Modelling targeted delivery of biomimetic polymer vesicle gene therapy to cancer

  • Webb, Steven (Principal Investigator)

Project: Research

Project Details


The aim of the project is to assess the feasibility of using nanoparticles to deliver chemotherapeutic drugs to cancer cells. The nanoparticles are synthetic and designed to encapsulate drugs and carry specific markers that target toxic effects efficiently to the tumour cells while protecting other tissues, and thus reducing systemic toxicity. The nanoparticles in question differ to other synthetic delivery devices in terms of their greater loading capacity, improved drug retention and better targeting efficiency. The biggest challenge in their design, however, is how to optimize their specificity of action. We will develop novel mathematical models to tackle this issue. We will use the latest modeling techniques to discover how infiltration, targeting and uptake of the nanoparticles are regulated by their size, mechanical, chemical and membrane properties. Data generated from in vitro lab experiments with the head and neck cancers will be used to inform the mathematical approach for parameterisation and validation. We will then extend the validated models to predict the therapeutic effect in tumours in vivo, focussing on tumours that have acquired a blood supply and developing a model framework which will help focus an in vivo experimental program before animal studies begin. This will permit the investigation of different experimental situations which are technically difficult and the collection of data limited, at a minimum of cost and use of animal models. These targeting issues are relevant to the delivery field in general so our model will also act as a framework for targeted delivery for other tumours as well as other pathologic conditions. The aims of the project are:(i) To develop novel mathematical models of ligand-receptor binding of nanoparticles to cancer cells to predict how targeting can be enhanced by modulating the numbers of ligands and 'stealth' particles on the nanoparticles.(ii) To use data generated from cancer cell culture experiments to parameterise and validate the mathematical models and assess infiltration and delivery patterns in cell populations andidentify conditions of non-specific and actual targeting.(iii) To develop spatio-temporal partial differential equation models to make predictions about nanoparticle stability and therapeutic efficiency given different particle sizes, fluidity and membrane properties and different loads and combinations of cytotoxic drugs with different hydrophobic-hydrophilic properties.(iv) To modify the mathematical models to determine whether acidic tumour conditions can trigger premature release of the vesicle contents.(v) To utilize the mathematical models to inform in vivo experimentation by generating testable hypotheses for determining therapeutic efficiency.

Key findings

"Development of an analytically tractable statistical moment closure system describing the binding and uptake of ligand-coated nanoparticles into tumour cells.

Development of a dynamic Monte Carlo model for nanoparticle uptake that predicts the critical effects of statistical variances in batch-to-batch variability on uptake.

Development of a biomechanical model for nanoparticle uptake into avascular tumours that can be used to investigate infiltration patterns and treatment efficacy given different particle sizes and membrane properties.

Theoretical predictions that explain differences in uptake between different cell lines and the critical dependency of uptake rate on cell receptor expression.

Theoretical predictions to suggest that differences between cell endocytosis rates are unlikely to be responsible for the observed cell-to-cell differences in polymersome uptake.

Theoretical predictions for co-cultures of multiple cell types that show the same polymersome uptake as cells cultured in isolation. This was confirmed by experimental studies.

Polymersome uptake by cells in serum conditions was shown to be lower than uptake in serum free conditions.

Development of a 3D in vivo computational model that will inform how to tune the surface chemistry of the BPVs to maximise the treatment efficacy."
Effective start/end date1/04/1131/05/12


  • EPSRC (Engineering and Physical Sciences Research Council): £96,037.00


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