Computational Nanomaterial Design for Drug Delivery: Molecular Modelling & Simulation

Aim

Workshop Objectives

Workshop Structure

Day 1 – Computational Nanomaterial Design & Drug–Carrier Interactions

Focus: Understanding nanomaterial properties and selecting suitable drug delivery systems through computational analysis.

• Introduction to computational nanomaterial design for drug delivery applications.
• Overview of polymeric nanoparticles, lipid nanocarriers, and inorganic nanomaterials.
• Nanomaterial properties: particle size, surface chemistry, stability, and biocompatibility.
• Drug–carrier compatibility: solubility, polarity, hydrogen bonding, and hydrophobic interactions.
• Molecular structure preparation and physicochemical descriptor analysis using RDKit.
• Selection of a model drug and polymeric nanocarrier for molecular simulation.

Hands-On Lab: Molecular Structure Analysis & Computational Nanocarrier Selection

Calculate drug molecular descriptors, visualise molecular structures, and compare candidate carrier materials using a guided Python notebook.

Deliverable: Molecular property analysis and nanocarrier selection report.

Tools: Google Colab | Python | RDKit

Day 2 – Molecular Modelling, Molecular Dynamics & Nanomaterial Stability

Focus: Applying molecular simulation techniques to investigate drug–nanomaterial interactions and structural behaviour.

• Fundamentals of molecular mechanics, force fields, and molecular dynamics simulations.
• Atomistic and coarse-grained modelling approaches for nanomaterials.
• Preparation of a simplified drug–polymer molecular simulation system.
• Energy minimisation, solvation, equilibration, and simulation parameters.
• Analysis of molecular trajectories, structural stability, and drug–carrier contacts.
• Evaluation of molecular interactions through RMSD, radius of gyration, and hydrogen-bond analysis.
• Interpretation of simulation results and their limitations in nanocarrier design.

Hands-On Lab: Molecular Dynamics Simulation of Drug–Polymer Interactions

Run a guided short molecular dynamics simulation using a prepared molecular system and analyse precomputed simulation trajectories.

Deliverable: Molecular simulation results, structural plots, and drug–carrier interaction analysis.

Tools: OpenMM | Google Colab | Python | MDTraj

Day 3 – Drug Release Modelling, Nanocarrier Optimisation & Formulation Evaluation

Focus: Connecting molecular simulation results with controlled drug-release behaviour and computational formulation evaluation.

• Drug encapsulation, diffusion, polymer degradation, and controlled-release mechanisms.
• Influence of nanomaterial composition, surface properties, and drug–carrier interactions on formulation performance.
• Drug-release kinetic models: Higuchi and Korsmeyer–Peppas.
• Computational analysis of experimental drug-release profiles.
• Comparison of candidate nanocarriers using molecular and release-related properties.
• Nanocarrier optimisation considerations: stability, loading, release behaviour, and biocompatibility.
• Experimental validation requirements and limitations of computational predictions.

Hands-On Lab: Drug Release Kinetics & Computational Nanocarrier Evaluation

Analyse provided drug-release datasets, fit suitable kinetic models, compare formulation behaviour, and prepare an evidence-based nanocarrier evaluation report.

Deliverable: Drug-release plots, kinetic model results, and final nanocarrier evaluation report.

Tools: Python | Google Colab | NumPy | SciPy | Matplotlib

Who Should Enrol?

Important Dates

Workshop Outcomes

Fee Structure