In this episode I am joined by Paul Thomas, founder of Kreatis, a company that specialises in developing in silico tools for predicting chemical properties and hazard endpoints.

Join us for an interesting conversation covering:

• Paul’s early career and experiences with building a company
• Quantitative structure activity relationship (QSAR) models for predicting chemical properties
• The role of QSARs for reducing animal testing
• The role of QSARs in the new approach methodologies (NAMs) discussion
• The new QSAR Assessment Framework (QAF) and validating predictions for regulatory use
• Publicly available chemical databases and their importance for QSAR development
• Innovation in QSARs, and balancing protecting commercial interests with the need for transparency

More information about Kreatis: KREATiS - Experts in Computational (Eco)Toxicology

The QSAR Assessment Framework: (Q)SAR Assessment Framework: Guidance for the regulatory assessment of (Quantitative) Structure Activity Relationship models and predictions | OECD

Correction:

In this episode, Paul and I discussed the concept of FAIR data, in which I identify the ‘F’ term as ‘freely available’. The correct term is 'findable' (FAIR stands for Findable, Accessible, Interoperable and Reusable). More information on the FAIR principles can be found here: https://www.go-fair.org/fair-principles/