ChemoPredictionAcademy

Machine learning methods for drug discovery and toxicology: How to develop a QSAR model using Python.

This course will provide you with the tools and knowledge necessary to develop your own QSAR models for bioactivity or toxicology prediction. You will learn to use open libraries to create your customized Python scripts, enabling you to construct these models effectively. You will learn the theoretical background about QSAR modelling and the general workflow to develop the model: including the rationale of the different steps and the tools to implement them. Covering data management and curation, calculation and selection of molecular descriptors, different machine-learning algorithms, the statistical evaluation of the models and the evaluation of the applicability domain.

This is an online course that allows you to learn at your own pace. Our platform provides access to recorded lessons, written explanations, interactive Python exercises and supplementary resources. The course emphasizes practical learning, with several hands-on exercises and finishing with a project where you will develop a whole QSAR model by yourself. But you are not alone, you will be guided by a tutor from ProtoQSAR that will follow your advance on the platform, give you feedback in your assignments and remain reachable by e-mail. Additionally, you will be able to engage with fellow learners and instructors through internal forums and chats, and a series of live videoconferences will be organized to address any queries or concerns.

Prerequisites: The tasks require a basic knowledge of Python (additional learning resources and links to external resources will be provided in the platform for begginers).

For more information regarding the contents and the registration visit:https://protoqsar.com/formacion/

Direct link to the registration form https://forms.gle/PDZUVjFubCJU8o4q6

This online course provides comprehensive training in the theoretical and practical aspects of (Q)SAR and read-across techniques, focusing on their application in regulatory contexts. In the first section, we will review the main features of key regulations for chemical products and how they incorporate in silico methods. Then, participants will learn to use various computational tools to make chemical safety predictions and informed decisions. The course combines theoretical lessons with practical exercises designed to reinforce learning and facilitate the application of these methods in real-world regulatory scenarios.

• Module 1: Regulatory aspects for the registration of chemical products
• Module 2: Computational methods in regulatory chemistry
• 2.1 Introduction to computational methods
• 2.2 Analogs and read across with QSAR Toolbox
• 2.3 QSAR with different prediction platforms

For more details, please download the course content .

Date: Starting on 15 February 2025	Modality: Online
Price: 900€*	Language: English

*A 50% discount will be applied to accredited students. Discounts for groups are available.

Pre-registration: Fill out the following FORM

Contact: training@protoqsar.com