
Sustainable Nanomaterials for Drug Delivery and Biomedical Innovation
Designing the Future of Medicine through Sustainable Nanotechnology and Intelligent Drug Delivery
Skills you will gain:
About Program:
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.
Program 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.
What you will learn?
Day 1: Foundations of Sustainable Nanomedicine
- Introduction to Nanomaterials: Types and classifications (e.g., liposomes, dendrimers, carbon nanotubes)
- Principles of Biological Nanomaterials as Sustainable, Eco-friendly and biocompatible
- Green synthesis of nanomaterials and its advantages
- Different Systems of Drug Delivery: Encapsulation
- Tools: Design & Visualization Tools: BioRender, PubChem/ChemSpider,
- 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: PDB,RDKit, Scikit-learn (for basic modeling), Pandas, SwissModel 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 nano-medicine
- Challenges and Future Trends in Translating Nanomaterials to Clinics: Scale-up, stability, safety, patient-specific factors and personalized medicine
- Tools: pkCSM, SwissTargetPrediction, FormSCI, SwissADME, Tensor Flow/Keras (for data analysis), Streamlit (for creating simple UIs),
Mentor Profile
Fee Plan
Get an e-Certificate of Participation!

Intended For :
- 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.
Career Supporting Skills
Program 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.
