New QSAR Modeling Courses

Are you ready to dive into the fascinating world of computational chemistry and make a significant impact in drug discovery and toxicology? Look no further; we’re thrilled to introduce our two cutting-edge courses aimed at equipping you with the skills and knowledge to excel in this dynamic field. Don’t miss out on this incredible opportunity to supercharge your education and career – register today!

Course 1: In Silico Toxicology Predictions for Regulatory Purposes: Introduction to (Q)SAR and Read Across

Are you ready to explore the vital world of in silico toxicology and its critical role in regulatory assessments? Our first course introduces you to the essential concepts of (Quantitative) Structure-Activity Relationship, or (Q)SAR, and Read Across. These techniques are indispensable for predicting the toxicity of chemicals and their regulatory implications.

This course presents three different modules:

  • Module 1: Introduction to computational methods in regulatory chemistry.
  • Module 2: Analogs identification and read-across with QSAR Toolbox.
  • Module 3: (Q)SAR with differents in silico platforms.

(More details about the course can be found here)

With this knowledge, you’ll be prepared to navigate the complex landscape of chemical safety assessments and contribute to crucial regulatory processes.

Don’t miss your chance to be part of the next generation of computational scientists. Register today, and embark on a journey of learning and growth with our innovative courses. Whether you’re an aspiring scientist or a seasoned professional looking to expand your horizons, these courses will equip you with the expertise and confidence to excel in the world of computational chemistry.

Course 2: Machine Learning Methods for Drug Discovery and Toxicology: How to Develop a QSAR Model Using Python

Are you passionate about leveraging the power of data and machine learning in the realm of drug discovery and toxicology? Our second course offers a comprehensive exploration of developing QSAR models using Python. With a strong focus on practical implementation, you’ll learn how to harness Python’s capabilities to predict molecular properties and biological activities.

(More details about the course can be found here)

This online course allows you to learn at your own pace and offers a comprehensive learning platform. It includes recorded lessons, text explanations, interactive Python exercises, and additional resources. The course is highly practical, featuring numerous exercises and culminating in the creation of a complete QSAR model. You will receive guidance from a ProtoQSAR tutor who will provide feedback on your assignments and be reachable via email. You’ll also have the opportunity to engage with your peers and instructors through internal forums, chats, and live videoconferences for any questions or concerns.

Upon completion, you’ll be well-equipped to tackle real-world challenges in the pharmaceutical and toxicology industries, using state-of-the-art machine learning techniques. Don’t miss your chance to be at the forefront of innovation!

 Join us on this exciting adventure, and together, we’ll pave the way for a brighter future in drug discovery, toxicology, and beyond!