface to avoid late-stage failures
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Synthetic Reality Checks: Utilizing RetroSynth to bridge the gap between high-scoring digital designs and practical bench-top feasibility
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LiveDesign in Action: A live walkthrough of a “lead-to-DC” scenario, demonstrating how the LiveDesign Assistant and integrated modeling tools allow a chemist to move from a raw SAR table to a prioritized, tractable synthesis list in a single session
Who Should Attend:
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Medicinal Chemists looking to leverage the industry’s most accurate potency predictions and ML models within their daily design workflow
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Project Team Leads seeking to maximize budget efficiency and eliminate the technical silos that delay candidate selection
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Computational Chemists aiming to scale their impact by deploying validated, gold-standard models for organization-wide use
Our Speakers
Jason Castaneda
Executive Director, Account Management, Schrödinger
Márton Vass
Senior Principal Applications Scientist, Schrödinger
Márton Vass is the Global Lead of the All Access Applications Science team at Schrödinger. He works on the development and deployment of scientific workflows in LiveDesign, with special focus on FEP+ and Desmond MD in LiveDesign, and his research is focussed on automating the use of ML protein folding and cofolding methods for drug discovery applications. Before joining Schrödinger Márton received his PhD at the Budapest University of Technology and Economics while working at Gedeon Richer Plc mid-sized pharmaceutical company. He also held a postdoctoral position at the Vrije Universiteit Amsterdam implementing cheminformatics algorithms for GPCR drug discovery in Knime, after which he joined BenevolentAI in London to apply machine learning augmented drug discovery methodologies, and to lead the development of protein structure-based machine learning tools in the company.
