#shef2023 Lauren Reid (MedChemica) on SARkush: Automated Markush-like Structure Generation using Matched Pairs and Generic Atom Scaffolds

#shef2023 Rajarshi Guha (Vertex) on Virtual Screening of Virtual Libraries using a Genetic Algorithm

#shef2023 Tuomo Kalliokoski (Orion) on Efficient SBVS of ultra-large enumerated chemical spaces using machine learning boosted docking (HASTEN)

#shef2023 Moritz Walter (BI) on Integrating heterogeneous assay data for ML-based ADME prediction

#shef2023 Uschi Dolfus (Hamburg) on Full modification control over retrosynthetic routes for guided opt of lead structures

#shef2023 Max Beckers (NIBR) on Leveraging Large-scale in silico ADMET Predictions to Estimate Small Molecule Developability

#shef2023 Marc Lehner (ETH) on DASH: Dynamic attention-based substructure hierarchy for partial charge assignment

#shef2023 Sebastien Guesné (Lhasa) on Beyond balanced accuracy: Balanced Matthews' Correlation Coefficient

#shef2023 Richard Gowers on The Open Free Energy Consortium

#shef2023 David Palmer (Uni Strathclyde) on Simultaneous Entropy, Enthalpy and Free Energy Prediction using a Physics-Informed Neural Network and Multi-task Learning.

#shef2023 Adele Hardie (Uni Edinburgh) on an sMD/MSM approach for rational design of allosteric modulators.