Course on in silico methods in the safety assessment of chemicals
The course covers various topics related to using in silico (computer-based) methods to assess the safety of chemicals. It provides training on machine learning methods, databases, molecular descriptors, similarity analysis, read-across approach, and QSAR/QSPR modeling. These methods are widely used in the assessment of chemical properties, toxicity, and potential risks associated with chemical substances.
The course is in English (or Polish – if the whole group of participants will be Polish-speaking).
Date and place
*Price includes: participation in classes, training materials, certificate of participation, coffee catering.
Participant will acquire knowledge about databases and learn how to effectively search these resources to find the necessary information. Additionally, they will be introduced to two important types of chemometric analysis, namely Hierarchical Cluster Analysis (HCA) and Principal Component Analysis (PCA). These advanced techniques will enable them to analyze large datasets and present results graphically.
- Introduction to machine learning methods in safety assessment of chemicals
- Databases and data FAIRnes
- Overview of database structure, search methods, types of information,
- Examples of databases (PubChem, ChemSpider)
- Description of a chemical structure and molecular descriptors
- Introduction of descriptor’s group
- Practical exercises – calculation of Lipinski descriptors and 2D descriptors using RDiK pakage
- Similarity analysis: Introduction to PCA and practical exercises
- Similarity analysis: Introduction to HCA and practical exercises
Participant will be gradually introduced to building QSAR/QSPR models. They will learn about the essential data required for this process and the criteria that must be met to utilize the models for regulatory purposes. Apart from the modeling methodology, participants will also learn the practical use of available tools, allowing them to predict the physicochemical and toxicological properties of chemical compounds. These skills will empower them to make more informed decisions regarding the safety assessment of chemical substances.
- Grouping and read-across approach.
- Assumptions of the read-across method
- Criteria of substance similarity
- Read-Across Assessment Framework
- QSAR/QSPR modeling.
- Assumptions of the QSAR/QSPR modeling
- Phases of modeling (calibration, validation, applicability domain, application of the model)
- QMRF reports
- Application of in silico methods in risk assessment of chemicals.
- Introduction to open-source tools to predict the properties of compounds.
- Case study in OECD QSAR Toolbox
- Practical exercise using open-source tools to predict the toxicity of chemicals (VEGA / Danish (Q)SAR Database / T.E.S.T.)
- Preparation of input files
- Analysis with the use of selected software
- Discussion of obtained results (comparing results depending on the tool used, searching for experimental values)