AI in Nanotoxicology & Safe-by-Design Nanomaterials
Ensuring Safe Nanomaterials for a Healthier Future with AI
About This Course
Nanotoxicology plays a crucial role in evaluating the safety of nanomaterials, especially with their growing use in industries such as healthcare, electronics, and manufacturing. This workshop focuses on understanding the mechanisms of nanotoxicity and integrating artificial intelligence (AI) to predict potential hazards. AI models can aid in identifying toxicological properties, which is essential for developing nanomaterials that are safe for human health and the environment.
The workshop will provide hands-on experience with AI tools for toxicity prediction, regulatory considerations, and safe-by-design nanomaterials. Day one introduces the basics of nanotoxicology, regulatory frameworks, and the role of AI in safety prediction. Day two focuses on the practical use of AI in toxicity prediction, with machine learning models to classify nanomaterial hazards. Day three explores the application of safe-by-design strategies in nanomaterial development and industry adoption.
Aim
This workshop aims to equip participants with knowledge and skills to assess the safety of nanomaterials using AI-based approaches. It covers the regulatory landscape, risk assessment models, and safe-by-design strategies. The focus is on applying AI in nanotoxicology for predicting toxicity and ensuring the development of safe nanomaterials.
Workshop Objectives
- Learn the fundamentals of nanotoxicology and its relevance in nanomaterial safety.
- Understand the role of AI in predicting the toxicity of nanomaterials.
- Gain hands-on experience with machine learning models for hazard classification.
- Explore regulatory requirements for safe nanomaterial development.
- Apply safe-by-design strategies to nanomaterial development pipelines.
Workshop Structure
Day 1 – Basics of Nanotoxicology & Regulatory Requirements
- Introduction to nanotoxicology and its importance in product safety
- Understanding nanomaterial risk assessment models
- The role of AI in predicting nanotoxicity
- Regulatory frameworks for safe-by-design nanomaterials
Day 2 – AI-Based Nanomaterial Safety Prediction
- AI for predicting cytotoxicity and environmental impact of nanomaterials
- Machine learning models for nanomaterial hazard classification
- Demonstration: Running toxicity prediction models using Python and open-source tools
- Data challenges: Variability in toxicity data and how AI handles it
Day 3 – Safe-by-Design Nanomaterials: Practical Applications & Industry Adoption
- Design strategies for developing safe nanomaterials using AI
- Integrating AI safety models into nanomaterial development pipelines
- Regulatory bodies and AI: How they view AI predictions for nanomaterials
- Capstone Discussion: Drafting a safe-by-design strategy using AI for new nanomaterials
Who Should Enrol?
- Undergraduate/postgraduate degree in Nanotechnology, Toxicology, Environmental Science, Chemistry, or related fields.
- Professionals in healthcare, pharma, diagnostics, environmental safety, or regulatory sectors.
- Data scientists and AI/ML engineers interested in applying their skills in nanotoxicology and safety assessment.
- Individuals with an interest in sustainable, safe nanomaterial development.
Important Dates
Registration Ends
09/15/2025
IST 6:00 PM
Workshop Dates
09/15/2025 – 09/17/2025
IST 7:00 PM
Workshop Outcomes
- Ability to assess and predict the toxicity of nanomaterials using AI models.
- Understanding of the regulatory landscape and safety requirements for nanomaterials.
- Hands-on skills in applying machine learning for hazard classification and risk assessment.
- Knowledge of integrating AI safety models in nanomaterial development pipelines.
- Practical understanding of safe-by-design strategies for sustainable nanotechnology.
Fee Structure
Student Fee
₹1399 | $50
Ph.D. Scholar / Researcher Fee
₹1699 | $55
Academician / Faculty Fee
₹2199 | $60
Industry Professional Fee
₹2699 | $85
What You’ll Gain
- Live & recorded sessions
- e-Certificate upon completion
- Post-workshop query support
- Hands-on learning experience
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