First look: Guide your compound design strategy with new visual, industry-leading affinity predictions
Accurate predictions of binding affinity are the holy grail of early-phase discovery, enabling teams to significantly reduce the synthesis and…
In this webinar, Peter Hunt and Matthew Segall examine the effective use of QSAR modelling in drug discovery and discuss a variety of pain points for medicinal chemists in knowing when a model can be trusted and how to avoid common pitfalls. We discuss key learning points for the successful use of QSAR models and how they can be used to make better decisions in a multi-parameter optimisation workflow to select and design high-quality compounds for your projects.
Topics for discussion include:
- What is a QSAR model?
- How do you assess and compare models?
- The limitations of data for modelling and validation
- Where can I use a model? Local vs Global models
- How can I make the best use of imperfect models?
- How do I know if a model prediction is good enough to use in practice?
- Effectively guiding compound design
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