The push for greater productivity and accelerated R&D has led to wider adoption of predictive tools in the lab. Join our short webinar series where experts in the field discuss how to apply ionization (Day 1) and NMR spectral prediction (Day 2) to support confident decision-making and extending their use in today’s digital world.
Day 1: Leveraging Ionization Data in Drug Discovery—A Deep Dive
Elevate your understanding of when and how to apply ionization predictions (calculated pKa values). Industry experts will share insights, case studies, and practical advice to guide decisions that depend on ionization modelling in drug discovery.
- Accuracy requirements differ in early screening, lead optimization, and candidate selection. Learn how to assess the dependencies.
- Prediction or measurement? Understand when you need to measure values, or train algorithms.
- AI-enabled innovation, done right—set your data science projects up for success by ensuring you employ the right descriptors and parameters effectively in SAR modelling.
- Industry collaborations are important to the continual development of prediction algorithms. See highlights of select projects and model validation studies.
- Calculation speed is important for library screening. Hear about the algorithmic changes that have made predictions up to 7-times faster.
Day 2: Driving Decisions from NMR Spectra
Do you predict NMR spectra to confirm or speed up interpretations of experimental spectra? Do you use or want to use automated structure verification (ASV)? Learn how to accelerate your workflows and get more from NMR prediction software. Join NMR experts for practical advice to boost your confidence, improve the accuracy of predicted spectra, and help you tackle more demanding problems. We will discuss:
- Predicting spectra in desktop applications or your browser
- When is training predictive algorithms important?
- Accurate prediction of 2D spectra and optimizing instrument time
- Dealing with mixtures and complex samples (including biosequencing)
- Application of NMR predictions to digitalize analysis workflows
March 6th: Leveraging Ionization Data in Drug Discovery—A Deep Dive
Accounting for Ionization in the Increasingly Digital R&D Paradigm
Andrew Anderson, Vice President of Innovation & Informatics Strategy
Collaborations & Developments that Bring You Industry-Leading Predictive pKa
Kiril Lanevskij, Principal Research Scientist, Percepta
March 7th: Driving Decisions from NMR Spectra
How to Make the Most of Your NMR Predictions
Dimitris Argyropoulos, NMR Business Manager
Digital Reference Materials: Revolutionizing the Way NMR Analysis is Done
Albert Farre Perez, R&D Scientist, MilliporeSigma
Director, Marketing & Communications
Marketing Communications Specialist