
Cellular Digital Twin for Precision Nano-Theranostics
Simulating Cells, Optimizing Nanotherapy—The Future of Precision Theranostics
Skills you will gain:
About Program:
Nano-theranostics combines targeted drug delivery, imaging, and therapy into a single nanoscale platform, offering powerful solutions for cancer and complex diseases. However, patient-to-patient variability, tumor heterogeneity, immune interactions, and toxicity concerns make nanomedicine development highly challenging. Cellular digital twins—virtual computational replicas of cellular systems—provide a next-generation approach to simulate how cells respond to nanocarriers, drugs, and microenvironment conditions before clinical translation.
This workshop explores how AI-powered digital twin models integrate genomic, proteomic, imaging, and clinical data to predict therapeutic response, nanoparticle uptake, toxicity risk, and treatment outcomes. Participants will learn dry-lab workflows for building simplified cellular twin models, applying predictive analytics, and understanding how digital twins accelerate nanotherapeutic design. The program emphasizes future-ready applications in precision oncology, personalized nanomedicine, and safe-by-design nano-therapeutics.
Aim:
This workshop aims to introduce participants to the concept of cellular digital twins and their transformative role in precision nano-theranostics. It focuses on how computational models, AI, and multi-omics data can simulate cellular behavior to optimize nanoparticle-based diagnosis and targeted therapy. Participants will learn how digital twin frameworks support personalized treatment design and safer nanomedicine development. The program bridges nanotechnology, systems biology, and AI-driven precision healthcare.
Program Objectives:
- Understand the concept and architecture of cellular digital twins.
- Learn how nano-theranostic systems interact with cellular pathways.
- Explore AI-driven prediction of nanoparticle uptake, efficacy, and toxicity.
- Integrate multi-omics and imaging data into digital twin frameworks.
- Study personalized and safe-by-design strategies for nano-therapeutic development.
What you will learn?
Day 1: Foundations of Cellular Digital Twins & Multi-Omics Integration
- What is a Cellular Digital Twin? (CDT architecture: data + model + feedback loop)
- Static vs Dynamic Biological Models (ODE, agent-based, hybrid models)
- Role of CDTs in Precision Nanomedicine & Personalized Therapy
- Case studies from literature (tumor microenvironment modeling, patient-specific simulations)
- Hands-On : Load real dataset (e.g., TCGA / GEO RNA-seq), Perform preprocessing & normalization
- Hands-On : Apply PCA/UMAP for cell-state visualization, basic cellular state map, Gene interaction network (GIN)
Day 2: Modeling Nano-Therapeutic Interactions in a Digital Cell
- Nano-theranostics overview (drug delivery + diagnostics integration)
- Nanoparticle-cell interaction mechanisms: Endocytosis pathways & Surface functionalization & targeting ligands
- Receptor-ligand binding models, Systems pharmacology basics
- Pathway modeling: KEGG / Reactome pathways
- Signal transduction under nanoparticle influence, Drug perturbation modeling & Dose-response curve modeling
- Computational Modeling: Gene Regulatory Networks (GRNs)
Day 3: Real-Time Updating, Uncertainty & Precision Decision Systems
- Predictive response modeling
- Clinical decision support systems (CDSS)
- Digital twin-guided therapy optimization
- Ethical & regulatory considerations (FDA digital twin frameworks)
- Simulate nanoparticle interaction with a cell pathway
- Model drug-induced gene expression changes
- Hands On Tools: Python/PyMC/Numpy/ Scipy
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
Participants will be able to:
- Explain how cellular digital twins enable precision nano-theranostics.
- Identify key biological and nano-scale parameters influencing therapy response.
- Apply AI concepts to predict efficacy, uptake, and safety of nanocarriers.
- Understand integration of omics + imaging data into digital twin models.
- Propose personalized nano-therapeutic strategies supported by simulations.
