How to perform fast and accurate 3D ligand-based affinity predictions
Binding affinity prediction continues to be a challenge in computer-aided drug design, especially in the absence of a high-quality target…
In this webinar, we explore how the limitations of pharmaceutical data can impact conventional predictive model building. Our speakers, Julian Levell (Constellation pharmaceuticals), Ben Irwin and matt Segall (Optibrium) demonstrate how the deep learning imputation algorithm underlying our Cerella platform, overcomes these challenges.
Walking through case studies from a collaboration between Constellation Pharmaceuticals and Optibrium on applying deep learning imputation to project data, we see the impact our methods can bring at all stages from early screening of datasets over temporal validation to later stage models, larger applications and the potential of this cutting-edge technology for future projects.
