Sustainable Nanomaterials for Drug Delivery and Biomedical Innovation
Designing the Future of Medicine through Sustainable Nanotechnology and Intelligent Drug Delivery
About This Course
This three-day workshop (1.5-hour lecture per day) provides a comprehensive introduction to sustainable nanomaterials for drug delivery and biomedical innovation, integrating green synthesis principles, advanced characterization techniques, and AI-driven optimization strategies. Participants will explore nanocarriers such as Liposome, Dendrimer, and Carbon Nanotube, while gaining practical exposure to computational tools including Python, RDKit, Scikit-learn, and TensorFlow. The program bridges foundational science, translational challenges, regulatory considerations, and future trends such as personalized nanomedicine and AI-powered drug design, preparing participants for research and industry applications.
Aim
To provide foundational knowledge and practical insight into the design, characterization, optimization, and clinical translation of sustainable nanomaterials for advanced drug delivery systems.
Workshop Objectives
- Understand classifications and biomedical applications of nanomaterials.
- Learn principles of eco-friendly and sustainable nanomaterial synthesis.
- Explore drug delivery fundamentals including encapsulation and release kinetics.
- Gain knowledge of advanced characterization techniques (TEM, SEM, AFM).
- Apply data analysis and basic machine learning tools for nanomaterial optimization.
- Understand regulatory frameworks including U.S. Food and Drug Administration guidelines.
- Analyze translational challenges and future trends in nanomedicine.
Workshop Structure
Day 1: Foundations of Sustainable Nanomedicine
- Introduction to Nanomaterials in Medicine: Types and classifications (e.g., liposomes, dendrimers, carbon nanotubes)
- Principles of sustainable nanomaterial design: Eco-friendly and biocompatible approaches
- Green synthesis of nanomaterials: Methods, challenges, and advantages
- Fundamentals of drug delivery systems: Encapsulation, release kinetics, and bioavailability
- Tools: Python (for basic modeling), Pandas, Matplotlib (for plotting), Colab/Jupyter (for interactive coding)
Day 2: Design, Characterization & Optimization
- Nanomaterial Design for Drug Delivery: Structure-property relationships and targeting strategies
- Characterization of Nanomaterials: Surface charge, morphology, size distribution, and stability analysis
- Advanced Techniques for Nanomaterial Characterization:
Transmission Electron Microscopy (TEM),Scanning Electron Microscopy (SEM), Atomic Force Microscopy (AFM) - Optimization of Nanocarriers: Influence of size, shape, and surface modification on drug loading and release
- Tools: RDKit, Scikit-learn (for basic modeling), Pandas, NumPy, Jupyter/Colab, Matplotlib for data visualization
Day 3: Applications, Translation & Future Directions
- Clinical Applications of Nanomedicine: Targeted drug delivery, cancer therapy, and gene delivery
- Regulatory Considerations: FDA guidelines and global regulatory bodies for nanomedicine
- Challenges in Translating Nanomaterials to Clinics: Scale-up, stability, safety, and patient-specific factors
- Future Trends in Nanomedicine: Personalized medicine, smart nanomaterials, and AI-powered drug design
- Tools: TensorFlow/Keras (for data analysis), Streamlit (for creating simple UIs), Scikit-learn (for model deployment)
Who Should Enrol?
- Doctoral Scholars & Researchers: PhD candidates seeking to integrate computational workflows into their molecular research.
- Postdoctoral Fellows: Early-career scientists aiming to enhance their data-driven publication profile.
- University Faculty: Professors and HODs interested in modern bioinformatics pedagogy and tool mastery.
- Industry Scientists: R&D professionals from the Biotechnology and Pharmaceutical sectors transitioning to genomic-driven discovery.
- Postgraduate Students: Final-year PG students looking for specialized research-grade exposure beyond standard curricula.
Important Dates
Registration Ends
02/17/2026
IST 07:00 PM
Workshop Dates
02/17/2026 – 02/19/2026
IST 08:00 PM
Workshop Outcomes
By the end of the workshop, participants will be able to:
- Explain structure–property relationships in nanocarrier systems.
- Evaluate sustainable synthesis approaches for biomedical nanomaterials.
- Interpret nanomaterial characterization data (size, morphology, surface charge).
- Perform basic computational modeling and visualization using Python tools.
- Understand clinical translation pathways and regulatory considerations.
- Identify future research directions in smart and AI-driven nanomedicine.
Fee Structure
Student Fee
₹1699 | $65
Ph.D. Scholar / Researcher Fee
₹2699 | $75
Academician / Faculty Fee
₹3699 | $85
Industry Professional Fee
₹4699 | $95
What You’ll Gain
- Live & recorded sessions
- e-Certificate upon completion
- Post-workshop query support
- Hands-on learning experience
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