
Smart Bioactive Scaffolds for Regenerative Medicine: AI, Bioinformatics & 3D/4D Bioprinting
Designing Intelligent, Data-Driven Biomaterials for Next-Generation Tissue Engineering & Regenerative Medicine
Skills you will gain:
About Program:
This workshop provides an interdisciplinary introduction to smart bioactive scaffolds, advanced biomaterials, 3D/4D bioprinting, bioinformatics, and AI-driven regenerative medicine. Participants will explore how material properties, biological data, bioink engineering, and computational methods can be integrated to design functional and personalized tissue-engineering systems. The program combines fundamental concepts with practical, research-oriented computational workflows.
Aim: To equip participants with the knowledge and practical skills required to understand, design, and optimize smart bioactive scaffolds and bioprinted tissue constructs using advanced biomaterials, biological data, and AI-driven approaches.
Program Objectives:
- Understand key natural, synthetic, composite, and smart biomaterials used in regenerative medicine.
- Learn principles of bioink formulation, rheology, 3D and 4D bioprinting.
- Explore scaffold architecture, cell–material interactions, and tissue-specific design.
- Understand how transcriptomic and single-cell data can inform regenerative medicine research.
- Apply basic AI/ML approaches to biomaterial, bioink, and scaffold optimization.
- Explore data-driven and personalized tissue-engineering strategies.
- Understand emerging applications including organoid-integrated bioprinting and intelligent biofabrication.
What you will learn?
🗓️ Day 1 — Advanced Biomaterials & Scaffold Design
- Fundamentals of tissue engineering and regenerative medicine
- Natural, synthetic, composite and nanocomposite biomaterials
- Scaffold properties: porosity, mechanics, degradation and biocompatibility
- Cell–material interactions and ECM mimicry
- Surface functionalization and bioactive modification
- Smart hydrogels and stimuli-responsive biomaterials
- Tissue-specific scaffold design
🛠️ Hands-On: Data-Driven Biomaterial & Scaffold Design
Task: Compare biomaterials and optimize scaffold formulations based on material and biological properties.
Tools: Google Colab, Python, Pandas, Matplotlib
🗓️ Day 2 — 3D/4D Bioprinting & Advanced Bioinks
- Extrusion-based 3D bioprinting principles
- Bioink formulation, rheology and printability
- Cell-laden and acellular bioinks
- Crosslinking strategies
- Printing parameters and shape fidelity
- Cell viability and shear stress
- Multi-material and multi-cell bioprinting
- Vascularization and complex tissue architectures
- 4D bioprinting and stimuli-responsive constructs
🛠️ Hands-On: AI-Assisted Bioink & Printing Optimization
Task: Optimize printing conditions for printability, structural fidelity and predicted cell viability.
Tools: Python, Pandas, Scikit-learn, Google Colab
🗓️ Day 3 — Bioinformatics, AI & Personalized Regenerative Medicine
- Omics-driven regenerative medicine
- Transcriptomic and single-cell data for tissue regeneration
- Regeneration-associated cell populations and biomarkers
- Cell–material interaction analysis
- AI/ML for scaffold property prediction
- AI-assisted bioink and biomaterial optimization
- Personalized tissue-construct design
- Smart and stimuli-responsive scaffolds
- Organoid-integrated bioprinting
- Clinical translation and future intelligent biofabrication
🛠️ Hands-On: Omics-to-Scaffold: Bioinformatics & AI-Assisted Design
Task: Omics Data → Cell/Marker Identification → Biological Requirements → Scaffold Properties → AI-Assisted Material Selection
Tools: Python, Pandas, Scikit-learn, Google Colab & public biological datas
Mentor Profile
Fee Plan
Get an e-Certificate of Participation!

Intended For :
- PhD Scholars and Researchers
- MSc/MTech/Postgraduate Students
- Biotechnology and Biomedical Science Professionals
- Biomedical, Chemical, Materials, Mechanical and Bioengineering Researchers
- Nanotechnology and Tissue Engineering Researchers
- Professionals working in Biomaterials, 3D Bioprinting and Regenerative Medicine
- Academicians and Industry R&D Professionals
Career Supporting Skills
Program Outcomes
- Select suitable biomaterials based on tissue-engineering requirements.
- Evaluate key scaffold and bioink properties.
- Interpret important 3D/4D bioprinting parameters.
- Analyze biological datasets relevant to tissue regeneration.
- Develop basic computational workflows for scaffold and bioink optimization.
- Connect biological data with material-design decisions.
- Understand emerging approaches in AI-enabled and personalized regenerative medicine.
